explanatory multiple case study

Types of Case Studies

There are several different types of case studies, as well as several types of subjects of case studies. We will investigate each type in this article.

Different Types of Case Studies

There are several types of case studies, each differing from each other based on the hypothesis and/or thesis to be proved. It is also possible for types of case studies to overlap each other.

Each of the following types of cases can be used in any field or discipline. Whether it is psychology, business or the arts, the type of case study can apply to any field.

Explanatory

The explanatory case study focuses on an explanation for a question or a phenomenon. Basically put, an explanatory case study is 1 + 1 = 2. The results are not up for interpretation.

A case study with a person or group would not be explanatory, as with humans, there will always be variables. There are always small variances that cannot be explained.

However, event case studies can be explanatory. For example, let's say a certain automobile has a series of crashes that are caused by faulty brakes. All of the crashes are a result of brakes not being effective on icy roads.

What kind of case study is explanatory? Think of an example of an explanatory case study that could be done today

When developing the case study, the researcher will explain the crash, and the detailed causes of the brake failure. They will investigate what actions caused the brakes to fail, and what actions could have been taken to prevent the failure.

Other car companies could then use this case study to better understand what makes brakes fail. When designing safer products, looking to past failures is an excellent way to ensure similar mistakes are not made.

The same can be said for other safety issues in cars. There was a time when cars did not have seatbelts. The process to get seatbelts required in all cars started with a case study! The same can be said about airbags and collapsible steering columns. They all began with a case study that lead to larger research, and eventual change.

Exploratory

An exploratory case study is usually the precursor to a formal, large-scale research project. The case study's goal is to prove that further investigation is necessary.

For example, an exploratory case study could be done on veterans coming home from active combat. Researchers are aware that these vets have PTSD, and are aware that the actions of war are what cause PTSD. Beyond that, they do not know if certain wartime activities are more likely to contribute to PTSD than others.

For an exploratory case study, the researcher could develop a study that certain war events are more likely to cause PTSD. Once that is demonstrated, a large-scale research project could be done to determine which events are most likely to cause PTSD.

Exploratory case studies are very popular in psychology and the social sciences. Psychologists are always looking for better ways to treat their patients, and exploratory studies allow them to research new ideas or theories.

Multiple-Case Studies or Collective Studies

Multiple case or collective studies use information from different studies to formulate the case for a new study. The use of past studies allows additional information without needing to spend more time and money on additional studies.

Using the PTSD issue again is an excellent example of a collective study. When studying what contributes most to wartime PTSD, a researcher could use case studies from different war. For instance, studies about PTSD in WW2 vets, Persian Gulf War vets, and Vietnam vets could provide an excellent sampling of which wartime activities are most likely to cause PTSD.

If a multiple case study on vets was done with vets from the Vietnam War, the Persian Gulf War, and the Iraq War, and it was determined the vets from Vietnam had much less PTSD, what could be inferred?

Furthermore, this type of study could uncover differences as well. For example, a researcher might find that veterans who serve in the Middle East are more likely to suffer a certain type of ailment. Or perhaps, that veterans who served with large platoons were more likely to suffer from PTSD than veterans who served in smaller platoons.

An intrinsic case study is the study of a case wherein the subject itself is the primary interest. The "Genie" case is an example of this. The study wasn't so much about psychology, but about Genie herself, and how her experiences shaped who she was.

Genie is the topic. Genie is what the researchers are interested in, and what their readers will be most interested in. When the researchers started the study, they didn't know what they would find.

They asked the question…"If a child is never introduced to language during the crucial first years of life, can they acquire language skills when they are older?" When they met Genie, they didn't know the answer to that question.

Instrumental

An instrumental case study uses a case to gain insights into a phenomenon. For example, a researcher interested in child obesity rates might set up a study with middle school students and an exercise program. In this case, the children and the exercise program are not the focus. The focus is learning the relationship between children and exercise, and why certain children become obese.

What is an example of an instrumental case study?

Focus on the results, not the topic!

Types of Subjects of Case Studies

There are generally five different types of case studies, and the subjects that they address. Every case study, whether explanatory or exploratory, or intrinsic or instrumental, fits into one of these five groups. These are:

Person – This type of study focuses on one particular individual. This case study would use several types of research to determine an outcome.

The best example of a person case is the "Genie" case study. Again, "Genie" was a 13-year-old girl who was discovered by social services in Los Angeles in 1970. Her father believed her to be mentally retarded, and therefore locked her in a room without any kind of stimulation. She was never nourished or cared for in any way. If she made a noise, she was beaten.

When "Genie" was discovered, child development specialists wanted to learn as much as possible about how her experiences contributed to her physical, emotional and mental health. They also wanted to learn about her language skills. She had no form of language when she was found, she only grunted. The study would determine whether or not she could learn language skills at the age of 13.

Since Genie was placed in a children's hospital, many different clinicians could observe her. In addition, researchers were able to interview the few people who did have contact with Genie and would be able to gather whatever background information was available.

This case study is still one of the most valuable in all of child development. Since it would be impossible to conduct this type of research with a healthy child, the information garnered from Genie's case is invaluable.

Group – This type of study focuses on a group of people. This could be a family, a group or friends, or even coworkers.

An example of this type of case study would be the uncontacted tribes of Indians in the Peruvian and Brazilian rainforest. These tribes have never had any modern contact. Therefore, there is a great interest to study them.

Scientists would be interested in just about every facet of their lives. How do they cook, how do they make clothing, how do they make tools and weapons. Also, doing psychological and emotional research would be interesting. However, because so few of these tribes exist, no one is contacting them for research. For now, all research is done observationally.

If a researcher wanted to study uncontacted Indian tribes, and could only observe the subjects, what type of observations should be made?

Location – This type of study focuses on a place, and how and why people use the place.

For example, many case studies have been done about Siberia, and the people who live there. Siberia is a cold and barren place in northern Russia, and it is considered the most difficult place to live in the world. Studying the location, and it's weather and people can help other people learn how to live with extreme weather and isolation.

Location studies can also be done on locations that are facing some kind of change. For example, a case study could be done on Alaska, and whether the state is seeing the effects of climate change.

Another type of study that could be done in Alaska is how the environment changes as population increases. Geographers and those interested in population growth often do these case studies.

Organization/Company – This type of study focuses on a business or an organization. This could include the people who work for the company, or an event that occurred at the organization.

An excellent example of this type of case study is Enron. Enron was one of the largest energy company's in the United States, when it was discovered that executives at the company were fraudulently reporting the company's accounting numbers.

Once the fraud was uncovered, investigators discovered willful and systematic corruption that caused the collapse of Enron, as well as their financial auditors, Arthur Andersen. The fraud was so severe that the top executives of the company were sentenced to prison.

This type of case study is used by accountants, auditors, financiers, as well as business students, in order to learn how such a large company could get away with committing such a serious case of corporate fraud for as long as they did. It can also be looked at from a psychological standpoint, as it is interesting to learn why the executives took the large risks that they took.

Most company or organization case studies are done for business purposes. In fact, in many business schools, such as Harvard Business School, students learn by the case method, which is the study of case studies. They learn how to solve business problems by studying the cases of businesses that either survived the same problem, or one that didn't survive the problem.

Event – This type of study focuses on an event, whether cultural or societal, and how it affects those that are affected by it. An example would be the Tylenol cyanide scandal. This event affected Johnson & Johnson, the parent company, as well as the public at large.

The case study would detail the events of the scandal, and more specifically, what management at Johnson & Johnson did to correct the problem. To this day, when a company experiences a large public relations scandal, they look to the Tylenol case study to learn how they managed to survive the scandal.

A very popular topic for case studies was the events of September 11 th . There were studies in almost all of the different types of research studies.

Obviously the event itself was a very popular topic. It was important to learn what lead up to the event, and how best to proven it from happening in the future. These studies are not only important to the U.S. government, but to other governments hoping to prevent terrorism in their countries.

Planning A Case Study

You have decided that you want to research and write a case study. Now what? In this section you will learn how to plan and organize a research case study.

Selecting a Case

The first step is to choose the subject, topic or case. You will want to choose a topic that is interesting to you, and a topic that would be of interest to your potential audience. Ideally you have a passion for the topic, as then you will better understand the issues surrounding the topic, and which resources would be most successful in the study.

You also must choose a topic that would be of interest to a large number of people. You want your case study to reach as large an audience as possible, and a topic that is of interest to just a few people will not have a very large reach. One of the goals of a case study is to reach as many people as possible.

Who is your audience?

Are you trying to reach the layperson? Or are you trying to reach other professionals in your field? Your audience will help determine the topic you choose.

If you are writing a case study that is looking for ways to lower rates of child obesity, who is your audience?

If you are writing a psychology case study, you must consider whether your audience will have the intellectual skills to understand the information in the case. Does your audience know the vocabulary of psychology? Do they understand the processes and structure of the field?

You want your audience to have as much general knowledge as possible. When it comes time to write the case study, you may have to spend some time defining and explaining terms that might be unfamiliar to the audience.

Lastly, when selecting a topic you do not want to choose a topic that is very old. Current topics are always the most interesting, so if your topic is more than 5-10 years old, you might want to consider a newer topic. If you choose an older topic, you must ask yourself what new and valuable information do you bring to the older topic, and is it relevant and necessary.

Determine Research Goals

What type of case study do you plan to do?

An illustrative case study will examine an unfamiliar case in order to help others understand it. For example, a case study of a veteran with PTSD can be used to help new therapists better understand what veterans experience.

An exploratory case study is a preliminary project that will be the precursor to a larger study in the future. For example, a case study could be done challenging the efficacy of different therapy methods for vets with PTSD. Once the study is complete, a larger study could be done on whichever method was most effective.

A critical instance case focuses on a unique case that doesn't have a predetermined purpose. For example, a vet with an incredibly severe case of PTSD could be studied to find ways to treat his condition.

Ethics are a large part of the case study process, and most case studies require ethical approval. This approval usually comes from the institution or department the researcher works for. Many universities and research institutions have ethics oversight departments. They will require you to prove that you will not harm your study subjects or participants.

This should be done even if the case study is on an older subject. Sometimes publishing new studies can cause harm to the original participants. Regardless of your personal feelings, it is essential the project is brought to the ethics department to ensure your project can proceed safely.

Developing the Case Study

Once you have your topic, it is time to start planning and developing the study. This process will be different depending on what type of case study you are planning to do. For thissection, we will assume a psychological case study, as most case studies are based on the psychological model.

Once you have the topic, it is time to ask yourself some questions. What question do you want to answer with the study?

For example, a researcher is considering a case study about PTSD in veterans. The topic is PTSD in veterans. What questions could be asked?

Do veterans from Middle Eastern wars suffer greater instances of PTSD?

Do younger soldiers have higher instances of PTSD?

Does the length of the tour effect the severity of PTSD?

Each of these questions is a viable question, and finding the answers, or the possible answers, would be helpful for both psychologists and veterans who suffer from PTSD.

Research Notebook

1. What is the background of the case study? Who requested the study to be done and why? What industry is the study in, and where will the study take place?

2. What is the problem that needs a solution? What is the situation, and what are the risks?

3. What questions are required to analyze the problem? What questions might the reader of the study have? What questions might colleagues have?

4. What tools are required to analyze the problem? Is data analysis necessary?

5. What is your current knowledge about the problem or situation? How much background information do you need to procure? How will you obtain this background info?

6. What other information do you need to know to successfully complete the study?

7. How do you plan to present the report? Will it be a simple written report, or will you add PowerPoint presentations or images or videos? When is the report due? Are you giving yourself enough time to complete the project?

The research notebook is the heart of the study. Other organizational methods can be utilized, such as Microsoft Excel, but a physical notebook should always be kept as well.

Planning the Research

The most important parts of the case study are:

1. The case study's questions

2. The study's propositions

3. How information and data will be analyzed

4. The logic behind the propositions

5. How the findings will be interpreted

The study's questions should be either a "how" or "why" question, and their definition is the researchers first job. These questions will help determine the study's goals.

Not every case study has a proposition. If you are doing an exploratory study, you will not have propositions. Instead, you will have a stated purpose, which will determine whether your study is successful, or not.

How the information will be analyzed will depend on what the topic is. This would vary depending on whether it was a person, group, or organization.

When setting up your research, you will want to follow case study protocol. The protocol should have the following sections:

1. An overview of the case study, including the objectives, topic and issues.

2. Procedures for gathering information and conducting interviews.

3. Questions that will be asked during interviews and data collection.

4. A guide for the final case study report.

When deciding upon which research methods to use, these are the most important:

1. Documents and archival records

2. Interviews

3. Direct observations

4. Indirect observations, or observations of subjects

5. Physical artifacts and tools

Documents could include almost anything, including letters, memos, newspaper articles, Internet articles, other case studies, or any other document germane to the study.

Archival records can include military and service records, company or business records, survey data or census information.

Research Strategy

Before beginning the study you want a clear research strategy. Your best chance at success will be if you use an outline that describes how you will gather your data and how you will answer your research questions.

The researcher should create a list with four or five bullet points that need answers. Consider the approaches for these questions, and the different perspectives you could take.

The researcher should then choose at least two data sources (ideally more). These sources could include interviews, Internet research, and fieldwork or report collection. The more data sources used, the better the quality of the final data.

The researcher then must formulate interview questions that will result in detailed and in-depth answers that will help meet the research goals. A list of 15-20 questions is a good start, but these can and will change as the process flows.

Planning Interviews

The interview process is one of the most important parts of the case study process. But before this can begin, it is imperative the researcher gets informed consent from the subjects.

The process of informed consent means the subject understands their role in the study, and that their story will be used in the case study. You will want to have each subject complete a consent form.

The researcher must explain what the study is trying to achieve, and how their contribution will help the study. If necessary, assure the subject that their information will remain private if requested, and they do not need to use their real name if they are not comfortable with that. Pseudonyms are commonly used in case studies.

Informed Consent

The process by which permission is granted before beginning medical or psychological research

A fictitious name used to hide ones identity

It is important the researcher is clear regarding the expectations of the study participation. For example, are they comfortable on camera? Do they mind if their photo is used in the final written study.

Interviews are one of the most important sources of information for case studies. There are several types of interviews. They are:

Open-ended – This type of interview has the interviewer and subject talking to each other about the subject. The interviewer asks questions, and the subject answers them. But the subject can elaborate and add information whenever they see fit.

A researcher might meet with a subject multiple times, and use the open-ended method. This can be a great way to gain insight into events. However, the researcher mustn't rely solely on the information from the one subject, and be sure to have multiple sources.

Focused – This type of interview is used when the subject is interviewed for a short period of time, and answers a set of questions. This type of interview could be used to verify information learned in an open-ended interview with another subject. Focused interviews are normally done to confirm information, not to gain new information.

Structured – Structured interviews are similar to surveys. These are usually used when collecting data for large groups, like neighborhoods. The questions are decided before hand, and the expected answers are usually simple.

When conducting interviews, the answers are obviously important. But just as important are the observations that can be made. This is one of the reasons in-person interviews are preferable over phone interviews, or Internet or mail surveys.

Ideally, when conducing in-person interviews, more than one researcher should be present. This allows one researcher to focus on observing while the other is interviewing. This is particularly important when interviewing large groups of people.

The researcher must understand going into the case study that the information gained from the interviews might not be valuable. It is possible that once the interviews are completed, the information gained is not relevant.

• Course Catalog
• Group Discounts
• Gift Certificates
• For Libraries
• CEU Verification
• Medical Terminology
• Accounting Course
• Writing Basics
• QuickBooks Training
• Proofreading Class
• Sensitivity Training
• Excel Certificate
• Teach Online
• Terms of Service
• Privacy Policy

The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

Whatever field you're in, ATLAS.ti puts your data to work for you

Download a free trial of ATLAS.ti to turn your data into insights.

Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

Ready to jumpstart your research with ATLAS.ti?

Conceptualize your research project with our intuitive data analysis interface. Download a free trial today.

Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

Ready to analyze your data with ATLAS.ti?

See how our intuitive software can draw key insights from your data with a free trial today.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

Prevent plagiarism. Run a free check.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, November 20). What Is a Case Study? | Definition, Examples & Methods. Scribbr. Retrieved March 25, 2024, from https://www.scribbr.com/methodology/case-study/

Is this article helpful?

Shona McCombes

Other students also liked, primary vs. secondary sources | difference & examples, what is a theoretical framework | guide to organizing, what is action research | definition & examples, what is your plagiarism score.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 25 March 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

Is this article helpful?

Shona McCombes

Other students also liked, correlational research | guide, design & examples, a quick guide to experimental design | 5 steps & examples, descriptive research design | definition, methods & examples.

• Privacy Policy

Buy Me a Coffee

Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Questionnaire – Definition, Types, and Examples

Observational Research – Methods and Guide

Quantitative Research – Methods, Types and...

Qualitative Research Methods

Explanatory Research – Types, Methods, Guide

Survey Research – Types, Methods, Examples

• Open access
• Published: 10 November 2020

Case study research for better evaluations of complex interventions: rationale and challenges

• Sara Paparini   ORCID: orcid.org/0000-0002-1909-2481 1 ,
• Judith Green 2 ,
• Chrysanthi Papoutsi 1 ,
• Jamie Murdoch 3 ,
• Mark Petticrew 4 ,
• Trish Greenhalgh 1 ,
• Benjamin Hanckel 5 &
• Sara Shaw 1  

BMC Medicine volume  18 , Article number:  301 ( 2020 ) Cite this article

17k Accesses

39 Citations

35 Altmetric

Metrics details

The need for better methods for evaluation in health research has been widely recognised. The ‘complexity turn’ has drawn attention to the limitations of relying on causal inference from randomised controlled trials alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes. We argue that case study research—currently denigrated as poor evidence—is an under-utilised resource for not only providing evidence about context and transferability, but also for helping strengthen causal inferences when pathways between intervention and effects are likely to be non-linear.

Case study research, as an overall approach, is based on in-depth explorations of complex phenomena in their natural, or real-life, settings. Empirical case studies typically enable dynamic understanding of complex challenges and provide evidence about causal mechanisms and the necessary and sufficient conditions (contexts) for intervention implementation and effects. This is essential evidence not just for researchers concerned about internal and external validity, but also research users in policy and practice who need to know what the likely effects of complex programmes or interventions will be in their settings. The health sciences have much to learn from scholarship on case study methodology in the social sciences. However, there are multiple challenges in fully exploiting the potential learning from case study research. First are misconceptions that case study research can only provide exploratory or descriptive evidence. Second, there is little consensus about what a case study is, and considerable diversity in how empirical case studies are conducted and reported. Finally, as case study researchers typically (and appropriately) focus on thick description (that captures contextual detail), it can be challenging to identify the key messages related to intervention evaluation from case study reports.

Whilst the diversity of published case studies in health services and public health research is rich and productive, we recommend further clarity and specific methodological guidance for those reporting case study research for evaluation audiences.

Peer Review reports

The need for methodological development to address the most urgent challenges in health research has been well-documented. Many of the most pressing questions for public health research, where the focus is on system-level determinants [ 1 , 2 ], and for health services research, where provisions typically vary across sites and are provided through interlocking networks of services [ 3 ], require methodological approaches that can attend to complexity. The need for methodological advance has arisen, in part, as a result of the diminishing returns from randomised controlled trials (RCTs) where they have been used to answer questions about the effects of interventions in complex systems [ 4 , 5 , 6 ]. In conditions of complexity, there is limited value in maintaining the current orientation to experimental trial designs in the health sciences as providing ‘gold standard’ evidence of effect.

There are increasing calls for methodological pluralism [ 7 , 8 ], with the recognition that complex intervention and context are not easily or usefully separated (as is often the situation when using trial design), and that system interruptions may have effects that are not reducible to linear causal pathways between intervention and outcome. These calls are reflected in a shifting and contested discourse of trial design, seen with the emergence of realist [ 9 ], adaptive and hybrid (types 1, 2 and 3) [ 10 , 11 ] trials that blend studies of effectiveness with a close consideration of the contexts of implementation. Similarly, process evaluation has now become a core component of complex healthcare intervention trials, reflected in MRC guidance on how to explore implementation, causal mechanisms and context [ 12 ].

Evidence about the context of an intervention is crucial for questions of external validity. As Woolcock [ 4 ] notes, even if RCT designs are accepted as robust for maximising internal validity, questions of transferability (how well the intervention works in different contexts) and generalisability (how well the intervention can be scaled up) remain unanswered [ 5 , 13 ]. For research evidence to have impact on policy and systems organisation, and thus to improve population and patient health, there is an urgent need for better methods for strengthening external validity, including a better understanding of the relationship between intervention and context [ 14 ].

Policymakers, healthcare commissioners and other research users require credible evidence of relevance to their settings and populations [ 15 ], to perform what Rosengarten and Savransky [ 16 ] call ‘careful abstraction’ to the locales that matter for them. They also require robust evidence for understanding complex causal pathways. Case study research, currently under-utilised in public health and health services evaluation, can offer considerable potential for strengthening faith in both external and internal validity. For example, in an empirical case study of how the policy of free bus travel had specific health effects in London, UK, a quasi-experimental evaluation (led by JG) identified how important aspects of context (a good public transport system) and intervention (that it was universal) were necessary conditions for the observed effects, thus providing useful, actionable evidence for decision-makers in other contexts [ 17 ].

The overall approach of case study research is based on the in-depth exploration of complex phenomena in their natural, or ‘real-life’, settings. Empirical case studies typically enable dynamic understanding of complex challenges rather than restricting the focus on narrow problem delineations and simple fixes. Case study research is a diverse and somewhat contested field, with multiple definitions and perspectives grounded in different ways of viewing the world, and involving different combinations of methods. In this paper, we raise awareness of such plurality and highlight the contribution that case study research can make to the evaluation of complex system-level interventions. We review some of the challenges in exploiting the current evidence base from empirical case studies and conclude by recommending that further guidance and minimum reporting criteria for evaluation using case studies, appropriate for audiences in the health sciences, can enhance the take-up of evidence from case study research.

Case study research offers evidence about context, causal inference in complex systems and implementation

Well-conducted and described empirical case studies provide evidence on context, complexity and mechanisms for understanding how, where and why interventions have their observed effects. Recognition of the importance of context for understanding the relationships between interventions and outcomes is hardly new. In 1943, Canguilhem berated an over-reliance on experimental designs for determining universal physiological laws: ‘As if one could determine a phenomenon’s essence apart from its conditions! As if conditions were a mask or frame which changed neither the face nor the picture!’ ([ 18 ] p126). More recently, a concern with context has been expressed in health systems and public health research as part of what has been called the ‘complexity turn’ [ 1 ]: a recognition that many of the most enduring challenges for developing an evidence base require a consideration of system-level effects [ 1 ] and the conceptualisation of interventions as interruptions in systems [ 19 ].

The case study approach is widely recognised as offering an invaluable resource for understanding the dynamic and evolving influence of context on complex, system-level interventions [ 20 , 21 , 22 , 23 ]. Empirically, case studies can directly inform assessments of where, when, how and for whom interventions might be successfully implemented, by helping to specify the necessary and sufficient conditions under which interventions might have effects and to consolidate learning on how interdependencies, emergence and unpredictability can be managed to achieve and sustain desired effects. Case study research has the potential to address four objectives for improving research and reporting of context recently set out by guidance on taking account of context in population health research [ 24 ], that is to (1) improve the appropriateness of intervention development for specific contexts, (2) improve understanding of ‘how’ interventions work, (3) better understand how and why impacts vary across contexts and (4) ensure reports of intervention studies are most useful for decision-makers and researchers.

However, evaluations of complex healthcare interventions have arguably not exploited the full potential of case study research and can learn much from other disciplines. For evaluative research, exploratory case studies have had a traditional role of providing data on ‘process’, or initial ‘hypothesis-generating’ scoping, but might also have an increasing salience for explanatory aims. Across the social and political sciences, different kinds of case studies are undertaken to meet diverse aims (description, exploration or explanation) and across different scales (from small N qualitative studies that aim to elucidate processes, or provide thick description, to more systematic techniques designed for medium-to-large N cases).

Case studies with explanatory aims vary in terms of their positioning within mixed-methods projects, with designs including (but not restricted to) (1) single N of 1 studies of interventions in specific contexts, where the overall design is a case study that may incorporate one or more (randomised or not) comparisons over time and between variables within the case; (2) a series of cases conducted or synthesised to provide explanation from variations between cases; and (3) case studies of particular settings within RCT or quasi-experimental designs to explore variation in effects or implementation.

Detailed qualitative research (typically done as ‘case studies’ within process evaluations) provides evidence for the plausibility of mechanisms [ 25 ], offering theoretical generalisations for how interventions may function under different conditions. Although RCT designs reduce many threats to internal validity, the mechanisms of effect remain opaque, particularly when the causal pathways between ‘intervention’ and ‘effect’ are long and potentially non-linear: case study research has a more fundamental role here, in providing detailed observational evidence for causal claims [ 26 ] as well as producing a rich, nuanced picture of tensions and multiple perspectives [ 8 ].

Longitudinal or cross-case analysis may be best suited for evidence generation in system-level evaluative research. Turner [ 27 ], for instance, reflecting on the complex processes in major system change, has argued for the need for methods that integrate learning across cases, to develop theoretical knowledge that would enable inferences beyond the single case, and to develop generalisable theory about organisational and structural change in health systems. Qualitative Comparative Analysis (QCA) [ 28 ] is one such formal method for deriving causal claims, using set theory mathematics to integrate data from empirical case studies to answer questions about the configurations of causal pathways linking conditions to outcomes [ 29 , 30 ].

Nonetheless, the single N case study, too, provides opportunities for theoretical development [ 31 ], and theoretical generalisation or analytical refinement [ 32 ]. How ‘the case’ and ‘context’ are conceptualised is crucial here. Findings from the single case may seem to be confined to its intrinsic particularities in a specific and distinct context [ 33 ]. However, if such context is viewed as exemplifying wider social and political forces, the single case can be ‘telling’, rather than ‘typical’, and offer insight into a wider issue [ 34 ]. Internal comparisons within the case can offer rich possibilities for logical inferences about causation [ 17 ]. Further, case studies of any size can be used for theory testing through refutation [ 22 ]. The potential lies, then, in utilising the strengths and plurality of case study to support theory-driven research within different methodological paradigms.

Evaluation research in health has much to learn from a range of social sciences where case study methodology has been used to develop various kinds of causal inference. For instance, Gerring [ 35 ] expands on the within-case variations utilised to make causal claims. For Gerring [ 35 ], case studies come into their own with regard to invariant or strong causal claims (such as X is a necessary and/or sufficient condition for Y) rather than for probabilistic causal claims. For the latter (where experimental methods might have an advantage in estimating effect sizes), case studies offer evidence on mechanisms: from observations of X affecting Y, from process tracing or from pattern matching. Case studies also support the study of emergent causation, that is, the multiple interacting properties that account for particular and unexpected outcomes in complex systems, such as in healthcare [ 8 ].

Finally, efficacy (or beliefs about efficacy) is not the only contributor to intervention uptake, with a range of organisational and policy contingencies affecting whether an intervention is likely to be rolled out in practice. Case study research is, therefore, invaluable for learning about contextual contingencies and identifying the conditions necessary for interventions to become normalised (i.e. implemented routinely) in practice [ 36 ].

The challenges in exploiting evidence from case study research

At present, there are significant challenges in exploiting the benefits of case study research in evaluative health research, which relate to status, definition and reporting. Case study research has been marginalised at the bottom of an evidence hierarchy, seen to offer little by way of explanatory power, if nonetheless useful for adding descriptive data on process or providing useful illustrations for policymakers [ 37 ]. This is an opportune moment to revisit this low status. As health researchers are increasingly charged with evaluating ‘natural experiments’—the use of face masks in the response to the COVID-19 pandemic being a recent example [ 38 ]—rather than interventions that take place in settings that can be controlled, research approaches using methods to strengthen causal inference that does not require randomisation become more relevant.

A second challenge for improving the use of case study evidence in evaluative health research is that, as we have seen, what is meant by ‘case study’ varies widely, not only across but also within disciplines. There is indeed little consensus amongst methodologists as to how to define ‘a case study’. Definitions focus, variously, on small sample size or lack of control over the intervention (e.g. [ 39 ] p194), on in-depth study and context [ 40 , 41 ], on the logic of inference used [ 35 ] or on distinct research strategies which incorporate a number of methods to address questions of ‘how’ and ‘why’ [ 42 ]. Moreover, definitions developed for specific disciplines do not capture the range of ways in which case study research is carried out across disciplines. Multiple definitions of case study reflect the richness and diversity of the approach. However, evidence suggests that a lack of consensus across methodologists results in some of the limitations of published reports of empirical case studies [ 43 , 44 ]. Hyett and colleagues [ 43 ], for instance, reviewing reports in qualitative journals, found little match between methodological definitions of case study research and how authors used the term.

This raises the third challenge we identify that case study reports are typically not written in ways that are accessible or useful for the evaluation research community and policymakers. Case studies may not appear in journals widely read by those in the health sciences, either because space constraints preclude the reporting of rich, thick descriptions, or because of the reported lack of willingness of some biomedical journals to publish research that uses qualitative methods [ 45 ], signalling the persistence of the aforementioned evidence hierarchy. Where they do, however, the term ‘case study’ is used to indicate, interchangeably, a qualitative study, an N of 1 sample, or a multi-method, in-depth analysis of one example from a population of phenomena. Definitions of what constitutes the ‘case’ are frequently lacking and appear to be used as a synonym for the settings in which the research is conducted. Despite offering insights for evaluation, the primary aims may not have been evaluative, so the implications may not be explicitly drawn out. Indeed, some case study reports might properly be aiming for thick description without necessarily seeking to inform about context or causality.

Acknowledging plurality and developing guidance

We recognise that definitional and methodological plurality is not only inevitable, but also a necessary and creative reflection of the very different epistemological and disciplinary origins of health researchers, and the aims they have in doing and reporting case study research. Indeed, to provide some clarity, Thomas [ 46 ] has suggested a typology of subject/purpose/approach/process for classifying aims (e.g. evaluative or exploratory), sample rationale and selection and methods for data generation of case studies. We also recognise that the diversity of methods used in case study research, and the necessary focus on narrative reporting, does not lend itself to straightforward development of formal quality or reporting criteria.

Existing checklists for reporting case study research from the social sciences—for example Lincoln and Guba’s [ 47 ] and Stake’s [ 33 ]—are primarily orientated to the quality of narrative produced, and the extent to which they encapsulate thick description, rather than the more pragmatic issues of implications for intervention effects. Those designed for clinical settings, such as the CARE (CAse REports) guidelines, provide specific reporting guidelines for medical case reports about single, or small groups of patients [ 48 ], not for case study research.

The Design of Case Study Research in Health Care (DESCARTE) model [ 44 ] suggests a series of questions to be asked of a case study researcher (including clarity about the philosophy underpinning their research), study design (with a focus on case definition) and analysis (to improve process). The model resembles toolkits for enhancing the quality and robustness of qualitative and mixed-methods research reporting, and it is usefully open-ended and non-prescriptive. However, even if it does include some reflections on context, the model does not fully address aspects of context, logic and causal inference that are perhaps most relevant for evaluative research in health.

Hence, for evaluative research where the aim is to report empirical findings in ways that are intended to be pragmatically useful for health policy and practice, this may be an opportune time to consider how to best navigate plurality around what is (minimally) important to report when publishing empirical case studies, especially with regards to the complex relationships between context and interventions, information that case study research is well placed to provide.

The conventional scientific quest for certainty, predictability and linear causality (maximised in RCT designs) has to be augmented by the study of uncertainty, unpredictability and emergent causality [ 8 ] in complex systems. This will require methodological pluralism, and openness to broadening the evidence base to better understand both causality in and the transferability of system change intervention [ 14 , 20 , 23 , 25 ]. Case study research evidence is essential, yet is currently under exploited in the health sciences. If evaluative health research is to move beyond the current impasse on methods for understanding interventions as interruptions in complex systems, we need to consider in more detail how researchers can conduct and report empirical case studies which do aim to elucidate the contextual factors which interact with interventions to produce particular effects. To this end, supported by the UK’s Medical Research Council, we are embracing the challenge to develop guidance for case study researchers studying complex interventions. Following a meta-narrative review of the literature, we are planning a Delphi study to inform guidance that will, at minimum, cover the value of case study research for evaluating the interrelationship between context and complex system-level interventions; for situating and defining ‘the case’, and generalising from case studies; as well as provide specific guidance on conducting, analysing and reporting case study research. Our hope is that such guidance can support researchers evaluating interventions in complex systems to better exploit the diversity and richness of case study research.

Availability of data and materials

Not applicable (article based on existing available academic publications)

Abbreviations

Qualitative comparative analysis

Quasi-experimental design

Randomised controlled trial

Diez Roux AV. Complex systems thinking and current impasses in health disparities research. Am J Public Health. 2011;101(9):1627–34.

Article   Google Scholar  

Ogilvie D, Mitchell R, Mutrie N, M P, Platt S. Evaluating health effects of transport interventions: methodologic case study. Am J Prev Med 2006;31:118–126.

Walshe C. The evaluation of complex interventions in palliative care: an exploration of the potential of case study research strategies. Palliat Med. 2011;25(8):774–81.

Woolcock M. Using case studies to explore the external validity of ‘complex’ development interventions. Evaluation. 2013;19:229–48.

Cartwright N. Are RCTs the gold standard? BioSocieties. 2007;2(1):11–20.

Deaton A, Cartwright N. Understanding and misunderstanding randomized controlled trials. Soc Sci Med. 2018;210:2–21.

Salway S, Green J. Towards a critical complex systems approach to public health. Crit Public Health. 2017;27(5):523–4.

Greenhalgh T, Papoutsi C. Studying complexity in health services research: desperately seeking an overdue paradigm shift. BMC Med. 2018;16(1):95.

Bonell C, Warren E, Fletcher A. Realist trials and the testing of context-mechanism-outcome configurations: a response to Van Belle et al. Trials. 2016;17:478.

Pallmann P, Bedding AW, Choodari-Oskooei B. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med. 2018;16:29.

Curran G, Bauer M, Mittman B, Pyne J, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50(3):217–26. https://doi.org/10.1097/MLR.0b013e3182408812 .

Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015 [cited 2020 Jun 27];350. Available from: https://www.bmj.com/content/350/bmj.h1258 .

Evans RE, Craig P, Hoddinott P, Littlecott H, Moore L, Murphy S, et al. When and how do ‘effective’ interventions need to be adapted and/or re-evaluated in new contexts? The need for guidance. J Epidemiol Community Health. 2019;73(6):481–2.

Shoveller J. A critical examination of representations of context within research on population health interventions. Crit Public Health. 2016;26(5):487–500.

Treweek S, Zwarenstein M. Making trials matter: pragmatic and explanatory trials and the problem of applicability. Trials. 2009;10(1):37.

Rosengarten M, Savransky M. A careful biomedicine? Generalization and abstraction in RCTs. Crit Public Health. 2019;29(2):181–91.

Green J, Roberts H, Petticrew M, Steinbach R, Goodman A, Jones A, et al. Integrating quasi-experimental and inductive designs in evaluation: a case study of the impact of free bus travel on public health. Evaluation. 2015;21(4):391–406.

Canguilhem G. The normal and the pathological. New York: Zone Books; 1991. (1949).

Google Scholar  

Hawe P, Shiell A, Riley T. Theorising interventions as events in systems. Am J Community Psychol. 2009;43:267–76.

King G, Keohane RO, Verba S. Designing social inquiry: scientific inference in qualitative research: Princeton University Press; 1994.

Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q. 2004;82(4):581–629.

Yin R. Enhancing the quality of case studies in health services research. Health Serv Res. 1999;34(5 Pt 2):1209.

CAS   PubMed   PubMed Central   Google Scholar  

Raine R, Fitzpatrick R, Barratt H, Bevan G, Black N, Boaden R, et al. Challenges, solutions and future directions in the evaluation of service innovations in health care and public health. Health Serv Deliv Res. 2016 [cited 2020 Jun 30];4(16). Available from: https://www.journalslibrary.nihr.ac.uk/hsdr/hsdr04160#/abstract .

Craig P, Di Ruggiero E, Frohlich KL, E M, White M, Group CCGA. Taking account of context in population health intervention research: guidance for producers, users and funders of research. NIHR Evaluation, Trials and Studies Coordinating Centre; 2018.

Grant RL, Hood R. Complex systems, explanation and policy: implications of the crisis of replication for public health research. Crit Public Health. 2017;27(5):525–32.

Mahoney J. Strategies of causal inference in small-N analysis. Sociol Methods Res. 2000;4:387–424.

Turner S. Major system change: a management and organisational research perspective. In: Rosalind Raine, Ray Fitzpatrick, Helen Barratt, Gywn Bevan, Nick Black, Ruth Boaden, et al. Challenges, solutions and future directions in the evaluation of service innovations in health care and public health. Health Serv Deliv Res. 2016;4(16) 2016. https://doi.org/10.3310/hsdr04160.

Ragin CC. Using qualitative comparative analysis to study causal complexity. Health Serv Res. 1999;34(5 Pt 2):1225.

Hanckel B, Petticrew M, Thomas J, Green J. Protocol for a systematic review of the use of qualitative comparative analysis for evaluative questions in public health research. Syst Rev. 2019;8(1):252.

Schneider CQ, Wagemann C. Set-theoretic methods for the social sciences: a guide to qualitative comparative analysis: Cambridge University Press; 2012. 369 p.

Flyvbjerg B. Five misunderstandings about case-study research. Qual Inq. 2006;12:219–45.

Tsoukas H. Craving for generality and small-N studies: a Wittgensteinian approach towards the epistemology of the particular in organization and management studies. Sage Handb Organ Res Methods. 2009:285–301.

Stake RE. The art of case study research. London: Sage Publications Ltd; 1995.

Mitchell JC. Typicality and the case study. Ethnographic research: A guide to general conduct. Vol. 238241. 1984.

Gerring J. What is a case study and what is it good for? Am Polit Sci Rev. 2004;98(2):341–54.

May C, Mort M, Williams T, F M, Gask L. Health technology assessment in its local contexts: studies of telehealthcare. Soc Sci Med 2003;57:697–710.

McGill E. Trading quality for relevance: non-health decision-makers’ use of evidence on the social determinants of health. BMJ Open. 2015;5(4):007053.

Greenhalgh T. We can’t be 100% sure face masks work – but that shouldn’t stop us wearing them | Trish Greenhalgh. The Guardian. 2020 [cited 2020 Jun 27]; Available from: https://www.theguardian.com/commentisfree/2020/jun/05/face-masks-coronavirus .

Hammersley M. So, what are case studies? In: What’s wrong with ethnography? New York: Routledge; 1992.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach. BMC Med Res Methodol. 2011;11(1):100.

Luck L, Jackson D, Usher K. Case study: a bridge across the paradigms. Nurs Inq. 2006;13(2):103–9.

Yin RK. Case study research and applications: design and methods: Sage; 2017.

Hyett N, A K, Dickson-Swift V. Methodology or method? A critical review of qualitative case study reports. Int J Qual Stud Health Well-Being. 2014;9:23606.

Carolan CM, Forbat L, Smith A. Developing the DESCARTE model: the design of case study research in health care. Qual Health Res. 2016;26(5):626–39.

Greenhalgh T, Annandale E, Ashcroft R, Barlow J, Black N, Bleakley A, et al. An open letter to the BMJ editors on qualitative research. Bmj. 2016;352.

Thomas G. A typology for the case study in social science following a review of definition, discourse, and structure. Qual Inq. 2011;17(6):511–21.

Lincoln YS, Guba EG. Judging the quality of case study reports. Int J Qual Stud Educ. 1990;3(1):53–9.

Riley DS, Barber MS, Kienle GS, Aronson JK, Schoen-Angerer T, Tugwell P, et al. CARE guidelines for case reports: explanation and elaboration document. J Clin Epidemiol. 2017;89:218–35.

Download references

Acknowledgements

Not applicable

This work was funded by the Medical Research Council - MRC Award MR/S014632/1 HCS: Case study, Context and Complex interventions (TRIPLE C). SP was additionally funded by the University of Oxford's Higher Education Innovation Fund (HEIF).

Author information

Authors and affiliations.

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Sara Paparini, Chrysanthi Papoutsi, Trish Greenhalgh & Sara Shaw

Wellcome Centre for Cultures & Environments of Health, University of Exeter, Exeter, UK

Judith Green

School of Health Sciences, University of East Anglia, Norwich, UK

Jamie Murdoch

Public Health, Environments and Society, London School of Hygiene & Tropical Medicin, London, UK

Mark Petticrew

Institute for Culture and Society, Western Sydney University, Penrith, Australia

Benjamin Hanckel

You can also search for this author in PubMed   Google Scholar

Contributions

JG, MP, SP, JM, TG, CP and SS drafted the initial paper; all authors contributed to the drafting of the final version, and read and approved the final manuscript.

Corresponding author

Correspondence to Sara Paparini .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Paparini, S., Green, J., Papoutsi, C. et al. Case study research for better evaluations of complex interventions: rationale and challenges. BMC Med 18 , 301 (2020). https://doi.org/10.1186/s12916-020-01777-6

Download citation

Received : 03 July 2020

Accepted : 07 September 2020

Published : 10 November 2020

DOI : https://doi.org/10.1186/s12916-020-01777-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Qualitative
• Case studies
• Mixed-method
• Public health
• Health services research
• Interventions

BMC Medicine

ISSN: 1741-7015

• Submission enquiries: [email protected]
• General enquiries: [email protected]

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Sage Choice

Continuing to enhance the quality of case study methodology in health services research

Shannon l. sibbald.

1 Faculty of Health Sciences, Western University, London, Ontario, Canada.

2 Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.

3 The Schulich Interfaculty Program in Public Health, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.

Stefan Paciocco

Meghan fournie, rachelle van asseldonk, tiffany scurr.

Case study methodology has grown in popularity within Health Services Research (HSR). However, its use and merit as a methodology are frequently criticized due to its flexible approach and inconsistent application. Nevertheless, case study methodology is well suited to HSR because it can track and examine complex relationships, contexts, and systems as they evolve. Applied appropriately, it can help generate information on how multiple forms of knowledge come together to inform decision-making within healthcare contexts. In this article, we aim to demystify case study methodology by outlining its philosophical underpinnings and three foundational approaches. We provide literature-based guidance to decision-makers, policy-makers, and health leaders on how to engage in and critically appraise case study design. We advocate that researchers work in collaboration with health leaders to detail their research process with an aim of strengthening the validity and integrity of case study for its continued and advanced use in HSR.

Introduction

The popularity of case study research methodology in Health Services Research (HSR) has grown over the past 40 years. 1 This may be attributed to a shift towards the use of implementation research and a newfound appreciation of contextual factors affecting the uptake of evidence-based interventions within diverse settings. 2 Incorporating context-specific information on the delivery and implementation of programs can increase the likelihood of success. 3 , 4 Case study methodology is particularly well suited for implementation research in health services because it can provide insight into the nuances of diverse contexts. 5 , 6 In 1999, Yin 7 published a paper on how to enhance the quality of case study in HSR, which was foundational for the emergence of case study in this field. Yin 7 maintains case study is an appropriate methodology in HSR because health systems are constantly evolving, and the multiple affiliations and diverse motivations are difficult to track and understand with traditional linear methodologies.

Despite its increased popularity, there is debate whether a case study is a methodology (ie, a principle or process that guides research) or a method (ie, a tool to answer research questions). Some criticize case study for its high level of flexibility, perceiving it as less rigorous, and maintain that it generates inadequate results. 8 Others have noted issues with quality and consistency in how case studies are conducted and reported. 9 Reporting is often varied and inconsistent, using a mix of approaches such as case reports, case findings, and/or case study. Authors sometimes use incongruent methods of data collection and analysis or use the case study as a default when other methodologies do not fit. 9 , 10 Despite these criticisms, case study methodology is becoming more common as a viable approach for HSR. 11 An abundance of articles and textbooks are available to guide researchers through case study research, including field-specific resources for business, 12 , 13 nursing, 14 and family medicine. 15 However, there remains confusion and a lack of clarity on the key tenets of case study methodology.

Several common philosophical underpinnings have contributed to the development of case study research 1 which has led to different approaches to planning, data collection, and analysis. This presents challenges in assessing quality and rigour for researchers conducting case studies and stakeholders reading results.

This article discusses the various approaches and philosophical underpinnings to case study methodology. Our goal is to explain it in a way that provides guidance for decision-makers, policy-makers, and health leaders on how to understand, critically appraise, and engage in case study research and design, as such guidance is largely absent in the literature. This article is by no means exhaustive or authoritative. Instead, we aim to provide guidance and encourage dialogue around case study methodology, facilitating critical thinking around the variety of approaches and ways quality and rigour can be bolstered for its use within HSR.

Purpose of case study methodology

Case study methodology is often used to develop an in-depth, holistic understanding of a specific phenomenon within a specified context. 11 It focuses on studying one or multiple cases over time and uses an in-depth analysis of multiple information sources. 16 , 17 It is ideal for situations including, but not limited to, exploring under-researched and real-life phenomena, 18 especially when the contexts are complex and the researcher has little control over the phenomena. 19 , 20 Case studies can be useful when researchers want to understand how interventions are implemented in different contexts, and how context shapes the phenomenon of interest.

In addition to demonstrating coherency with the type of questions case study is suited to answer, there are four key tenets to case study methodologies: (1) be transparent in the paradigmatic and theoretical perspectives influencing study design; (2) clearly define the case and phenomenon of interest; (3) clearly define and justify the type of case study design; and (4) use multiple data collection sources and analysis methods to present the findings in ways that are consistent with the methodology and the study’s paradigmatic base. 9 , 16 The goal is to appropriately match the methods to empirical questions and issues and not to universally advocate any single approach for all problems. 21

Approaches to case study methodology

Three authors propose distinct foundational approaches to case study methodology positioned within different paradigms: Yin, 19 , 22 Stake, 5 , 23 and Merriam 24 , 25 ( Table 1 ). Yin is strongly post-positivist whereas Stake and Merriam are grounded in a constructivist paradigm. Researchers should locate their research within a paradigm that explains the philosophies guiding their research 26 and adhere to the underlying paradigmatic assumptions and key tenets of the appropriate author’s methodology. This will enhance the consistency and coherency of the methods and findings. However, researchers often do not report their paradigmatic position, nor do they adhere to one approach. 9 Although deliberately blending methodologies may be defensible and methodologically appropriate, more often it is done in an ad hoc and haphazard way, without consideration for limitations.

Cross-analysis of three case study approaches, adapted from Yazan 2015

The post-positive paradigm postulates there is one reality that can be objectively described and understood by “bracketing” oneself from the research to remove prejudice or bias. 27 Yin focuses on general explanation and prediction, emphasizing the formulation of propositions, akin to hypothesis testing. This approach is best suited for structured and objective data collection 9 , 11 and is often used for mixed-method studies.

Constructivism assumes that the phenomenon of interest is constructed and influenced by local contexts, including the interaction between researchers, individuals, and their environment. 27 It acknowledges multiple interpretations of reality 24 constructed within the context by the researcher and participants which are unlikely to be replicated, should either change. 5 , 20 Stake and Merriam’s constructivist approaches emphasize a story-like rendering of a problem and an iterative process of constructing the case study. 7 This stance values researcher reflexivity and transparency, 28 acknowledging how researchers’ experiences and disciplinary lenses influence their assumptions and beliefs about the nature of the phenomenon and development of the findings.

Defining a case

A key tenet of case study methodology often underemphasized in literature is the importance of defining the case and phenomenon. Researches should clearly describe the case with sufficient detail to allow readers to fully understand the setting and context and determine applicability. Trying to answer a question that is too broad often leads to an unclear definition of the case and phenomenon. 20 Cases should therefore be bound by time and place to ensure rigor and feasibility. 6

Yin 22 defines a case as “a contemporary phenomenon within its real-life context,” (p13) which may contain a single unit of analysis, including individuals, programs, corporations, or clinics 29 (holistic), or be broken into sub-units of analysis, such as projects, meetings, roles, or locations within the case (embedded). 30 Merriam 24 and Stake 5 similarly define a case as a single unit studied within a bounded system. Stake 5 , 23 suggests bounding cases by contexts and experiences where the phenomenon of interest can be a program, process, or experience. However, the line between the case and phenomenon can become muddy. For guidance, Stake 5 , 23 describes the case as the noun or entity and the phenomenon of interest as the verb, functioning, or activity of the case.

Designing the case study approach

Yin’s approach to a case study is rooted in a formal proposition or theory which guides the case and is used to test the outcome. 1 Stake 5 advocates for a flexible design and explicitly states that data collection and analysis may commence at any point. Merriam’s 24 approach blends both Yin and Stake’s, allowing the necessary flexibility in data collection and analysis to meet the needs.

Yin 30 proposed three types of case study approaches—descriptive, explanatory, and exploratory. Each can be designed around single or multiple cases, creating six basic case study methodologies. Descriptive studies provide a rich description of the phenomenon within its context, which can be helpful in developing theories. To test a theory or determine cause and effect relationships, researchers can use an explanatory design. An exploratory model is typically used in the pilot-test phase to develop propositions (eg, Sibbald et al. 31 used this approach to explore interprofessional network complexity). Despite having distinct characteristics, the boundaries between case study types are flexible with significant overlap. 30 Each has five key components: (1) research question; (2) proposition; (3) unit of analysis; (4) logical linking that connects the theory with proposition; and (5) criteria for analyzing findings.

Contrary to Yin, Stake 5 believes the research process cannot be planned in its entirety because research evolves as it is performed. Consequently, researchers can adjust the design of their methods even after data collection has begun. Stake 5 classifies case studies into three categories: intrinsic, instrumental, and collective/multiple. Intrinsic case studies focus on gaining a better understanding of the case. These are often undertaken when the researcher has an interest in a specific case. Instrumental case study is used when the case itself is not of the utmost importance, and the issue or phenomenon (ie, the research question) being explored becomes the focus instead (eg, Paciocco 32 used an instrumental case study to evaluate the implementation of a chronic disease management program). 5 Collective designs are rooted in an instrumental case study and include multiple cases to gain an in-depth understanding of the complexity and particularity of a phenomenon across diverse contexts. 5 , 23 In collective designs, studying similarities and differences between the cases allows the phenomenon to be understood more intimately (for examples of this in the field, see van Zelm et al. 33 and Burrows et al. 34 In addition, Sibbald et al. 35 present an example where a cross-case analysis method is used to compare instrumental cases).

Merriam’s approach is flexible (similar to Stake) as well as stepwise and linear (similar to Yin). She advocates for conducting a literature review before designing the study to better understand the theoretical underpinnings. 24 , 25 Unlike Stake or Yin, Merriam proposes a step-by-step guide for researchers to design a case study. These steps include performing a literature review, creating a theoretical framework, identifying the problem, creating and refining the research question(s), and selecting a study sample that fits the question(s). 24 , 25 , 36

Data collection and analysis

Using multiple data collection methods is a key characteristic of all case study methodology; it enhances the credibility of the findings by allowing different facets and views of the phenomenon to be explored. 23 Common methods include interviews, focus groups, observation, and document analysis. 5 , 37 By seeking patterns within and across data sources, a thick description of the case can be generated to support a greater understanding and interpretation of the whole phenomenon. 5 , 17 , 20 , 23 This technique is called triangulation and is used to explore cases with greater accuracy. 5 Although Stake 5 maintains case study is most often used in qualitative research, Yin 17 supports a mix of both quantitative and qualitative methods to triangulate data. This deliberate convergence of data sources (or mixed methods) allows researchers to find greater depth in their analysis and develop converging lines of inquiry. For example, case studies evaluating interventions commonly use qualitative interviews to describe the implementation process, barriers, and facilitators paired with a quantitative survey of comparative outcomes and effectiveness. 33 , 38 , 39

Yin 30 describes analysis as dependent on the chosen approach, whether it be (1) deductive and rely on theoretical propositions; (2) inductive and analyze data from the “ground up”; (3) organized to create a case description; or (4) used to examine plausible rival explanations. According to Yin’s 40 approach to descriptive case studies, carefully considering theory development is an important part of study design. “Theory” refers to field-relevant propositions, commonly agreed upon assumptions, or fully developed theories. 40 Stake 5 advocates for using the researcher’s intuition and impression to guide analysis through a categorical aggregation and direct interpretation. Merriam 24 uses six different methods to guide the “process of making meaning” (p178) : (1) ethnographic analysis; (2) narrative analysis; (3) phenomenological analysis; (4) constant comparative method; (5) content analysis; and (6) analytic induction.

Drawing upon a theoretical or conceptual framework to inform analysis improves the quality of case study and avoids the risk of description without meaning. 18 Using Stake’s 5 approach, researchers rely on protocols and previous knowledge to help make sense of new ideas; theory can guide the research and assist researchers in understanding how new information fits into existing knowledge.

Practical applications of case study research

Columbia University has recently demonstrated how case studies can help train future health leaders. 41 Case studies encompass components of systems thinking—considering connections and interactions between components of a system, alongside the implications and consequences of those relationships—to equip health leaders with tools to tackle global health issues. 41 Greenwood 42 evaluated Indigenous peoples’ relationship with the healthcare system in British Columbia and used a case study to challenge and educate health leaders across the country to enhance culturally sensitive health service environments.

An important but often omitted step in case study research is an assessment of quality and rigour. We recommend using a framework or set of criteria to assess the rigour of the qualitative research. Suitable resources include Caelli et al., 43 Houghten et al., 44 Ravenek and Rudman, 45 and Tracy. 46

New directions in case study

Although “pragmatic” case studies (ie, utilizing practical and applicable methods) have existed within psychotherapy for some time, 47 , 48 only recently has the applicability of pragmatism as an underlying paradigmatic perspective been considered in HSR. 49 This is marked by uptake of pragmatism in Randomized Control Trials, recognizing that “gold standard” testing conditions do not reflect the reality of clinical settings 50 , 51 nor do a handful of epistemologically guided methodologies suit every research inquiry.

Pragmatism positions the research question as the basis for methodological choices, rather than a theory or epistemology, allowing researchers to pursue the most practical approach to understanding a problem or discovering an actionable solution. 52 Mixed methods are commonly used to create a deeper understanding of the case through converging qualitative and quantitative data. 52 Pragmatic case study is suited to HSR because its flexibility throughout the research process accommodates complexity, ever-changing systems, and disruptions to research plans. 49 , 50 Much like case study, pragmatism has been criticized for its flexibility and use when other approaches are seemingly ill-fit. 53 , 54 Similarly, authors argue that this results from a lack of investigation and proper application rather than a reflection of validity, legitimizing the need for more exploration and conversation among researchers and practitioners. 55

Although occasionally misunderstood as a less rigourous research methodology, 8 case study research is highly flexible and allows for contextual nuances. 5 , 6 Its use is valuable when the researcher desires a thorough understanding of a phenomenon or case bound by context. 11 If needed, multiple similar cases can be studied simultaneously, or one case within another. 16 , 17 There are currently three main approaches to case study, 5 , 17 , 24 each with their own definitions of a case, ontological and epistemological paradigms, methodologies, and data collection and analysis procedures. 37

Individuals’ experiences within health systems are influenced heavily by contextual factors, participant experience, and intricate relationships between different organizations and actors. 55 Case study research is well suited for HSR because it can track and examine these complex relationships and systems as they evolve over time. 6 , 7 It is important that researchers and health leaders using this methodology understand its key tenets and how to conduct a proper case study. Although there are many examples of case study in action, they are often under-reported and, when reported, not rigorously conducted. 9 Thus, decision-makers and health leaders should use these examples with caution. The proper reporting of case studies is necessary to bolster their credibility in HSR literature and provide readers sufficient information to critically assess the methodology. We also call on health leaders who frequently use case studies 56 – 58 to report them in the primary research literature.

The purpose of this article is to advocate for the continued and advanced use of case study in HSR and to provide literature-based guidance for decision-makers, policy-makers, and health leaders on how to engage in, read, and interpret findings from case study research. As health systems progress and evolve, the application of case study research will continue to increase as researchers and health leaders aim to capture the inherent complexities, nuances, and contextual factors. 7

• First Online: 27 October 2022

Cite this chapter

• R. M. Channaveer 4 &
• Rajendra Baikady 5  

2112 Accesses

1 Citations

This chapter reviews the strengths and limitations of case study as a research method in social sciences. It provides an account of an evidence base to justify why a case study is best suitable for some research questions and why not for some other research questions. Case study designing around the research context, defining the structure and modality, conducting the study, collecting the data through triangulation mode, analysing the data, and interpreting the data and theory building at the end give a holistic view of it. In addition, the chapter also focuses on the types of case study and when and where to use case study as a research method in social science research.

• Qualitative research approach
• Social work research

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Ang, C. S., Lee, K. F., & Dipolog-Ubanan, G. F. (2019). Determinants of first-year student identity and satisfaction in higher education: A quantitative case study. SAGE Open, 9 (2), 215824401984668. https://doi.org/10.1177/2158244019846689

Baxter, P., & Jack, S. (2015). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report . Published. https://doi.org/10.46743/2160-3715/2008.1573

Bhatta, T. P. (2018). Case study research, philosophical position and theory building: A methodological discussion. Dhaulagiri Journal of Sociology and Anthropology, 12 , 72–79. https://doi.org/10.3126/dsaj.v12i0.22182

Article   Google Scholar  

Bromley, P. D. (1990). Academic contributions to psychological counselling. A philosophy of science for the study of individual cases. Counselling Psychology Quarterly , 3 (3), 299–307.

Google Scholar  

Crowe, S., Cresswell, K., Robertson, A., Huby, G., Avery, A., & Sheikh, A. (2011). The case study approach. BMC Medical Research Methodology, 11 (1), 1–9.

Grässel, E., & Schirmer, B. (2006). The use of volunteers to support family carers of dementia patients: Results of a prospective longitudinal study investigating expectations towards and experience with training and professional support. Zeitschrift Fur Gerontologie Und Geriatrie, 39 (3), 217–226.

Greenwood, D., & Lowenthal, D. (2005). Case study as a means of researching social work and improving practitioner education. Journal of Social Work Practice, 19 (2), 181–193. https://doi.org/10.1080/02650530500144782

Gülseçen, S., & Kubat, A. (2006). Teaching ICT to teacher candidates using PBL: A qualitative and quantitative evaluation. Journal of Educational Technology & Society, 9 (2), 96–106.

Gomm, R., Hammersley, M., & Foster, P. (2000). Case study and generalization. Case study method , 98–115.

Hamera, J., Denzin, N. K., & Lincoln, Y. S. (2011). Performance ethnography . SAGE.

Hayes, N. (2000). Doing psychological research (p. 133). Open University Press.

Harrison, H., Birks, M., Franklin, R., & Mills, J. (2017). Case study research: Foundations and methodological orientations. In Forum qualitative sozialforschung/forum: Qualitative social research (Vol. 18, No. 1).

Iwakabe, S., & Gazzola, N. (2009). From single-case studies to practice-based knowledge: Aggregating and synthesizing case studies. Psychotherapy Research, 19 (4–5), 601–611. https://doi.org/10.1080/10503300802688494

Johnson, M. P. (2006). Decision models for the location of community corrections centers. Environment and Planning b: Planning and Design, 33 (3), 393–412. https://doi.org/10.1068/b3125

Kaarbo, J., & Beasley, R. K. (1999). A practical guide to the comparative case study method in political psychology. Political Psychology, 20 (2), 369–391. https://doi.org/10.1111/0162-895x.00149

Lovell, G. I. (2006). Justice excused: The deployment of law in everyday political encounters. Law Society Review, 40 (2), 283–324. https://doi.org/10.1111/j.1540-5893.2006.00265.x

McDonough, S., & McDonough, S. (1997). Research methods as part of English language teacher education. English Language Teacher Education and Development, 3 (1), 84–96.

Meredith, J. (1998). Building operations management theory through case and field research. Journal of Operations Management, 16 (4), 441–454. https://doi.org/10.1016/s0272-6963(98)00023-0

Mills, A. J., Durepos, G., & Wiebe, E. (Eds.). (2009). Encyclopedia of case study research . Sage Publications.

Ochieng, P. A. (2009). An analysis of the strengths and limitation of qualitative and quantitative research paradigms. Problems of Education in the 21st Century , 13 , 13.

Page, E. B., Webb, E. J., Campell, D. T., Schwart, R. D., & Sechrest, L. (1966). Unobtrusive measures: Nonreactive research in the social sciences. American Educational Research Journal, 3 (4), 317. https://doi.org/10.2307/1162043

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case study method: A step-by-step guide for business researchers. International Journal of Qualitative Methods, 18 , 160940691986242. https://doi.org/10.1177/1609406919862424

Ridder, H. G. (2017). The theory contribution of case study research designs. Business Research, 10 (2), 281–305. https://doi.org/10.1007/s40685-017-0045-z

Sadeghi Moghadam, M. R., Ghasemnia Arabi, N., & Khoshsima, G. (2021). A Review of case study method in operations management research. International Journal of Qualitative Methods, 20 , 160940692110100. https://doi.org/10.1177/16094069211010088

Sommer, B. B., & Sommer, R. (1997). A practical guide to behavioral research: Tools and techniques . Oxford University Press.

Stake, R. E. (2010). Qualitative research: Studying how things work .

Stake, R. E. (1995). The Art of Case Study Research . Sage Publications.

Stoecker, R. (1991). Evaluating and rethinking the case study. The Sociological Review, 39 (1), 88–112.

Suryani, A. (2013). Comparing case study and ethnography as qualitative research approaches .

Taylor, S., & Berridge, V. (2006). Medicinal plants and malaria: An historical case study of research at the London School of Hygiene and Tropical Medicine in the twentieth century. Transactions of the Royal Society of Tropical Medicine and Hygiene, 100 (8), 707–714. https://doi.org/10.1016/j.trstmh.2005.11.017

Tellis, W. (1997). Introduction to case study. The Qualitative Report . Published. https://doi.org/10.46743/2160-3715/1997.2024

Towne, L., & Shavelson, R. J. (2002). Scientific research in education . National Academy Press Publications Sales Office.

Widdowson, M. D. J. (2011). Case study research methodology. International Journal of Transactional Analysis Research, 2 (1), 25–34.

Yin, R. K. (2004). The case study anthology . Sage.

Yin, R. K. (2003). Design and methods. Case Study Research , 3 (9.2).

Yin, R. K. (1994). Case study research: Design and methods (2nd ed.). Sage Publishing.

Yin, R. (1984). Case study research: Design and methods . Sage Publications Beverly Hills.

Yin, R. (1993). Applications of case study research . Sage Publishing.

Zainal, Z. (2003). An investigation into the effects of discipline-specific knowledge, proficiency and genre on reading comprehension and strategies of Malaysia ESP Students. Unpublished Ph. D. Thesis. University of Reading , 1 (1).

Zeisel, J. (1984). Inquiry by design: Tools for environment-behaviour research (No. 5). CUP archive.

Download references

Author information

Authors and affiliations.

Department of Social Work, Central University of Karnataka, Kadaganchi, India

R. M. Channaveer

Department of Social Work, University of Johannesburg, Johannesburg, South Africa

Rajendra Baikady

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to R. M. Channaveer .

Editor information

Editors and affiliations.

Centre for Family and Child Studies, Research Institute of Humanities and Social Sciences, University of Sharjah, Sharjah, United Arab Emirates

M. Rezaul Islam

Department of Development Studies, University of Dhaka, Dhaka, Bangladesh

Niaz Ahmed Khan

Department of Social Work, School of Humanities, University of Johannesburg, Johannesburg, South Africa

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Channaveer, R.M., Baikady, R. (2022). Case Study. In: Islam, M.R., Khan, N.A., Baikady, R. (eds) Principles of Social Research Methodology. Springer, Singapore. https://doi.org/10.1007/978-981-19-5441-2_21

Download citation

DOI : https://doi.org/10.1007/978-981-19-5441-2_21

Published : 27 October 2022

Publisher Name : Springer, Singapore

Print ISBN : 978-981-19-5219-7

Online ISBN : 978-981-19-5441-2

eBook Packages : Social Sciences

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

Case study research: opening up research opportunities

RAUSP Management Journal

ISSN : 2531-0488

Article publication date: 30 December 2019

Issue publication date: 3 March 2020

The case study approach has been widely used in management studies and the social sciences more generally. However, there are still doubts about when and how case studies should be used. This paper aims to discuss this approach, its various uses and applications, in light of epistemological principles, as well as the criteria for rigor and validity.

Design/methodology/approach

This paper discusses the various concepts of case and case studies in the methods literature and addresses the different uses of cases in relation to epistemological principles and criteria for rigor and validity.

The use of this research approach can be based on several epistemologies, provided the researcher attends to the internal coherence between method and epistemology, or what the authors call “alignment.”

Originality/value

This study offers a number of implications for the practice of management research, as it shows how the case study approach does not commit the researcher to particular data collection or interpretation methods. Furthermore, the use of cases can be justified according to multiple epistemological orientations.

• Epistemology

Takahashi, A.R.W. and Araujo, L. (2020), "Case study research: opening up research opportunities", RAUSP Management Journal , Vol. 55 No. 1, pp. 100-111. https://doi.org/10.1108/RAUSP-05-2019-0109

Emerald Publishing Limited

Copyright © 2019, Adriana Roseli Wünsch Takahashi and Luis Araujo.

Published in RAUSP Management Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

The case study as a research method or strategy brings us to question the very term “case”: after all, what is a case? A case-based approach places accords the case a central role in the research process ( Ragin, 1992 ). However, doubts still remain about the status of cases according to different epistemologies and types of research designs.

Despite these doubts, the case study is ever present in the management literature and represents the main method of management research in Brazil ( Coraiola, Sander, Maccali, & Bulgacov, 2013 ). Between 2001 and 2010, 2,407 articles (83.14 per cent of qualitative research) were published in conferences and management journals as case studies (Takahashi & Semprebom, 2013 ). A search on Spell.org.br for the term “case study” under title, abstract or keywords, for the period ranging from January 2010 to July 2019, yielded 3,040 articles published in the management field. Doing research using case studies, allows the researcher to immerse him/herself in the context and gain intensive knowledge of a phenomenon, which in turn demands suitable methodological principles ( Freitas et al. , 2017 ).

Our objective in this paper is to discuss notions of what constitutes a case and its various applications, considering epistemological positions as well as criteria for rigor and validity. The alignment between these dimensions is put forward as a principle advocating coherence among all phases of the research process.

This article makes two contributions. First, we suggest that there are several epistemological justifications for using case studies. Second, we show that the quality and rigor of academic research with case studies are directly related to the alignment between epistemology and research design rather than to choices of specific forms of data collection or analysis. The article is structured as follows: the following four sections discuss concepts of what is a case, its uses, epistemological grounding as well as rigor and quality criteria. The brief conclusions summarize the debate and invite the reader to delve into the literature on the case study method as a way of furthering our understanding of contemporary management phenomena.

2. What is a case study?

The debate over what constitutes a case in social science is a long-standing one. In 1988, Howard Becker and Charles Ragin organized a workshop to discuss the status of the case as a social science method. As the discussion was inconclusive, they posed the question “What is a case?” to a select group of eight social scientists in 1989, and later to participants in a symposium on the subject. Participants were unable to come up with a consensual answer. Since then, we have witnessed that further debates and different answers have emerged. The original question led to an even broader issue: “How do we, as social scientists, produce results and seem to know what we know?” ( Ragin, 1992 , p. 16).

An important step that may help us start a reflection on what is a case is to consider the phenomena we are looking at. To do that, we must know something about what we want to understand and how we might study it. The answer may be a causal explanation, a description of what was observed or a narrative of what has been experienced. In any case, there will always be a story to be told, as the choice of the case study method demands an answer to what the case is about.

A case may be defined ex ante , prior to the start of the research process, as in Yin’s (2015) classical definition. But, there is no compelling reason as to why cases must be defined ex ante . Ragin (1992 , p. 217) proposed the notion of “casing,” to indicate that what the case is emerges from the research process:

Rather than attempt to delineate the many different meanings of the term “case” in a formal taxonomy, in this essay I offer instead a view of cases that follows from the idea implicit in many of the contributions – that concocting cases is a varied but routine social scientific activity. […] The approach of this essay is that this activity, which I call “casing”, should be viewed in practical terms as a research tactic. It is selectively invoked at many different junctures in the research process, usually to resolve difficult issues in linking ideas and evidence.

In other words, “casing” is tied to the researcher’s practice, to the way he/she delimits or declares a case as a significant outcome of a process. In 2013, Ragin revisited the 1992 concept of “casing” and explored its multiple possibilities of use, paying particular attention to “negative cases.”

According to Ragin (1992) , a case can be centered on a phenomenon or a population. In the first scenario, cases are representative of a phenomenon, and are selected based on what can be empirically observed. The process highlights different aspects of cases and obscures others according to the research design, and allows for the complexity, specificity and context of the phenomenon to be explored. In the alternative, population-focused scenario, the selection of cases precedes the research. Both positive and negative cases are considered in exploring a phenomenon, with the definition of the set of cases dependent on theory and the central objective to build generalizations. As a passing note, it is worth mentioning here that a study of multiple cases requires a definition of the unit of analysis a priori . Otherwise, it will not be possible to make cross-case comparisons.

These two approaches entail differences that go beyond the mere opposition of quantitative and qualitative data, as a case often includes both types of data. Thus, the confusion about how to conceive cases is associated with Ragin’s (1992) notion of “small vs large N,” or McKeown’s (1999) “statistical worldview” – the notion that relevant findings are only those that can be made about a population based on the analysis of representative samples. In the same vein, Byrne (2013) argues that we cannot generate nomothetic laws that apply in all circumstances, periods and locations, and that no social science method can claim to generate invariant laws. According to the same author, case studies can help us understand that there is more than one ideographic variety and help make social science useful. Generalizations still matter, but they should be understood as part of defining the research scope, and that scope points to the limitations of knowledge produced and consumed in concrete time and space.

Thus, what defines the orientation and the use of cases is not the mere choice of type of data, whether quantitative or qualitative, but the orientation of the study. A statistical worldview sees cases as data units ( Byrne, 2013 ). Put differently, there is a clear distinction between statistical and qualitative worldviews; the use of quantitative data does not by itself means that the research is (quasi) statistical, or uses a deductive logic:

Case-based methods are useful, and represent, among other things, a way of moving beyond a useless and destructive tradition in the social sciences that have set quantitative and qualitative modes of exploration, interpretation, and explanation against each other ( Byrne, 2013 , p. 9).

Other authors advocate different understandings of what a case study is. To some, it is a research method, to others it is a research strategy ( Creswell, 1998 ). Sharan Merrian and Robert Yin, among others, began to write about case study research as a methodology in the 1980s (Merrian, 2009), while authors such as Eisenhardt (1989) called it a research strategy. Stake (2003) sees the case study not as a method, but as a choice of what to be studied, the unit of study. Regardless of their differences, these authors agree that case studies should be restricted to a particular context as they aim to provide an in-depth knowledge of a given phenomenon: “A case study is an in-depth description and analysis of a bounded system” (Merrian, 2009, p. 40). According to Merrian, a qualitative case study can be defined by the process through which the research is carried out, by the unit of analysis or the final product, as the choice ultimately depends on what the researcher wants to know. As a product of research, it involves the analysis of a given entity, phenomenon or social unit.

Thus, whether it is an organization, an individual, a context or a phenomenon, single or multiple, one must delimit it, and also choose between possible types and configurations (Merrian, 2009; Yin, 2015 ). A case study may be descriptive, exploratory, explanatory, single or multiple ( Yin, 2015 ); intrinsic, instrumental or collective ( Stake, 2003 ); and confirm or build theory ( Eisenhardt, 1989 ).

both went through the same process of implementing computer labs intended for the use of information and communication technologies in 2007;

both took part in the same regional program (Paraná Digital); and

they shared similar characteristics regarding location (operation in the same neighborhood of a city), number of students, number of teachers and technicians and laboratory sizes.

However, the two institutions differed in the number of hours of program use, with one of them displaying a significant number of hours/use while the other showed a modest number, according to secondary data for the period 2007-2013. Despite the context being similar and the procedures for implementing the technology being the same, the mechanisms of social integration – an idiosyncratic factor of each institution – were different in each case. This explained differences in their use of resource, processes of organizational learning and capacity to absorb new knowledge.

On the other hand, multiple case studies seek evidence in different contexts and do not necessarily require direct comparisons ( Stake, 2003 ). Rather, there is a search for patterns of convergence and divergence that permeate all the cases, as the same issues are explored in every case. Cases can be added progressively until theoretical saturation is achieved. An example is of a study that investigated how entrepreneurial opportunity and management skills were developed through entrepreneurial learning ( Zampier & Takahashi, 2014 ). The authors conducted nine case studies, based on primary and secondary data, with each one analyzed separately, so a search for patterns could be undertaken. The convergence aspects found were: the predominant way of transforming experience into knowledge was exploitation; managerial skills were developed through by taking advantages of opportunities; and career orientation encompassed more than one style. As for divergence patterns: the experience of success and failure influenced entrepreneurs differently; the prevailing rationality logic of influence was different; and the combination of styles in career orientation was diverse.

A full discussion of choice of case study design is outside the scope of this article. For the sake of illustration, we make a brief mention to other selection criteria such as the purpose of the research, the state of the art of the research theme, the time and resources involved and the preferred epistemological position of the researcher. In the next section, we look at the possibilities of carrying out case studies in line with various epistemological traditions, as the answers to the “what is a case?” question reveal varied methodological commitments as well as diverse epistemological and ontological positions ( Ragin, 2013 ).

3. Epistemological positioning of case study research

Ontology and epistemology are like skin, not a garment to be occasionally worn ( Marsh & Furlong, 2002 ). According to these authors, ontology and epistemology guide the choice of theory and method because they cannot or should not be worn as a garment. Hence, one must practice philosophical “self-knowledge” to recognize one’s vision of what the world is and of how knowledge of that world is accessed and validated. Ontological and epistemological positions are relevant in that they involve the positioning of the researcher in social science and the phenomena he or she chooses to study. These positions do not tend to vary from one project to another although they can certainly change over time for a single researcher.

Ontology is the starting point from which the epistemological and methodological positions of the research arise ( Grix, 2002 ). Ontology expresses a view of the world, what constitutes reality, nature and the image one has of social reality; it is a theory of being ( Marsh & Furlong, 2002 ). The central question is the nature of the world out there regardless of our ability to access it. An essentialist or foundationalist ontology acknowledges that there are differences that persist over time and these differences are what underpin the construction of social life. An opposing, anti-foundationalist position presumes that the differences found are socially constructed and may vary – i.e. they are not essential but specific to a given culture at a given time ( Marsh & Furlong, 2002 ).

Epistemology is centered around a theory of knowledge, focusing on the process of acquiring and validating knowledge ( Grix, 2002 ). Positivists look at social phenomena as a world of causal relations where there is a single truth to be accessed and confirmed. In this tradition, case studies test hypotheses and rely on deductive approaches and quantitative data collection and analysis techniques. Scholars in the field of anthropology and observation-based qualitative studies proposed alternative epistemologies based on notions of the social world as a set of manifold and ever-changing processes. In management studies since the 1970s, the gradual acceptance of qualitative research has generated a diverse range of research methods and conceptions of the individual and society ( Godoy, 1995 ).

The interpretative tradition, in direct opposition to positivism, argues that there is no single objective truth to be discovered about the social world. The social world and our knowledge of it are the product of social constructions. Thus, the social world is constituted by interactions, and our knowledge is hermeneutic as the world does not exist independent of our knowledge ( Marsh & Furlong, 2002 ). The implication is that it is not possible to access social phenomena through objective, detached methods. Instead, the interaction mechanisms and relationships that make up social constructions have to be studied. Deductive approaches, hypothesis testing and quantitative methods are not relevant here. Hermeneutics, on the other hand, is highly relevant as it allows the analysis of the individual’s interpretation, of sayings, texts and actions, even though interpretation is always the “truth” of a subject. Methods such as ethnographic case studies, interviews and observations as data collection techniques should feed research designs according to interpretivism. It is worth pointing out that we are to a large extent, caricaturing polar opposites rather characterizing a range of epistemological alternatives, such as realism, conventionalism and symbolic interactionism.

If diverse ontologies and epistemologies serve as a guide to research approaches, including data collection and analysis methods, and if they should be regarded as skin rather than clothing, how does one make choices regarding case studies? What are case studies, what type of knowledge they provide and so on? The views of case study authors are not always explicit on this point, so we must delve into their texts to glean what their positions might be.

Two of the cited authors in case study research are Robert Yin and Kathleen Eisenhardt. Eisenhardt (1989) argues that a case study can serve to provide a description, test or generate a theory, the latter being the most relevant in contributing to the advancement of knowledge in a given area. She uses terms such as populations and samples, control variables, hypotheses and generalization of findings and even suggests an ideal number of case studies to allow for theory construction through replication. Although Eisenhardt includes observation and interview among her recommended data collection techniques, the approach is firmly anchored in a positivist epistemology:

Third, particularly in comparison with Strauss (1987) and Van Maanen (1988), the process described here adopts a positivist view of research. That is, the process is directed toward the development of testable hypotheses and theory which are generalizable across settings. In contrast, authors like Strauss and Van Maanen are more concerned that a rich, complex description of the specific cases under study evolve and they appear less concerned with development of generalizable theory ( Eisenhardt, 1989 , p. 546).

This position attracted a fair amount of criticism. Dyer & Wilkins (1991) in a critique of Eisenhardt’s (1989) article focused on the following aspects: there is no relevant justification for the number of cases recommended; it is the depth and not the number of cases that provides an actual contribution to theory; and the researcher’s purpose should be to get closer to the setting and interpret it. According to the same authors, discrepancies from prior expectations are also important as they lead researchers to reflect on existing theories. Eisenhardt & Graebner (2007 , p. 25) revisit the argument for the construction of a theory from multiple cases:

A major reason for the popularity and relevance of theory building from case studies is that it is one of the best (if not the best) of the bridges from rich qualitative evidence to mainstream deductive research.

Although they recognize the importance of single-case research to explore phenomena under unique or rare circumstances, they reaffirm the strength of multiple case designs as it is through them that better accuracy and generalization can be reached.

Likewise, Robert Yin emphasizes the importance of variables, triangulation in the search for “truth” and generalizable theoretical propositions. Yin (2015 , p. 18) suggests that the case study method may be appropriate for different epistemological orientations, although much of his work seems to invoke a realist epistemology. Authors such as Merrian (2009) and Stake (2003) suggest an interpretative version of case studies. Stake (2003) looks at cases as a qualitative option, where the most relevant criterion of case selection should be the opportunity to learn and understand a phenomenon. A case is not just a research method or strategy; it is a researcher’s choice about what will be studied:

Even if my definition of case study was agreed upon, and it is not, the term case and study defy full specification (Kemmis, 1980). A case study is both a process of inquiry about the case and the product of that inquiry ( Stake, 2003 , p. 136).

Later, Stake (2003 , p. 156) argues that:

[…] the purpose of a case report is not to represent the world, but to represent the case. […] The utility of case research to practitioners and policy makers is in its extension of experience.

Still according to Stake (2003 , pp. 140-141), to do justice to complex views of social phenomena, it is necessary to analyze the context and relate it to the case, to look for what is peculiar rather than common in cases to delimit their boundaries, to plan the data collection looking for what is common and unusual about facts, what could be valuable whether it is unique or common:

Reflecting upon the pertinent literature, I find case study methodology written largely by people who presume that the research should contribute to scientific generalization. The bulk of case study work, however, is done by individuals who have intrinsic interest in the case and little interest in the advance of science. Their designs aim the inquiry toward understanding of what is important about that case within its own world, which is seldom the same as the worlds of researchers and theorists. Those designs develop what is perceived to be the case’s own issues, contexts, and interpretations, its thick descriptions . In contrast, the methods of instrumental case study draw the researcher toward illustrating how the concerns of researchers and theorists are manifest in the case. Because the critical issues are more likely to be know in advance and following disciplinary expectations, such a design can take greater advantage of already developed instruments and preconceived coding schemes.

The aforementioned authors were listed to illustrate differences and sometimes opposing positions on case research. These differences are not restricted to a choice between positivism and interpretivism. It is worth noting that Ragin’s (2013 , p. 523) approach to “casing” is compatible with the realistic research perspective:

In essence, to posit cases is to engage in ontological speculation regarding what is obdurately real but only partially and indirectly accessible through social science. Bringing a realist perspective to the case question deepens and enriches the dialogue, clarifying some key issues while sweeping others aside.

cases are actual entities, reflecting their operations of real causal mechanism and process patterns;

case studies are interactive processes and are open to revisions and refinements; and

social phenomena are complex, contingent and context-specific.

Ragin (2013 , p. 532) concludes:

Lurking behind my discussion of negative case, populations, and possibility analysis is the implication that treating cases as members of given (and fixed) populations and seeking to infer the properties of populations may be a largely illusory exercise. While demographers have made good use of the concept of population, and continue to do so, it is not clear how much the utility of the concept extends beyond their domain. In case-oriented work, the notion of fixed populations of cases (observations) has much less analytic utility than simply “the set of relevant cases,” a grouping that must be specified or constructed by the researcher. The demarcation of this set, as the work of case-oriented researchers illustrates, is always tentative, fluid, and open to debate. It is only by casing social phenomena that social scientists perceive the homogeneity that allows analysis to proceed.

In summary, case studies are relevant and potentially compatible with a range of different epistemologies. Researchers’ ontological and epistemological positions will guide their choice of theory, methodologies and research techniques, as well as their research practices. The same applies to the choice of authors describing the research method and this choice should be coherent. We call this research alignment , an attribute that must be judged on the internal coherence of the author of a study, and not necessarily its evaluator. The following figure illustrates the interrelationship between the elements of a study necessary for an alignment ( Figure 1 ).

In addition to this broader aspect of the research as a whole, other factors should be part of the researcher’s concern, such as the rigor and quality of case studies. We will look into these in the next section taking into account their relevance to the different epistemologies.

4. Rigor and quality in case studies

Traditionally, at least in positivist studies, validity and reliability are the relevant quality criteria to judge research. Validity can be understood as external, internal and construct. External validity means identifying whether the findings of a study are generalizable to other studies using the logic of replication in multiple case studies. Internal validity may be established through the theoretical underpinning of existing relationships and it involves the use of protocols for the development and execution of case studies. Construct validity implies defining the operational measurement criteria to establish a chain of evidence, such as the use of multiple sources of evidence ( Eisenhardt, 1989 ; Yin, 2015 ). Reliability implies conducting other case studies, instead of just replicating results, to minimize the errors and bias of a study through case study protocols and the development of a case database ( Yin, 2015 ).

Several criticisms have been directed toward case studies, such as lack of rigor, lack of generalization potential, external validity and researcher bias. Case studies are often deemed to be unreliable because of a lack of rigor ( Seuring, 2008 ). Flyvbjerg (2006 , p. 219) addresses five misunderstandings about case-study research, and concludes that:

[…] a scientific discipline without a large number of thoroughly executed case studies is a discipline without systematic production of exemplars, and a discipline without exemplars is an ineffective one.

theoretical knowledge is more valuable than concrete, practical knowledge;

the case study cannot contribute to scientific development because it is not possible to generalize on the basis of an individual case;

the case study is more useful for generating rather than testing hypotheses;

the case study contains a tendency to confirm the researcher’s preconceived notions; and

it is difficult to summarize and develop general propositions and theories based on case studies.

These criticisms question the validity of the case study as a scientific method and should be corrected.

The critique of case studies is often framed from the standpoint of what Ragin (2000) labeled large-N research. The logic of small-N research, to which case studies belong, is different. Cases benefit from depth rather than breadth as they: provide theoretical and empirical knowledge; contribute to theory through propositions; serve not only to confirm knowledge, but also to challenge and overturn preconceived notions; and the difficulty in summarizing their conclusions is because of the complexity of the phenomena studies and not an intrinsic limitation of the method.

Thus, case studies do not seek large-scale generalizations as that is not their purpose. And yet, this is a limitation from a positivist perspective as there is an external reality to be “apprehended” and valid conclusions to be extracted for an entire population. If positivism is the epistemology of choice, the rigor of a case study can be demonstrated by detailing the criteria used for internal and external validity, construct validity and reliability ( Gibbert & Ruigrok, 2010 ; Gibbert, Ruigrok, & Wicki, 2008 ). An example can be seen in case studies in the area of information systems, where there is a predominant orientation of positivist approaches to this method ( Pozzebon & Freitas, 1998 ). In this area, rigor also involves the definition of a unit of analysis, type of research, number of cases, selection of sites, definition of data collection and analysis procedures, definition of the research protocol and writing a final report. Creswell (1998) presents a checklist for researchers to assess whether the study was well written, if it has reliability and validity and if it followed methodological protocols.

In case studies with a non-positivist orientation, rigor can be achieved through careful alignment (coherence among ontology, epistemology, theory and method). Moreover, the concepts of validity can be understood as concern and care in formulating research, research development and research results ( Ollaik & Ziller, 2012 ), and to achieve internal coherence ( Gibbert et al. , 2008 ). The consistency between data collection and interpretation, and the observed reality also help these studies meet coherence and rigor criteria. Siggelkow (2007) argues that a case study should be persuasive and that even a single case study may be a powerful example to contest a widely held view. To him, the value of a single case study or studies with few cases can be attained by their potential to provide conceptual insights and coherence to the internal logic of conceptual arguments: “[…] a paper should allow a reader to see the world, and not just the literature, in a new way” ( Siggelkow, 2007 , p. 23).

Interpretative studies should not be justified by criteria derived from positivism as they are based on a different ontology and epistemology ( Sandberg, 2005 ). The rejection of an interpretive epistemology leads to the rejection of an objective reality: “As Bengtsson points out, the life-world is the subjects’ experience of reality, at the same time as it is objective in the sense that it is an intersubjective world” ( Sandberg, 2005 , p. 47). In this event, how can one demonstrate what positivists call validity and reliability? What would be the criteria to justify knowledge as truth, produced by research in this epistemology? Sandberg (2005 , p. 62) suggests an answer based on phenomenology:

This was demonstrated first by explicating life-world and intentionality as the basic assumptions underlying the interpretative research tradition. Second, based on those assumptions, truth as intentional fulfillment, consisting of perceived fulfillment, fulfillment in practice, and indeterminate fulfillment, was proposed. Third, based on the proposed truth constellation, communicative, pragmatic, and transgressive validity and reliability as interpretative awareness were presented as the most appropriate criteria for justifying knowledge produced within interpretative approach. Finally, the phenomenological epoché was suggested as a strategy for achieving these criteria.

From this standpoint, the research site must be chosen according to its uniqueness so that one can obtain relevant insights that no other site could provide ( Siggelkow, 2007 ). Furthermore, the view of what is being studied is at the center of the researcher’s attention to understand its “truth,” inserted in a given context.

The case researcher is someone who can reduce the probability of misinterpretations by analyzing multiple perceptions, searches for data triangulation to check for the reliability of interpretations ( Stake, 2003 ). It is worth pointing out that this is not an option for studies that specifically seek the individual’s experience in relation to organizational phenomena.

In short, there are different ways of seeking rigor and quality in case studies, depending on the researcher’s worldview. These different forms pervade everything from the research design, the choice of research questions, the theory or theories to look at a phenomenon, research methods, the data collection and analysis techniques, to the type and style of research report produced. Validity can also take on different forms. While positivism is concerned with validity of the research question and results, interpretivism emphasizes research processes without neglecting the importance of the articulation of pertinent research questions and the sound interpretation of results ( Ollaik & Ziller, 2012 ). The means to achieve this can be diverse, such as triangulation (of multiple theories, multiple methods, multiple data sources or multiple investigators), pre-tests of data collection instrument, pilot case, study protocol, detailed description of procedures such as field diary in observations, researcher positioning (reflexivity), theoretical-empirical consistency, thick description and transferability.

5. Conclusions

The central objective of this article was to discuss concepts of case study research, their potential and various uses, taking into account different epistemologies as well as criteria of rigor and validity. Although the literature on methodology in general and on case studies in particular, is voluminous, it is not easy to relate this approach to epistemology. In addition, method manuals often focus on the details of various case study approaches which confuse things further.

Faced with this scenario, we have tried to address some central points in this debate and present various ways of using case studies according to the preferred epistemology of the researcher. We emphasize that this understanding depends on how a case is defined and the particular epistemological orientation that underpins that conceptualization. We have argued that whatever the epistemological orientation is, it is possible to meet appropriate criteria of research rigor and quality provided there is an alignment among the different elements of the research process. Furthermore, multiple data collection techniques can be used in in single or multiple case study designs. Data collection techniques or the type of data collected do not define the method or whether cases should be used for theory-building or theory-testing.

Finally, we encourage researchers to consider case study research as one way to foster immersion in phenomena and their contexts, stressing that the approach does not imply a commitment to a particular epistemology or type of research, such as qualitative or quantitative. Case study research allows for numerous possibilities, and should be celebrated for that diversity rather than pigeon-holed as a monolithic research method.

The interrelationship between the building blocks of research

Byrne , D. ( 2013 ). Case-based methods: Why We need them; what they are; how to do them . Byrne D. In D Byrne. and C.C Ragin (Eds.), The SAGE handbooks of Case-Based methods , pp. 1 – 10 . London : SAGE Publications Inc .

Creswell , J. W. ( 1998 ). Qualitative inquiry and research design: choosing among five traditions , London : Sage Publications .

Coraiola , D. M. , Sander , J. A. , Maccali , N. & Bulgacov , S. ( 2013 ). Estudo de caso . In A. R. W. Takahashi , (Ed.), Pesquisa qualitativa em administração: Fundamentos, métodos e usos no Brasil , pp. 307 – 341 . São Paulo : Atlas .

Dyer , W. G. , & Wilkins , A. L. ( 1991 ). Better stories, not better constructs, to generate better theory: a rejoinder to Eisenhardt . The Academy of Management Review , 16 , 613 – 627 .

Eisenhardt , K. ( 1989 ). Building theory from case study research . Academy of Management Review , 14 , 532 – 550 .

Eisenhardt , K. M. , & Graebner , M. E. ( 2007 ). Theory building from cases: Opportunities and challenges . Academy of Management Journal , 50 , 25 – 32 .

Flyvbjerg , B. ( 2006 ). Five misunderstandings about case-study research . Qualitative Inquiry , 12 , 219 – 245 .

Freitas , J. S. , Ferreira , J. C. A. , Campos , A. A. R. , Melo , J. C. F. , Cheng , L. C. , & Gonçalves , C. A. ( 2017 ). Methodological roadmapping: a study of centering resonance analysis . RAUSP Management Journal , 53 , 459 – 475 .

Gibbert , M. , Ruigrok , W. , & Wicki , B. ( 2008 ). What passes as a rigorous case study? . Strategic Management Journal , 29 , 1465 – 1474 .

Gibbert , M. , & Ruigrok , W. ( 2010 ). The “what” and “how” of case study rigor: Three strategies based on published work . Organizational Research Methods , 13 , 710 – 737 .

Godoy , A. S. ( 1995 ). Introdução à pesquisa qualitativa e suas possibilidades . Revista de Administração de Empresas , 35 , 57 – 63 .

Grix , J. ( 2002 ). Introducing students to the generic terminology of social research . Politics , 22 , 175 – 186 .

Marsh , D. , & Furlong , P. ( 2002 ). A skin, not a sweater: ontology and epistemology in political science . In D Marsh. , & G Stoker , (Eds.), Theory and Methods in Political Science , New York, NY : Palgrave McMillan , pp. 17 – 41 .

McKeown , T. J. ( 1999 ). Case studies and the statistical worldview: Review of King, Keohane, and Verba’s designing social inquiry: Scientific inference in qualitative research . International Organization , 53 , 161 – 190 .

Merriam , S. B. ( 2009 ). Qualitative research: a guide to design and implementation .

Ollaik , L. G. , & Ziller , H. ( 2012 ). Distintas concepções de validade em pesquisas qualitativas . Educação e Pesquisa , 38 , 229 – 241 .

Picoli , F. R. , & Takahashi , A. R. W. ( 2016 ). Capacidade de absorção, aprendizagem organizacional e mecanismos de integração social . Revista de Administração Contemporânea , 20 , 1 – 20 .

Pozzebon , M. , & Freitas , H. M. R. ( 1998 ). Pela aplicabilidade: com um maior rigor científico – dos estudos de caso em sistemas de informação . Revista de Administração Contemporânea , 2 , 143 – 170 .

Sandberg , J. ( 2005 ). How do we justify knowledge produced within interpretive approaches? . Organizational Research Methods , 8 , 41 – 68 .

Seuring , S. A. ( 2008 ). Assessing the rigor of case study research in supply chain management. Supply chain management . Supply Chain Management: An International Journal , 13 , 128 – 137 .

Siggelkow , N. ( 2007 ). Persuasion with case studies . Academy of Management Journal , 50 , 20 – 24 .

Stake , R. E. ( 2003 ). Case studies . In N. K. , Denzin , & Y. S. , Lincoln (Eds.). Strategies of Qualitative Inquiry , London : Sage Publications . pp. 134 – 164 .

Takahashi , A. R. W. , & Semprebom , E. ( 2013 ). Resultados gerais e desafios . In A. R. W. , Takahashi (Ed.), Pesquisa qualitativa em administração: Fundamentos, métodos e usos no brasil , pp. 343 – 354 . São Paulo : Atlas .

Ragin , C. C. ( 1992 ). Introduction: Cases of “what is a case? . In H. S. , Becker , & C. C. Ragin and (Eds). What is a case? Exploring the foundations of social inquiry , pp. 1 – 18 .

Ragin , C. C. ( 2013 ). Reflections on casing and Case-Oriented research . In D , Byrne. , & C. C. Ragin (Eds.), The SAGE handbooks of Case-Based methods , London : SAGE Publications , pp. 522 – 534 .

Yin , R. K. ( 2015 ). Estudo de caso: planejamento e métodos , Porto Alegre : Bookman .

Zampier , M. A. , & Takahashi , A. R. W. ( 2014 ). Aprendizagem e competências empreendedoras: Estudo de casos de micro e pequenas empresas do setor educacional . RGO Revista Gestão Organizacional , 6 , 1 – 18 .

Acknowledgements

Author contributions: Both authors contributed equally.

Corresponding author

Related articles, we’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

Research Writing and Analysis

• NVivo Group and Study Sessions
• SPSS This link opens in a new window
• Statistical Analysis Group sessions
• Using Qualtrics
• Dissertation and Data Analysis Group Sessions
• Research Process Flow Chart
• Research Alignment This link opens in a new window
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Literature Review This link opens in a new window
• Systematic Reviews & Meta-Analyses
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Synthesis and Analysis Group Sessions
• Problem Statement
• Purpose Statement
• Quantitative Research Questions
• Qualitative Research Questions
• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
• Dissertation to Journal Article This link opens in a new window
• International Journal of Online Graduate Education (IJOGE) This link opens in a new window
• Journal of Research in Innovative Teaching & Learning (JRIT&L) This link opens in a new window

Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

Was this resource helpful?

• << Previous: Thematic Data Analysis in Qualitative Design
• Next: Journal Article Reporting Standards (JARS) >>
• Last Updated: Mar 20, 2024 11:50 AM
• URL: https://resources.nu.edu/researchtools

Not logged in

Multiple case study, page actions.

• View source

A multiple case study is a research method that uses multiple research sites to gain a more comprehensive understanding of a particular phenomenon. It examines multiple cases in order to analyze patterns and the relationships between variables. This type of research method is used in management to gain a deeper understanding of a particular problem or issue. It is a systematic approach to gathering and analyzing data from multiple different sources such as individuals, organizations, or communities. The multiple case study approach allows researchers to gain greater insight into complex problems by considering a variety of perspectives, contexts, and sources of information .

• 1 Example of multiple case study
• 2 When to use multiple case study
• 3 Types of multiple case study
• 4 Steps of multiple case study
• 5 Limitations of multiple case study
• 6 Other approaches related to multiple case study
• 7 References

Example of multiple case study

• A multiple case study example could be a study of different companies in the same industry in order to analyze the differences in their strategies and performance. For instance, a researcher may examine three companies in the automotive industry and determine what strategies have been successful and which have not. They may then compare the results of these three companies in order to determine which strategies are most effective.
• Another example of a multiple case study could be an examination of how different countries have responded to the COVID-19 pandemic. In this case, the researcher could look at different strategies adopted by countries worldwide and analyze the results of those strategies. They could then compare the results in order to determine which strategies have been most successful in mitigating the spread of the virus.
• A third example could be a study of different schools and how they have adapted to the online learning environment . The researcher could look at the successes and failures of different schools in order to determine which strategies are most effective in transitioning to remote learning. They could then use these findings to suggest changes and improvements to the schools’ policies and procedures .

When to use multiple case study

A multiple case study approach is a useful tool for researchers looking to gain a deeper understanding of complex issues. This method can be used in a variety of contexts, such as studying organizational management , social phenomena, or public health interventions. It can provide a more comprehensive understanding of the problem by considering a variety of perspectives, contexts, and sources of information. Examples of when multiple case studies can be used include:

• Examining the effectiveness of a particular policy or program in multiple contexts.
• Exploring the dynamics of organizational change across different settings.
• Investigating the impact of a cultural or social phenomenon on different communities.
• Analyzing the differences in responses to a public health intervention between populations.
• Understanding the dynamics of an issue in order to inform the development of new policies or practices.

Types of multiple case study

• Exploratory multiple case study: An exploratory multiple case study is used to explore a research problem in greater detail. It is used when the research question or problem is not well-defined, or when the researcher is uncertain about the best approach to study the problem. This type of multiple case study is often used to generate new ideas and to identify potential research topics.
• Explanatory Multiple Case Study: An explanatory multiple case study is used to explain a research problem in detail. It is used when the researcher is looking to explain the cause of an event or phenomenon. This type of multiple case study is used to identify patterns and relationships between variables, and to identify potential explanations for the phenomenon being studied.
• Descriptive Multiple Case Study: A descriptive multiple case study is used to describe a research problem in detail. It is used when the researcher wants to provide a comprehensive overview of a particular topic or phenomenon. This type of multiple case study is useful for providing a detailed description of a particular event or phenomenon and its context.
• Comparative Multiple Case Study: A comparative multiple case study is used to compare two or more research sites. It is used when the researcher wants to compare and contrast a phenomenon across multiple sites. This type of multiple case study is useful for examining similarities and differences between different research sites.
• Embedded Multiple Case Study: An embedded multiple case study is used to embed a single case study within a larger research project . It is used when the researcher wants to incorporate a single case study within a larger research project. This type of multiple case study is useful for exploring the complexities of a particular research problem, and for providing an in-depth understanding of a particular phenomenon.

Steps of multiple case study

A multiple case study is a research method that uses multiple research sites to gain a more comprehensive understanding of a particular phenomenon. The multiple case study approach allows researchers to gain greater insight into complex problems by considering a variety of perspectives, contexts, and sources of information. The following steps are necessary for conducting a successful multiple case study:

• Selecting the research sites : The first step in a multiple case study is to select the research sites. This requires careful consideration of factors such as the size and scope of the problem, the availability of data and resources, and the accessibility of the research sites.
• Gathering data : After selecting the research sites, the next step is to gather data. This can be done through interviews, surveys, focus groups, and other data collection methods .
• Analyzing the data : Once the data has been gathered, it must be analyzed in order to identify patterns and relationships between variables. This requires careful analysis of the data and may involve using statistical methods such as regression and factor analysis.
• Drawing conclusions : After the data has been analyzed, the next step is to draw conclusions. This involves synthesizing the data and making sense of it in order to answer the research question.
• Reporting the results : The final step is to report the results of the multiple case study. This can be done through a written report, a presentation, or a multimedia format.

Limitations of multiple case study

Multiple case studies have some limitations that should be taken into consideration when using this method. These limitations include:

• The multiple case study approach can be time consuming and resource intensive, as researchers must collect and analyze data from multiple different sources.
• It can be difficult to identify patterns and relationships between variables when studying multiple cases.
• The data collected from multiple cases may be difficult to generalize to a larger population.
• The multiple case study approach is limited to studying phenomena in limited contexts, and does not provide a holistic picture of a phenomenon.
• It can be difficult to control for all variables in a multiple case study, which can lead to inaccurate results.

Other approaches related to multiple case study

A multiple case study is a research method that uses multiple research sites to gain a more comprehensive understanding of a particular phenomenon. Other approaches related to multiple case studies include:

• Qualitative research : Qualitative research is an empirical research approach which focuses on understanding the perspectives, experiences, and beliefs of people in their contexts. It typically involves interviews, observations, and other forms of data collection.
• Grounded Theory : Grounded theory is an inductive research method that examines how social processes are created, maintained, and changed. It involves the systematic collection and analysis of data to generate new theory.
• Action Research : Action research is a type of research that involves the active participation of stakeholders in the research process . It focuses on identifying and resolving practical problems in an organization or community.
• Gustafsson, J. (2017). Single case studies vs. multiple case studies: A comparative study .
• Methods and techniques
• Recent changes
• Random page
• Page information

Table of Contents

• Special pages

User page tools

• What links here
• Related changes
• Printable version
• Permanent link

• This page was last edited on 18 November 2023, at 01:04.
• Content is available under CC BY-SA Attribution-ShareAlike 4.0 International unless otherwise noted.
• Privacy policy
• About CEOpedia | Management online
• Disclaimers

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 28 March 2024

Transmission dynamics of Zika virus with multiple infection routes and a case study in Brazil

• Liying Wang 1 , 2 ,
• Qiaojuan Jia 2 ,
• Guanghu Zhu 1 , 2 ,
• Guanlin Ou 1 &
• Tian Tang 1 , 3  

Scientific Reports volume  14 , Article number:  7424 ( 2024 ) Cite this article

Metrics details

• Applied mathematics
• Infectious diseases
• Risk factors

The Zika virus (ZIKV) is a serious global public health crisis. A major control challenge is its multiple transmission modes. This paper aims to simulate the transmission patterns of ZIKV using a dynamic process-based epidemiological model written in ordinary differential equations, which incorporates the human-to-mosquito infection by bites and sewage, mosquito-to-human infection by bites, and human-to-human infection by sex. Mathematical analyses are carried out to calculate the basic reproduction number and backward bifurcation, and prove the existence and stability of the equilibria. The model is validated with infection data by applying it to the 2015–2016 ZIKV epidemic in Brazil. The results indicate that the reproduction number is estimated to be 2.13, in which the contributions by mosquito bite, sex and sewage account for 85.7%, 3.5% and 10.8%, respectively. This number and the morbidity rate are most sensitive to parameters related to mosquito ecology, rather than asymptomatic or human-to-human transmission. Multiple transmission routes and suitable temperature exacerbate ZIKV infection in Brazil, and the vast majority of human infection cases were prevented by the intervention implemented. These findings may provide new insights to improve the risk assessment of ZIKV infection.

Similar content being viewed by others

Impact of weather seasonality and sexual transmission on the spread of Zika fever

Attila Dénes, Mahmoud A. Ibrahim, … Tamás Tekeli

Modeling Zika Virus Transmission Dynamics: Parameter Estimates, Disease Characteristics, and Prevention

Munsur Rahman, Kidist Bekele-Maxwell, … Naveen K. Vaidya

Analysis of the dynamics of a vector-borne infection with the effect of imperfect vaccination from a fractional perspective

Tao-Qian Tang, Rashid Jan, … Mihaela Racheriu

Introduction

Zika virus (ZIKV) is a Flavivirus closely related to dengue, which was first discovered in 1947 in Uganda among a certain Rhesus macaque population 1 . However, few human infections were reported until 2015, when ZIKV infection unexpectedly struck the Americas and spread to other countries over the next 2 years 2 , 3 . The WHO has recorded that a total of 87 countries and territories have reported evidence of autochthonous ZIKV infection, with more than 1.4 million suspected and confirmed Zika cases 4 . ZIKV is a serious public health problem, which has the following concerns: (1) large number of human infections with ZIKV (0.4–1.3 million cases in Brazil alone) 3 ; (2) serious consequence of infection, in which ZIKV infection during pregnancy can cause microcephaly and other congenital anomalies in developing fetuses and newborns (nearly 6000 suspected cases of microcephaly among newborns might be linked to ZIKV infections in Brazil during 2015–2016 5 , 6 ); (3) about three quarters of cases of ZIKV infection are asymptomatic, who can transmate the disease but not easy to be identified 7 , 8 ; (4) multiple transmission routes, where human can be infected through mosquitoes or humans, adult mosquitoes can be infected through humans, and larvae mosquitoes can be infected through the virus sewage 9 , 10 , 11 , 12 , 13 , 14 , 15 . Understanding such complex transmission patterns can provide scientific evidence to guide disease control.

Existing studies mainly use epidemiological investigation, statistical approach and mathematical models to tackle the above-mentioned issues 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 . By addressing the impacts of multiple transmission routes on ZIKV infection, it is found that (1) sexual transmission increases the risk of infection and epidemic size, and prolongs the outbreak 9 ; (2) prevention and control efforts against ZIKV should target both the mosquito-borne and sexual transmission routes 9 ; and (3) scenario exploration indicates that personal protection could be more effective than mosquito-reduction intervention 10 , and releasing male Wolbachia mosquitoes may be a good choice of disease control 12 . Furthermore, experimental studies have shown that urine from infected humans could be a natural ZIKV source, where Aedes mosquitoes are permissive to ZIKV infection when breeding in urine or sewage containing low concentrations of ZIKV 13 , 14 . However, there is a lack of mechanistic frameworks for modeling different routes of ZIKV transmission, and fewer evaluations of these routes on infections 9 , 11 , 12 , 15 .

To fill the knowledge gap, this study proposes a mechanistic framework for modeling ZIKV transmission patterns by addressing the following questions: How to account for the vector–virus–host interactions and the multiple routes of infection and thus to simulate the diffusion process? How to calculate the dynamics of transmission and assess the risk of infection, and thus suggest how to intervene? How to characterize the role of the dominant factors in activating or inhibiting the disease evolution? Answering these questions may provide new insights to improve ZIKV risk assessment and guide disease control. Mathematical model and data fitting method are employed to tackle these challenges. Specifically, based on the classical Ross–Macdonald theory and compartmental principle of mosquito-borne disease 20 , a new ZIKV transmission model is established by ordinary differential equations (ODEs), which systematically combines the dynamics of virus evolution, multiple infection routes, mosquito ecology and human behavior. Since temperature plays a vital role in ZIKV infection, its effects is included by modulating the transmission factors of virus and mosquitoes (oviposition rate, aquatic transition rate, hatching rate, mosquito bite rate and infection rate). Mathematical analysis are used to explore the transmission dynamics, including the expression of the basic reproduction number, the existence of bifurcation, and the stability of the equilibria. By using Markov Chain Monte Carlo (MCMC) methods to fit the time series of the reporting cases, the model is further validated to analyze the ZIKV outbreak in Brazil during 2015–2016. Numerical simulations and sensitivity analysis are performed to illustrate the detailed transmission patterns in Brazil.

This paper is organized as follows. The model is presented in “ Modeling framework ” and analyzed mathematically in “ Mathematical analysis ”. Main results are presented in “ Model application ”, including simulation ZIKV transmission in Brazil, the impact of transmission routes on the epidemic and the effectiveness of epidemic prevention and control. A brief discussion is presented in the last section.

Modeling framework

A mechanistic framework for simulating ZIKV transmission patterns is established in this section. Inspired by recently-developed mathematical models 9 , 16 , 17 , 18 , 19 , and based on epidemiological feature of ZIKV, a new dynamic system is proposed, which takes into account human-to-human (sexual transmission) and human-to-mosquito (bite transmission and sewage transmission) interactions by using compartmental and deterministic principle. The total numbers of human, larval and adult mosquitoes are represented by \({{N}_{h}}\) , \({{M}_{v}}\) and \({{N}_{v}}\) . Given the stability of human demographics and the extremely low rate of ZIKV-related mortality, \({{N}_{h}}\) is assumed to be a constant.

Based on the characteristics of ZIKV infection, it is further assumed that: (1) the humans are divided into five categories: susceptible \({{S}_{h}}\) , latent \({{E}_{h}}\) , symptomatic infected \({{I}_{s}}\) , asymptomatic infected \({{I}_{a}}\) and recovered \({{R}_{h}}\) ; (2) the larval stage can be divided into two categories: uninfected \({{A}_{v}}\) (including eggs, larvae and pupae) and infected \({{J}_{v}}\) ; (3) the adult female mosquitoes are divided into three categories: susceptible \({{S}_{v}}\) , latent \({{E}_{v}}\) and infected \({{I}_{v}}\) .

It is known that mosquito oviposition is linked to mature females and the ability of mosquitoes to develop oviposition habitats. If there are too many eggs in the oviposition habitat or too few nutrients and water resources, the females will lay fewer eggs or choose another site 21 , 22 . In addition, larvae and pupae need water or nutrients complete their development 21 . This biological phenomenon can be expressed by a Logistic model which explicitly incorporates the idea of limited carrying capacity resources 21 , 22 . Hence, the per capita oviposition rate is given by \(\theta ( 1-({A}_{v}+{J}_{v})/K ){N}_{v}\) .

When ZIKV invades an area, humans and mosquitoes there could be infected with certain probability. It is governed by the following rules. A susceptible human may be infected with ZIKV from the bite of infectious mosquitoes at rate b or through human contact with infected people at rate \(\beta \) . Infected humans undergo an incubation period \({1}/{\delta }\) . After that they could be symptomatic \(\phi \) and asymptomatic \(1-\phi \) , and then the former follows by an infectious period of mean duration \({1}/{\eta }\) until recovery. The larvae may be directly infected by the virus sewage at rate p and grow up to become infectious adult mosquitoes at rate \(\alpha \) . Susceptible mosquitoes become infected at rate a by biting infectious humans, and the infected mosquito experience an extrinsic incubation period \({1}/{\gamma }\) , that is followed by an infectious state from which they do not recover. The mean larvae lifespan and adult lifespan are 1/ f and \(1/\mu \) , respectively. Flow chat is shown in Fig. 1 .

Flow diagram of the ZIKV transmission among humans and mosquitoes. The black solid lines indicate the progress of infection and ecology. The yellow lines indicated the infection pathes.

Accordingly, the following ODEs are used to simulate the transmission dynamics of ZIKV:

Detailed explanations of the variable and parameters are shown in Table 1 . All the variables and parameters are non-negative. Similar to the proofs in 21 , 22 , it is obtained that the following \(\Omega \) is positively invariant and attracting under the flow described by the system ( 1 ).

Temperature, as the most important factor in the modulation of mosquito-borne diseases, is considered by including in the model parameters, where the parameters are functions of temperature T . Based on observations from laboratory studies 23 , 24 , 25 , they are presented below.

Mathematical analysis

The transmission dynamics of the proposed model are analyzed mathematically, in which the epidemic threshold (i.e., the basic reproduction number) is calculated by the next generation matrix method, and the evolution trends of the model solutions are investigated by stability theory.

• Basic reproduction number

The basic reproduction number \({{R}_{0}}\) is interpreted as the average number of secondary cases that are produced by a single primary case in a fully susceptible population, acting as the critical measure of the transmissibility 31 . The basic reproduction number \({{R}_{0}}\) is calculated by using the theory of next generation matrix 31 . It is written as 31 : \({{R}_{0}}=\rho \left( F{{V}^{-1}} \right) \) , where F is the rate of occurring new infections, and V is the rate of transferring individuals outside the original group. Here \(\rho \) represents the spectral radius of matrix.

Let the right hand side of the system ( 1 ) equal to zero, it is obtained the disease-free equilibrium of the model

It follows from the next generation matrix method 31 that

Using \({{R}_{0}}=\rho \left( F{{V}^{-1}} \right) \) 31 , the basic reproduction number is calculated as follows:

Some typical features can be observed from Eq. ( 9 ): (a) \({{R}_{h{{h}_{1}}}}\) and \({{R}_{h{{v}_{1}}}}\) represent the parts of the basic reproductive number \({{R}_{0}}\) contributed by sexual transmission and mosquito-borne transmission, respectively; (b) \({{R}_{h{{h}_{1}}}}\) is determined by human-to-human transmission; (c) \({{R}_{h{{v}_{1}}}}\) is determine by parameters related to mosquitoes and humans, which can be further divided into two stages of larval transmission and adult transmission.

Model stability

Mosquitoes breeding in contaminated water can become infected with ZIKV, which can shorten the virus transmission cycle and promote the spread of ZIKV 14 . Based on this, the following mathematical analysis is divided into two cases, with or without larval infection in the virus sewage, corresponding to \(p=0\) or \(p\ne 0\) .

\(p=0\) (without larval mosquito infection in the virus sewage)

In this case there is no larval infection \({{J}_{v}}\) item in the system ( 1 ). The basic reproduction number of the available model is

Theorem 3.1

When \(p=0\) , if \({{\overline{R}_{0}}}<1\) , then the disease-free equilibrium of the system ( 1 ) is locally asymptotically stable.

The proof is similar to that of Theorem 3.5 , so it is omitted here.

The expression of endemic equilibrium is denoted by

Letting the right-hand side of system ( 1 ) to be zeros, direct calculation yields an equation about infectivity \(\lambda _{h}^{*}\) as

Let \({{a}_{1}}=\alpha +f, {{a}_{2}}=\gamma +\mu , {{a}_{3}}=\eta +d, {{a}_{4}}=\delta +d. \)

It is further obtained that

where \({{H}_{1}}=ac\left( \phi \delta +\left( 1-\phi \right) \delta k \right) ,{{H}_{2}}=p\left( \phi \delta +\left( 1-\phi \right) \delta q \right) ,{{H}_{3}}=\beta \left( \phi \delta +\left( 1-\phi \right) \delta \tau \right) \) . It follows from Eq. ( 11 ) that

Here \(\lambda _{h}^{*}\) can be obtained by solving the quadratic expression ( 12 ), which also determines the expression of the endemic equilibrium. When \(\mathop {{{\overline{R}}_{0}}}>1\) , one has \({\mathop {{{\overline{R}}_{0}}}}\,R_{h{{v}_{2}}}^{2}+{\mathop {{{\overline{R}}_{0}}}}\,{{R}_{hh2}}>R_{h{{v}_{2}}}^{2}+{\mathop {{{\overline{R}}_{0}}}}\,{{R}_{hh2}}\) . It is observed from Eq. ( 10 ) that \(R_{h{{v}_{2}}}^{2}+{\mathop {{{\overline{R}}_{0}}}}\,{{R}_{hh2}}={\mathop {\overline{R}_{0}^{2}}}\) .

Hence \(\mathop {{{\overline{R}}_{0}}}>1\) yields \(R_{h{{v}_{2}}}^{2}+{{R}_{hh2}}>{\mathop {{{\overline{R}}_{0}}}}>1.\) In this case,

Since \({{c}_{0}}>0\) and \({{c}_{2}}<0\) (when \({{\overline{R}_{0}}}>1\) ), it is obtained a unique solutions for Eq. ( 12 ), which indicates that the system ( 1 ) has a unique endemic equilibrium when \({{\overline{R}_{0}}}>1\) . Knowing that \({{c}_{2}}>0\) when \(\mathop {{R_0}}\limits ^\_ < 1\) , there are three scenarios under this condition:

If \({{c}_{1}}>0\) , the symmetry axis of \(f\left( \lambda _{h}^{*} \right) ={{c}_{0}}{{\left( \lambda _{h}^{*} \right) }^{2}}+{{c}_{1}}\lambda _{h}^{*}+{{c}_{2}}\) is on the negative half axis of x , and there is no intersection point between \(f\left( \lambda _{h}^{*} \right) \) and the positive half axis of x , so the system ( 1 ) has no endemic equilibrium.

If \({{c}_{1}}<0\) and \(c_{1}^{2}=4{{c}_{0}}{{c}_{2}}\) , there is only one intersection point between \(f\left( \lambda _{h}^{*} \right) \) and the positive half axis of x , so the system ( 1 ) has a positive equilibrium point.

If \({{c}_{1}}<0\) and \(c_{1}^{2}>4{{c}_{0}}{{c}_{2}}\) , \(f\left( \lambda _{h}^{*} \right) \) has two intersection points with the positive half axis of x , then the system ( 1 ) has two positive equilibrium points.

The above analysis concludes the following theorem.

Theorem 3.2

When \(p=0\) , if \({{\overline{R}_{0}}}>1\) , then \({{c}_{2}}<0\) , the system ( 1 ) has a unique endemic equilibrium. If \({{\overline{R}_{0}}}<1\) , the following conclusions can be drawn :

if \({{c}_{1}}>0\) , then System ( 1 ) has no endemic equilibrium ;

if \({{c}_{1}}<0\) and \(c_{1}^{2}=4{{c}_{0}}{{c}_{2}}\) , then System ( 1 ) has a unique endemic equilibrium ;

if \({{c}_{1}}<0\) and \(c_{1}^{2}>4{{c}_{0}}{{c}_{2}}\) , then System ( 1 ) has two endemic equilibria .

Theorem 3.3

When \(p=0\) , if \({{\overline{R}_{0}}}=1\) and \(d{{H}_{1}}{{H}_{3}}>d{{H}_{1}}{{a}_{3}}{{a}_{4}}+a_{3}^{2}a_{4}^{2}\mu \) , then the system ( 1 ) has a backward bifurcation; if \({{\overline{R}_{0}}}>1\) , the system ( 1 ) has a forward bifurcation and the endemic equilibrium is locally asymptotically stable .

\(X=\left( {{x}_{1}},{{x}_{2}},{{x}_{3}},{{x}_{4}},{{x}_{5}},{{x}_{6}},{{x}_{7}},{{x}_{8}},{{x}_{9}} \right) ^T\) and \(G=\left( g_{1}, g_{2}, g_{3}, g_{4}, g_{5}, g_{6}, g_{7}, g_{8}, g_{9} \right) ^T\) to be the left-hand and right-hand sides of system ( 1 ). Thus system ( 1 ) can be written as

The Jacobian matrix of system ( 1 ) at the disease-free equilibrium \({{E}_{0}}\) is

The probability of mosquito-to-human transmission b is selected as the branching parameter. When \({{\overline{R}_{0}}}=1\) , the critical value b is solved,

Therefore, when \(b={{b}^{*}}\) , the characteristic equation of the system is

where \(h(\lambda )={{\lambda }^{3}}+{{b}_{1}}{{\lambda }^{2}}+{{b}_{2}}\lambda +{{b}_{3}}\) , with \({{b}_{1}}=\mu +{{a}_{2}}+{{a}_{3}}+{{a}_{4}}\) , \({{b}_{2}}=\mu {{a}_{2}}+\mu {{a}_{3}}+\mu {{a}_{4}}+{{a}_{2}}{{a}_{3}}+{{a}_{2}}{{a}_{4}}+{{a}_{3}}{{a}_{4}}-{{H}_{3}}\) , and \({{b}_{3}}=\mu {{a}_{2}}{{a}_{3}}+\mu {{a}_{2}}{{a}_{4}}+\mu {{a}_{3}}{{a}_{4}}+{{a}_{2}}{{a}_{3}}{{a}_{4}}-{{H}_{3}}\left( \mu +{{a}_{2}} \right) \) . It follows from \({{\overline{R}_{0}}}=1\) that

Considering the coefficients of \(h\left( \lambda \right) \) , it is clear that \({{b}_{1}}=\mu +{{a}_{2}}+{{a}_{3}}+{{a}_{4}}>0,\) \({{b}_{2}}=\mu {{a}_{2}}+\mu {{a}_{3}}+\mu {{a}_{4}}+{{a}_{2}}{{a}_{3}}+{{a}_{2}}{{a}_{4}}+{{a}_{3}}{{a}_{4}}-{{H}_{3}}>0,\) \({{b}_{3}}=\mu {{a}_{2}}{{a}_{3}}+\mu {{a}_{2}}{{a}_{4}}+\mu {{a}_{3}}{{a}_{4}}+{{a}_{2}}{{a}_{3}}{{a}_{4}}-{{H}_{3}}\left( \mu +{{a}_{2}} \right)>\mu {{a}_{2}}{{a}_{3}}+\mu {{a}_{2}}{{a}_{4}}+\mu {{a}_{3}}{{a}_{4}}+{{a}_{2}}{{a}_{3}}{{a}_{4}}-\left( \mu +{{a}_{2}} \right) {{a}_{3}}{{a}_{4}}>0,\) and \({b_1}{b_2} \!-\! {b_3} = \mu \left( {\mu \!+\! {a_2} \!+\! {a_3} \!+\! {a_4}} \right) \left( {{a_2} \!+\! {a_3} \!+\! {a_4}} \right) \mathrm{{ \!+\! }}\left( {{a_3} \!+\! {a_4}} \right) \left( {a_2^2\mathrm{{ \!+\! }}{a_2}{a_3} \!+\! {a_2}{a_4}\mathrm{{ \!+\! }}{a_3}{a_4} \!-\! {H_3}} \right) > 0\) . Hence, it follows from \(Rrouth-Hurwitz\) theorem that the real parts of the characteristic roots of the equation \(h\left( \lambda \right) =0\) are all negative.

Furthermore, by calculating the eigenvalue of the matrix \({{J}_{{{b}^{*}}}}\left( {{E}_{0}} \right) \) , it is found that \({{J}_{{{b}^{*}}}}\left( {{E}_{0}} \right) \) has a zero eigenvalue, and other eigenvalues have negative real parts. Therefore, the system ( 13 ) satisfies the conditions of the Central Manifold theorem. The right eigenvector and the left eigenvector corresponding to the eigenvalues \(\lambda =0\) of the matrix \({{J}_{{{b}^{*}}}}\left( {{E}_{0}} \right) \) are respectively denoted as

where \({{w}_{1}}=-{a}_{4}{{w}_{2}}/d\) , \({{w}_{2}}>0\) , \({{w}_{3}}=\phi \delta {{w}_{2}}/{a}_{3}\) , \({{w}_{4}}=( 1-\phi )\delta {{w}_{2}}/{a}_{3}\) , \({{w}_{5}}=\eta \delta {{w}_{2}}/(d{a}_{3})\) , \({{w}_{6}}=0\) , \({{w}_{7}}= {a}_{2}{w}_{8}/\mu \) , \({{w}_{8}} = \mu {w}_{9}/\gamma \) , \({{w}_{9}}= {w}_{2}({a}_{4}- {H}_{3}/a_{3})/(bc)\) , and \({{v}_{1}}=0\) , \({{v}_{2}}>0\) , \({{v}_{3}}=(\beta {{v}_{2}}+ac{{N}_{v}^{*}}{{v}_{8}/{N}_{h}} )/{a}_{3}\) , \({{v}_{4}}=(\beta \tau {{v}_{2}}+ack{{N}_{v}^{*}}{{v}_{8}/{N}_{h}} )/{a}_{3}\) , \({{v}_{5}}={{v}_{6}}={{v}_{7}}=0\) , \({{v}_{8}}= \gamma {{v}_{9}}/{a}_{2}\) , \({{v}_{9}}=b^{*}c{{v}_{2}}/\mu \) .

According to Castillo-Chavez and Song theorem 32 , it is calculated

The sign of B will determine the occurrence of a backward bifurcation in a given model. When \(b={{b}^{*}}\) , the positive and negative of the coefficient A determines the local dynamical properties of the disease-free equilibrium 32 . Hence, it follows from Castillo-Chavez and Song theorem that system ( 1 ) undergoes a backward bifurcation at \({{\overline{R}_{0}}}=1\) if \(d{{H}_{1}}{{H}_{3}}>d{{H}_{1}}{{a}_{3}}{{a}_{4}}+a_{3}^{2}a_{4}^{2}\mu \) . When \({{\overline{R}_{0}}}>1\) and close to 1, it has \(A<0\) and thus the system has a forward branch and the endemic equilibrium is locally asymptotically stable. \(\square \)

Theorem 3.4

When \(p=0\) , if \({{\overline{R}_{0}}}>1,\) the endemic equilibrium of system ( 1 ) is globally asymptotically stable.

Define the following functions

Using the inequality \(1-x+\ln x\le 0\) , for \(x>0\) , differentiation yields:

System directed graph.

With the constants \({{a}_{ij}}\) above and \(A=[{{a}_{ij}}]\) , we construct the (strongly connected) directed graph \(\Gamma (A)\) in Fig. 2 . If and only if \({{a}_{ij}}>0\) , there is a weighted arc \(\left( i,j \right) \) . Along each of the cycles on the graph, one can verify that \(\sum {{{G}_{ij}}=0}\) , for instance, \({G_{5,4}}\mathrm{{ + }}{G_{1,5}}\mathrm{{ + }}{G_{2,1}}\mathrm{{ + }}{G_{4,2}}\mathrm{{ = }}0\) , and so on. Then, by Theorem 3.5 in 33 , there exist constants \({{c}_{i}}\) such that \(Q=\sum {_{i}{{c}_{i}}{{Q}_{i}}}\) is a Lyapunov function for system ( 1 ). To find the constants \({{c}_{i}}\) , we use the combinatorial identities \({{c}_{i}}{{a}_{ij}}=\sum \nolimits _{k=1}^{p}{{{c}_{j}}}{{a}_{jk}}\) or \({{c}_{i}}{{a}_{ij}}=\sum \nolimits _{k=1}^{p}{{{c}_{k}}}{{a}_{ki}}\) . We get \({{c}_{2}}{{a}_{2,1}}={{c}_{1}}{{a}_{1,2}}+{{c}_{4}}{{a}_{4,2}}\) , \({{c}_{3}}{{a}_{3,1}}={{c}_{1}}{{a}_{1,3}}+{{c}_{4}}{{a}_{4,3}}\) and \({{c}_{5}}{{a}_{5,4}}={{c}_{1}}{{a}_{1,5}}\) . Let \({c_1}\mathrm{{ = }}{c_4}\mathrm{{ = }}1\) , and

Then the function \(Q = {c_1}{Q_1}\mathrm{{ + }}{c_2}{Q_2}\mathrm{{ + }}{c_3}{Q_3}\mathrm{{ + }}{c_4}{Q_4}\mathrm{{ + }}{c_5}{Q_5}\) is a Lyapunov function. Its derivative along the model is

Now we consider the set \(S=\left\{ x\in R_{+}^{9}:{{Q}^{'}}=0 \right\} \) . When \({{Q}^{'}}=0\) , one can readily verify that \({{S}_{h}}{=}S_{h}^{*}, {{E}_{h}}{=}E_{h}^{*}, {{I}_{s}}{=}I_{s}^{*}, {{I}_{a}}{=}I_{a}^{*}, {{S}_{v}}=S_{v}^{*}, {{E}_{v}}=E_{v}^{*}\) and \({{I}_{v}}=I_{v}^{*}\) . For the left subsystem,

One can show that system ( 19 ) has a unique equilibrium \(\left( R_{h}^{*},A_{v}^{*} \right) \) , and that this point is globally asymptotically stable for this system. Therefore, the largest and only invariant set in S is the endemic equilibrium \({E_{0}^{*}}=\left( S_{h}^{*},E_{h}^{*},I_{s}^{*},I_{a}^{*},R_{h}^{*},A_{v}^{*},S_{v}^{*},E_{v}^{*},I_{v}^{*} \right) \) . Using LaSalle¡¯s Invariance Principle, we conclude that the endemic equilibrium \(E_{0}^{*}\) globally asymptotically stable in \(\Omega \) . \(\square \)

\(p\ne 0\) (mosquitoes hatched in contaminated water can be infected with ZIKV)

Theorem 3.5.

When \({{R}_{0}}<1\) , the disease-free equilibrium of the system ( 1 ) is globally asymptotically stable.

Substituting \({{S}_{h}}\) , \({{A}_{v}}\) and \({{S}_{v}}\) by \({{N}_{h}}-{{E}_{h}}-{{I}_{a}}-{{I}_{s}}-{{R}_{h}}\) , \({{M}_{v}}-{{J}_{v}}\) and \({{N}_{v}}-{{E}_{v}}-{{I}_{v}}\) respectively, it is obtained

It can be seen that the right side of the system ( 20 ) is the right side of the matrix \(F-V\) . According to \({{R}_{0}}=\rho \left( F{{V}^{-1}} \right) <1\) , it can be seen that the system ( 20 ) has only a balance point \(\left( {\overline{E}_{h}},{\overline{I}_{{s}}},{\overline{I}_{a}},{\overline{J}_{v}},{\overline{E}_{v}},{\overline{I}_{v}} \right) {=}\left( 0,0,0,0,0,0 \right) \) . Therefore, every non-negative solution of ( 20 ) satisfies

Because the system ( 20 ) is linear, the disease-free equilibrium of the system ( 20 ) is globally asymptotically stable.

According to the comparison theorem

The disease-free equilibrium is globally attractive, and it is locally stable. So the disease-free equilibrium of the system ( 1 ) is globally asymptotically stable. \(\square \)

Theorem 3.6

When \({{R}_{0}}>1\) , the system ( 1 ) exists endemic equilibrium .

It is denoted the expression of endemic equilibrium by

Based on the equilibrium definition, letting the right-hand side of system ( 1 ) to be zeros and substituting \(E_{1}^{*}\) , it is obtained an equation about infectivity \(\lambda _{h}^{*}\) , \(\lambda _{{{v}_{1}}}^{*}\) and \(\lambda _{{{v}_{2}}}^{*}\) as

It follows that

Substituting \(\lambda _{{{v}_{1}}}^{*}\) and \(\lambda _{{{v}_{2}}}^{*}\) into \(\lambda _{h}^{*}\) , sorted out

Substituting \(\lambda _{h}^{*}\) by 0 and \(+\infty \) , it follows that \(f\left( +\infty \right) =-1<0\) , and

According to the existence theorem of zero point, when \({{R}_{0}}>1\) , there exists \(\lambda _{h}^{*}>0\) , such that \(f\left( \lambda _{h}^{*} \right) =0\) , indicating the existence of endemic equilibrium for the system ( 1 ). \(\square \)

Model application

The massive outbreak of Zika in Brazil during 2015 and 2016 is used as a typical prototype to validate the proposed model. The \(\mathrm{{estimate}}\_\mathrm{{R}}\) function in EpiEstim package of R language is used to calculate the effective reproduction number \(R_{t}\) based on weekly morbidity time series, intergenerational distribution and window period 34 . \(R_{t}\) is the average number of people someone infected at time t can infect over their entire infectious lifespan, which can quantify the immediate transmissibility. Here \(R_{t}\) is used to determine the parameter b in the model. Since clinical studies have shown that the viral load of asymptomatically infected patients with Zika is about half that of symptomatic patients, it is assumed that the transmission probability of asymptomatic people is half that of symptomatic people 26 , 27 . In addition, due to the large temperature difference between the north and south of Brazil, the average weekly temperature \(T=24.15\,^\circ \) C of the three cities of Manaus, Brasilia and Porto Alegre (divided into the north, central and south of Brazil) is employed in the model parameters expressions.

In order to verify the model of case study, MCMC method is used to quantify the uncertain parameters: \(\vartheta \) , \(\beta \) and p . In the absence of surveillance data, it is assumed that the initial values of total mosquitoes sizes are at the positive stable level, \({{M}_{v}}(0)\) and \({{N}_{v}}(0)\) are given by (). The initial values of the numbers of vector in latent and infected states are also estimated by MCMC method. The MCMC is run for 200,000 iterations for each parameter and the posterior distributions are compiled from the final 80% of the iterations. The model is validated with 95% confidence interval of posterior estimations by sampling 1000 times of the posterior distributions of the estimated parameters and by incorporating them into the model. The normalized forward sensitivity and global sensitivity are used to quantify the importance of parameters related to the modeling incidence and the reproduction number \(R_{0}\) . The normalized forward sensitivity is computed by \(\frac{\partial R_{0} }{\partial x}\frac{x}{R_{0}}\) for parameter x . The global sensitivity is realized by computing partial rank correlation coefficient (PRCC) based on Latin hypercube sampling for the model inputs and outputs 35 .

Study area and data collection

Brazil is located in the eastern South America, with longitudes 35 \(^\circ \) W to 74 \(^\circ \) W and latitudes 5 \(^\circ \) N to 35 \(^\circ \) S. It is the largest country in South America, whose area is about 8,514,900 square kilometers. Brazil has typical tropical climate, with the annual average temperature as 20–28 \(^\circ \) C. Such climate is suitable for the growth of Aedes mosquitoes. As a result, Brazil faces public health problems related to mosquito-borne diseases.

The study use medical records of human Zika infections reported in Brazil from January 2015 to September 2016. The weekly numbers of cases is collected from the World Health Organization 36 and the Brazilian Ministry of Health, which is shown in Table S2 (see Supplementary Information [SI]). Brazilian population data is obtained from the Brazilian Institute of Statistics ( https://www.ibge.gov.br/ ). Brazil’s weekly average temperature record is extracted from the Brazilian Meteorological Agency ( https://previsao.inmet.gov.br/ ).

The reporting data shows that Brazil witnessed the first human infection in January 2015, but few case is recorded in the following 2 months. ZIKV began to expand since April, with the first epidemic peak in early July. After a continuous low incidence, human infections reached a higher peak in February 2016 and then decrease rapidly until zero in September. By fitting the epidemic curve of the cumulative number of weekly cases by the model, the estimated results of unknown parameters are shown in Table S1 and Fig. S1 . As shown in Fig. 3 a, it is observed that the estimated parameters enable the model to draw a good fitting capacity, except the first peak. The fitting deviation is possibly due to the temporal heterogeneity of transmission parameters and detection efficiency of human cases. Uncertainty analysis indicates that the model is robust in exploring transmission dynamics, which can draw consistent evolution of weekly accumulate incidence in case of random sampling (see Fig. S1 in SI).

Sensitivity analysis is used to quantify the response of model outputs to parameter variation. Results from Fig. 3 (b) indicate that the most sensitive parameter to the modeling infection is environmental capacity rate of mosquitoes ( \(\varphi \) ), followed by the human-to-human transmission rate ( \(\beta \) ) and the initial value of infected adult mosquitoes ( \({{I}_{v}}\) ). Yet the model output is not sensitive to the transmission rate from infected person fecal to larval ( p ).

( a ) The fitting results of the ZIKV cases in Brazil from the proposed model. The light colored area is the 95% confidence intervals (CIs) for all 1000 simulations. ( b ) Global sensitivity analysis for weekly incidence, where the PRCCs are the mean values in each week, and \(*\) indicates a significant difference from zero (with p value \( < 0.01\) ).

The contributions of different routes to the ZIKV infection in Brazil is estimated by splitting the values of the basic reproduction number \(R_{0}\) . Substituting the estimated parameters (in which b is chosen as the average value of the previous 7 weeks) into Eq. ( 9 ) yields the basic reproduction number to be \(R_{0}=2.13\) (95% CI 1.61–2.64), in which the contribution of mosquito transmission is 2.04 (95% CI 1.53–2.55). Moreover, the transmission of the virus by mosquitoes could be divided into adult mosquitoes and larval mosquitoes in sewage, in which the latter contribution to \(R_{0}\) is estimated to be 0.48 (95% CI 0.26–0.71).

Results of sensitivity analysis toward \(R_{0}\) are presented in Fig. 4 . Two different methods of sensitivity analysis show similar results, indicating the robustness of \(R_{0}\) to the parameters used. It is observed that the mortality of adult mosquitoes ( \(\mu \) ), infection period of human beings ( \(\eta \) ), mosquito biting rate ( c ), environmental capacity rate of mosquitoes ( \(\varphi \) ), human-mosquito transmission rates ( a and b ) and transition rate of mosquitoes from larval to adult ( \(\alpha \) ) are most sensitive parameters to determine \(R_{0}\) . Yet \(R_{0}\) is less sensitive to the transmission rates from fecal to larval and from human to human ( p and \(\beta \) ), oviposition rate of adult mosquitoes ( \(\theta \) ) proportion of symptomatical infections ( \(\phi \) ), human death rate ( d ) and relative infectivity of asymptomatic infections ( q and \(\tau \) ). These parameters could play minor roles in causing human infection of ZIKV.

Sensitivity analysis of the basic reproduction number \(R_{0}\) . ( a ) Normalize forward sensitivity; ( b ) global sensitivity with PRCC.

Figure 5 shows the effects of different transmission paths of the Zika outbreak in Brazil on the cumulative number of human infections from January 2015 to September 2016. The fitting results demonstrate that the total infections could be 304,648 (95% CI 304,096–305,199). If without human infection by sex or without larvae mosquito infection by sewage, this number could be 242,487 (95% CI 242,025–242,949) or 297,115 (95% CI 296,558–297,674). If without both of the above transmission routs, it could become 236,455 (95% CI 235,994–236,918). Of these three assumptions, the total number of human infections decreased by 20.4%, 2.47% and 22.38%, respectively. Moreover, in the absence of asymptomatic infection, the cumulative number of human infections could be 254,715 (95% CI 254,238–255,192), making human infections decrease by 16.39%. In this case, the above-mention three circumstance lead to the declines of human infections by 6.43%, 0.79% and 7.17%, respectively.

Influence of cutting off different transmission routes on the outbreak of Zika. The cumulative numbers of humans infection in Brazil with 95% CIs are estimated in cases of different transmission routes during January 2015 and September 2016.

Figure 6 shows the time evolution of human infection in cases of different human-to-human transmission rate \( (\beta )\) , larval mosquito transmission rate in sewage ( p ) and temperature. It is observed that the increase of transmission rates through sex and sewage would lead to moderately higher number of human cases and slightly faster of disease transmission, Such effect caused by high sex transmission rate is more significant. Furthermore, temperature around \(28.7\,^\circ \) C is most favourable for ZIKV infection, and temperature away from this value could cause low morbidity and low infection risk.

Impacts of ( a ) sexual transmission rate \(\beta \) , ( b ) sewage transmission rate p and ( c ) temperature on the number of new infections cases, which is achieved by simulating the proposed model with other parameters equal to those of the fitting results.

Figure 7 shows the effectiveness of the implementation of control measures on the spread of ZIKV infection in Brazil during January 2015 and November 2016. The intervention is measured by the effective reproduction number \(R_{t}\) . Here the values of \(R_{t}\) are fixed to be 2.17, 2.12, 1.98, 1.83, 1.70 and 1.62, which are its average values of in the previous 1–5, 1–10, 1–15, 1–20, 1–25 and 1–30 weeks, respectively. The simulation results indicate that (1) if \(R_{t}\) = 2.17 (few intervention measures), the cumulative number of human infections could reach 37.2 million, that is over 121 times of reported cases, with early peak of new cases as 3.7 million around the 37th week; (2) if \(R_{t}\) = 1.62 (limited intervention measures), the cumulative number of human cases could be 36 million, with peak number of new cases as 2.1 million around the 57th week. It is observed that the decrease of \(R_{t}\) causes an evident decline of humans infections and quick arriving of peak infection.

Impacts of different effective reproduction number on the number of human infection in Brazil during January 2015 and November 2016, which is achieved by simulating the proposed model with other parameters equal to those of fitting results.

A modeling framework for inferring ZIKV transmission patterns is attempted in this paper. Technologically, a new SEIR-AJ-SEI dynamic model is established, which couples the ZIKV circulation among/between mosquitoes and humans under potential routes, including mosquito bite, sex contact, and sewage breed. Compared with existing ZIKV model, such as using a discrete stochastic SEIR-SEI model to predict the optimal effect of bednets, infection treatment and insecticide spraying on disease transmission 18 , using a SEIIAR-SEI model to infer the impact of mosquito-borne and sexual transmission on ZIKV spread 9 , using a continuing climate-driven SEIIIR-SEI model to study threshold dynamics in a seasonal model of Zika virus disease 19 , using a high-dimensional ODE system to describe the joint dynamics of Zika and dengue 17 , and using partial differential equations model to understand how spatial heterogeneity of the vector and host populations influence ZIKV dynamics 16 , the proposed model is a combined update of recent works, which converges more dynamical detail.

First, the ZIKV transmission dynamics are clarified mathematically. The basic reproduction number \(R_{0}\) is calculated by using the next generation matrix, which is found to be determined by all the transmission routes. It is verified that the disease-free equilibrium is locally stable when the associated basic reproduction number is less than unity, and there exits endemic equilibrium when basic reproduction number is larger than unity. If without larval infection in virus sewage, central manifold theorem demonstrates that the system is capable of undergoing the phenomenon of backward bifurcation, under which the stable disease-free equilibrium would co-exist with a stable endemic equilibrium and an unstable endemic equilibrium. Such phenomenon could be caused by the combined effects of multiple transmission routes. The existence of larval infection in virus sewage would cause more complicated transmission dynamics. Dynamic details indicate that great efforts could be needed for preventing ZIKV infection.

Second, the proposed model is further validated to explore more transmission dynamics by fitting the reported cases of ZIKV infection in Brazil from January 2015 to September 2016. Two important insights based on this study may provide scientific clues for evaluating the infection risk and guiding control.

On the one hand, the impact of the transmission routes on the Zika epidemic is evaluated. It is found that mosquito-human infection by bite is still the prominent path for ZIKV occurrence, accounting for 85.7% of the basic reproduction number \(R_{0}\) , but the contributions by sexual transmission and larval transmission in sewage are 3.5% and 10.8%, respectively, both of which are less than 1. Therefore, these two routes of infection are not enough to trigger a large-scale outbreak of ZIKV, which is consistent with previous studies 9 , 11 , 15 . The sensitivity analysis further confirms that ZIKV infection is dominated by the parameters related to mosquito ecology, rather than those parameters related to asymptomatic or human-human transmission. Yet the latter two transmission routes can limitedly accelerate the development of Zika epidemic and prolongs the outbreak time. Such effects would be more significant for higher concentration of ZIKV in sewage and larger probability of human-to-human infection. Therefore, the prevention and control of ZIKV should target at reducing the infection through mosquito bite, and do not ignore the infection through sex and sewage.

On the other hand, the situations of ZIKV transmission in Brazil are evaluated. The present study suggests that multiple modes of transmission and suitable temperature may be responsible for the large outbreak of ZIKV in Brazil in 2015–2016. Nevertheless, the intervention implemented in Brazil plays an important role in controlling ZIKV infections. If without intervention, the number of human infections with ZIKV in Brazil would increase rapidly 37 , and result in more than 37.2 million cases. After the implementation of control measures in May 2015, the number of effective reproduction \(R_{t}\) decreased from 1.69 to less than 1, leading to a rapid decline in morbidity. However, human infections began to rebound rapidly in November of the same year, leading to the second peak of cases in Brazil at 59th week. Meanwhile, control measures were intensified, including mobilizing Brazilian army to support community health services 37 , house-to-house visits and the elimination of potential Aedes breeding sites 37 , aerial spraying of the product to kill larvae or adult mosquito 38 , and reduction of breeding sites through drainage of standing water, waste management and education about mosquitoes and personal protection measures 39 . Under these control measures, the incidence and effective reproduction number dropped fast. The present study indicates that such comprehensive and intensified ZIKV control strategies are highly effective in curtailing ZIKV transmission.

The following limitations need to be clarified. First, since the proposed model is only used to fit the surveillance data reported in Brazil, there may be geographical differences in its application to other countries. Second, since it is impossible to obtain the true values of some model parameters, they are extracted from the literature or are estimated by MCMC method. Third, the study dose not include all the underlying factors, such as human mobility and climate (except temperature). However, the model takes into account the most influential factors and incorporates model parameterizations, providing confidence in the model output for future analysis.

Data availability

All data generated or analysed during this study are included in this article and its supplementary information files.

Simpson, D. et al. Zika virus infection in man. Trans. R. Soc. Trop. Med. Hyg. 58 (4), 335–338. https://doi.org/10.1016/0035-9203(64)90200-7 (1964).

Article   CAS   PubMed   Google Scholar  

Musso, D., Nilles, E. & Cao-Lormeau, V. M. Rapid spread of emerging Zika virus in the Pacific area. Clin. Microbiol. Infect. 20 (10), O595–O596. https://doi.org/10.1111/1469-0691.12707 (2014).

Bogoch, I. I. et al. Anticipating the international spread of Zika virus from Brazil. Lancet 387 (10016), 335–336. https://doi.org/10.1016/S0140-6736(16)00080-5 (2016).

Article   PubMed   PubMed Central   Google Scholar  

Pan American Health Organization (PAHO). Zika virus infection. https://www.paho.org/en/documents/25-august-2017-zika-epidemiological-update-0 .

Mlakar, J. et al. Zika virus associated with microcephaly. N. Engl. J. Med. 374 (10), 951–958. https://doi.org/10.1056/NEJMoa1600651 (2016).

Cauchemez, S. et al. Association between Zika virus and microcephaly in French Polynesia, 2013–15: A retrospective study. Lancet 387 (10033), 2125–2132. https://doi.org/10.1016/S0140-6736(16)00651-6 (2016).

Duffy, M. R. et al. Zika virus outbreak on yap island, federated states of micronesia. N. Engl. J. Med. 360 (24), 2536–2543. https://doi.org/10.1056/NEJMoa0805715 (2009).

Musso, D. et al. Potential for Zika virus transmission through blood transfusion demonstrated during an outbreak in French Polynesia, november 2013 to february 2014. Eurosurveillance 19 (14), 20761. https://doi.org/10.2807/1560-7917.ES2014.19.14.20761 (2014).

Article   PubMed   Google Scholar  

Gao, D. et al. Prevention and control of zika as a mosquito-borne and sexually transmitted disease: A mathematical modeling analysis. Sci. Rep. 6 (1), 1–10. https://doi.org/10.1038/srep28070 (2016).

Article   CAS   Google Scholar  

Agusto, F. B., Bewick, S. & Fagan, W. Mathematical model of Zika virus with vertical transmission. Infect. Dis. Model. 2 (2), 244–267. https://doi.org/10.1016/j.idm.2017.05.003 (2017).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Wang, L. & Zhao, H. Modeling and dynamics analysis of Zika transmission with contaminated aquatic environments. Nonlinear Dyn. 104 , 845–862. https://doi.org/10.1007/s11071-021-06289-3 (2021).

Article   Google Scholar  

Wang, L., Zhao, H., Oliva, S. M. & Zhu, H. Modeling the transmission and control of Zika in Brazil. Sci. Rep. 7 (1), 7721. https://doi.org/10.1038/s41598-017-07264-y (2017).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Bonaldo, M. C. et al. Isolation of infective Zika virus from urine and saliva of patients in Brazil. PLoS Negl. Trop. Dis. 10 (6), e0004816. https://doi.org/10.1371/journal.pntd.0004816 (2016).

Du, S. et al. Aedes mosquitoes acquire and transmit Zika virus by breeding in contaminated aquatic environments. Nat. Commun. 10 (1), 1–11. https://doi.org/10.1038/s41467-019-09256-0 (2019).

Towers, S. et al. Estimate of the reproduction number of the Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission. Epidemics 17 (2016), 50–55. https://doi.org/10.1016/j.epidem.2016.10.003 (2015).

Cai, Y., Ding, Z., Yang, B., Peng, Z. & Wang, W. Transmission dynamics of Zika virus with spatial structure—a case study in Rio de Janeiro, Brazil. Phys. A 514 , 729–740. https://doi.org/10.1016/j.physa.2018.09.100 (2019).

Article   MathSciNet   Google Scholar  

Wang, L. & Zhao, H. Dynamics analysis of a Zika-dengue co-infection model with dengue vaccine and antibody-dependent enhancement. Phys. A 522 , 248–273. https://doi.org/10.1016/j.physa.2019.01.099 (2019).

Bonyah, E., Khan, M. A., Okosun, K. & Islam, S. A theoretical model for Zika virus transmission. PLoS One 12 (10), e0185540. https://doi.org/10.1371/journal.pone.0185540 (2017).

Ibrahim, M. A. & Dénes, A. Threshold dynamics in a model for Zika virus disease with seasonality. Bull. Math. Biol. 83 (4), 1–28. https://doi.org/10.1007/s11538-020-00844-6 (2021).

Reiner, R. C. Jr. et al. A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970–2010. J. R. Soc. Interface 10 (81), 20120921. https://doi.org/10.1098/rsif.2012.0921 (2013).

Moulay, D., Alaoui, M. A. A. & Cadivel, M. The Chikungunya disease: Modelling, vector and transmission global dynamics. Math. Biosci. 229 , 50–63. https://doi.org/10.1016/j.mbs.2010.10.008 (2011).

Article   MathSciNet   CAS   PubMed   Google Scholar  

Traore, B., Koutou, O. & Sangare, B. A global mathematical model of malaria transmission dynamics with structured mosquito population and temperature variations. Nonlinear Anal. RWA 53 , 103081. https://doi.org/10.1016/j.nonrwa.2019.10308 (2020).

Wesolowski, A. et al. Impact of human mobility on the emergence of dengue epidemics in Pakistan. Proc. Natl. Acad. Sci. 112 (38), 11887–11892. https://doi.org/10.1073/pnas.1504964112 (2015).

Yang, H., Macoris, M., Galvani, K., Andrighetti, M. & Wanderley, D. Assessing the effects of temperature on the population of Aedes Aegypti, the vector of dengue. Epidemiol. Infect. 137 (8), 1188–1202. https://doi.org/10.1017/S0950268809002040 (2009).

Lambrechts, L. et al. Impact of daily temperature fluctuations on dengue virus transmission by Aedes Aegypti. Proc. Natl. Acad. Sci. 108 (18), 7460–7465. https://doi.org/10.1073/prias.1101377108 (2011).

Aubry, M., Richard, V., Green, J., Broult, J. & Musso, D. Inactivation of Zika virus in plasma with amotosalen and ultraviolet a illumination. Transfusion 56 (1), 33–40. https://doi.org/10.1111/trf.13271 (2016).

Musso, D. & Gubler, D. J. Zika virus. Clin. Microbiol. Rev. 29 (3), 487–524. https://doi.org/10.1056/NEJMra1602113 (2016).

Haby, M. M., Pinart, M., Elias, V. & Reveiz, L. Prevalence of asymptomatic Zika virus infection: A systematic review. Bull. World Health Organ. 96 (6), 402. https://doi.org/10.2471/BLT.17.201541 (2018).

Charrel, R. N., Leparc-Goffart, I., Pas, S., Lamballerie, X. D. & Reusken, C. State of knowledge on Zika virus for an adequate laboratory response. Bull. World Health Organ. 94 , 8. https://doi.org/10.2471/BLT.16.171207 (2017).

Paz-Bailey, G. et al. Persistence of Zika virus in body fluids. N. Engl. J. Med. 379 (13), 1234–1243. https://doi.org/10.1056/NEJMoa1613108 (2018).

Van den Driessche, P. & Watmough, J. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 180 (1–2), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6 (2002).

Article   MathSciNet   PubMed   Google Scholar  

Castillo-Chavez, C. & Song, B. Dynamical models of tuberculosis and their applications. Math. Biosci. Eng. 1 (2), 361. https://doi.org/10.3934/mbe.2004.1.361 (2004).

Shuai, Z. & van den Driessche, P. Global stability of infectious disease models using lyapunov functions. SIAM J. Appl. Math. 73 (4), 1513–1532. https://doi.org/10.1137/120876642 (2013).

Thompson, R. et al. Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics 29 , 100356. https://doi.org/10.1016/j.epidem.2019.100356 (2019).

Marino, S., Hogue, I. B., Ray, C. J. & Kirschner, D. E. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theor. Biol. 254 (1), 178–196. https://doi.org/10.1016/j.jtbi.2008.04.011 (2008).

Article   ADS   MathSciNet   PubMed   PubMed Central   Google Scholar  

World Health Organization (WHO). Zika cases from the World Health Organization. http://www.who.int/emergencies/zika-virus/situation-report/en/ .

Heukelbach, J., Alencar, C. H., de Kelvin, A. A., de Oliveira, W. K. & Góes Cavalcanti, L. P. Zika virus outbreak in Brazil. J. Infect. Dev. Countr. 10 (2), 116–120. https://doi.org/10.3855/jidc.8217 (2016).

Schoch-Spana, M. et al. Vector control in Zika-affected communities: Local views on community engagement and public health ethics during outbreaks. Prev. Med. Rep. 18 , 101059. https://doi.org/10.1016/j.pmedr.2020.101059 (2020).

Stetson, A. Zika Virus: Control Measures for an Emerging Pathogen in Brazil (Boston University, 2017).

Google Scholar  

Download references

Acknowledgements

This research was jointly is funded by the National Natural Science Foundation of China (12171116), Director Fund Project of the Ministry of Education Key Laboratory of Cognitive Radio and Information Processing (CRKL210106) and Guangxi Key Laboratory of Cryptography and Information Security (GCIS201707).

Author information

Authors and affiliations.

Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology), Guilin, 541004, China

Liying Wang, Guanghu Zhu, Guanlin Ou & Tian Tang

School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, 541004, China

Liying Wang, Qiaojuan Jia & Guanghu Zhu

School of Information and Communication, Guilin University of Electronic Technology, Guilin, 541004, China

You can also search for this author in PubMed   Google Scholar

Contributions

L.W.: formal analysis, methodology, visualization, funding acquisition, writing—original draft; Q.J.: data curation, methodology, software, visualization, writing—review and editing; G.Z.: resources, conceptualization, funding acquisition, writing—review and editing; G.O.: methodology, software, writing—review and editing; T.T.: project administration, visualization, supervision, funding acquisition, writing—review and editing.

Corresponding author

Correspondence to Tian Tang .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary information., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Wang, L., Jia, Q., Zhu, G. et al. Transmission dynamics of Zika virus with multiple infection routes and a case study in Brazil. Sci Rep 14 , 7424 (2024). https://doi.org/10.1038/s41598-024-58025-7

Download citation

Received : 03 December 2023

Accepted : 25 March 2024

Published : 28 March 2024

DOI : https://doi.org/10.1038/s41598-024-58025-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Transmission dynamics
• Infection risk

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.