case study of tuberculosis patient in india

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Published: 20 June 2024

A mixed-methods study on impact of active case finding on pulmonary tuberculosis treatment outcomes in India

Akshat P. Shah 1 ,
Jigna D. Dave 2 ,
Mohit N. Makwana 1 , 3 ,
Mihir P. Rupani 1 , 4 &
Immad A. Shah 5

Archives of Public Health volume 82 , Article number: 92 ( 2024 ) Cite this article

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Tuberculosis (TB) remains a significant public health burden in India, with elimination targets set for 2025. Active case finding (ACF) is crucial for improving TB case detection rates, although conclusive evidence of its association with treatment outcomes is lacking. Our study aims to investigate the impact of ACF on successful TB treatment outcomes among pulmonary TB patients in Gujarat, India, and explore why ACF positively impacts these outcomes.

We conducted a retrospective cohort analysis in Gujarat, India, including 1,638 pulmonary TB cases identified through ACF and 80,957 cases through passive case finding (PCF) from January 2019 to December 2020. Generalized logistic mixed-model compared treatment outcomes between the ACF and PCF groups. Additionally, in-depth interviews were conducted with 11 TB program functionaries to explore their perceptions of ACF and its impact on TB treatment outcomes.

Our analysis revealed that patients diagnosed through ACF exhibited 1.4 times higher odds of successful treatment outcomes compared to those identified through PCF. Program functionaries emphasized that ACF enhances case detection rates and enables early detection and prompt treatment initiation. This early intervention facilitates faster sputum conversion and helps reduce the infectious period, thereby improving treatment outcomes. Functionaries highlighted that ACF identifies TB cases that might otherwise be missed, ensuring timely and appropriate treatment.

ACF significantly improves TB treatment outcomes in Gujarat, India. The mixed-methods analysis demonstrates a positive association between ACF and successful TB treatment, with early detection and prompt treatment initiation being key factors. Insights from TB program functionaries underscore the importance of ACF in ensuring timely diagnosis and treatment, which are critical for better treatment outcomes. Expanding ACF initiatives, especially among hard-to-reach populations, can further enhance TB control efforts. Future research should focus on optimizing ACF strategies and integrating additional interventions to sustain and improve TB treatment outcomes.

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Text box 1. Contributions to the literature
• Our study underscores active case finding’s (ACF’s) significant role in improving TB treatment outcomes in India, offering evidence-based insights.
• We identify district-level variability in treatment outcomes and consistent predictors across settings, enhancing contextual understanding.
• Insights into ACF mechanisms emphasize its importance in early case detection and treatment initiation, critical for reducing TB morbidity and mortality.
• Qualitative perspectives provide practical strategies to optimize ACF effectiveness, addressing complex TB challenges in resource-limited settings.

Introduction

Tuberculosis (TB) remains a formidable public health challenge worldwide, with the World Health Organization (WHO) estimating 10.6 million new cases reported globally in 2022 [ 1 ]. India, as one of the most populous countries, shoulders a significant burden of this disease, reporting 2.8 million incident cases of TB in the year 2022, constituting nearly 27% of the global caseload [ 1 , 2 ]. In fact, India consistently reports the highest number of TB cases globally [ 1 , 2 , 3 , 4 ]. Within India, the state of Gujarat recorded approximately 1.5 lakh notified TB cases in 2021 [ 2 ]. This high prevalence of TB underscores the urgent need for effective strategies to control and eliminate the disease [ 5 ]. One of these strategies is active case finding (ACF), a proactive approach involving systematic screening of the population through house-to-house visits conducted by healthcare staff, a part of national strategic plan of TB elimination in India [ 5 ]. In the year 2022, 48,329 TB cases (2.5%) were diagnosed through ACF in India [ 2 ].

The World Health Organization (WHO) advises conducting TB screening for individuals in close contact with TB patients, those living with HIV, as well as various vulnerable groups such as miners, prisoners, migrants, and indigenous populations [ 6 ]. Globally, evidence exists to understand the efficacy of ACF compared to passive case finding (PCF) in increasing case notifications and detecting undetected cases [ 7 , 8 ]. Importantly, evidence suggests that the efficacy of ACF in detecting new cases is particularly pronounced in developing countries, as compared to developed ones [ 9 , 10 , 11 , 12 , 13 , 14 ]. For instance, in the Philippines, ACF detected high rates of TB, whereas in Indonesia, no cases were detected through ACF [ 15 , 16 ]. However, among pregnant women, the number of new TB cases diagnosed through ACF has been reported to be low [ 17 ].

In India, the national TB program introduced ACF in 2017 with a focus on several key populations [ 18 ]. India has set an ambitious goal to eliminate TB by the year 2025, 5 years ahead of the global targets [ 5 , 18 , 19 ]. Previous studies in India have reported varying rates of TB positivity through ACF, ranging from as low as 0.17% among migrant workers to 17% overall [ 19 , 20 ]. Primarily, studies have emphasized the increase in TB case detection yields through ACF [ 21 ]. Additionally, research has focused on documenting the outcomes of contact investigations, revealing rates as high as 5% in southern India and 1.5% in remote tribal areas [ 19 , 22 ].

ACF plays a multifaceted role in curbing the TB epidemic: it not only reduces disease transmission by shortening the infectious period of patients but also contributes to earlier diagnosis and treatment, ultimately enhancing treatment outcomes [ 23 , 24 , 25 ]. Despite the importance of ACF, existing systematic reviews and meta-analyses fail to adequately address its association with TB treatment outcomes [ 26 ]. For instance, while one meta-analysis found no difference in treatment success between ACF and PCF groups [ 27 ], studies outside India have also reported conflicting results [ 28 , 29 ]. Moreover, within India, there is limited and inconsistent evidence on the impact of ACF on TB treatment outcomes [ 30 , 31 , 32 , 33 ]. Such inconsistencies underscore the critical need for further investigation. Thus, our study aims to bridge this gap by establishing the association between ACF and TB treatment outcomes while also exploring why ACF positively impacts these outcomes.

Study design and duration

Our study employed an explanatory mixed-methods approach, integrating a retrospective cohort study with qualitative interviews. We aimed to explore the impact of active case finding (ACF) on TB treatment outcomes and gather perspectives from key stakeholders regarding the mechanisms through which ACF contributes to the improvement of TB treatment outcomes. Data collection for the quantitative component spanned September 2022. Qualitative interviews with key stakeholders from the National TB Elimination Program (NTEP) were conducted between January and April 2023, guided by a comprehensive topic guide.

Study setting

Our study used state-level data from Gujarat, India. Gujarat, with a population of 60,439,692 and a literacy rate of 78% according to the 2011 Census, presents a diverse and significant setting for TB control efforts [ 34 ]. The state reported 104,696 TB cases in the public sector and 54,462 in the private sector in 2019 [ 35 ]. With approval from the State TB Cell of Gujarat, we accessed data on ACF and PCF for 2019 and 2020 through the Nikshay online portal. Initially, ACF in India was conducted thrice yearly for 15 days each in vulnerable populations [ 18 ]. In Gujarat, ACF surveys are now held every 2nd and 4 th Tuesday monthly, with flexibility to increase frequency. Health workers follow a protocol for symptom screening and testing using smear microscopy, X-rays, and nucleic acid amplification tests [ 18 , 36 ]. Gujarat, with 33 districts, eight municipal corporations, and three union territories, has made significant strides in TB management, reporting the lowest TB prevalence reported in a recent nationwide survey [ 37 ]. The state has a treatment success rate of 89%, low loss to follow-up rates at 1.8% and a treatment failure rate of 0.7% [ 2 ]. Nearly 50% of ACF-diagnosed cases did not present typical symptoms but showed radiological evidence of TB, suggesting early detection [ 2 ]. Gujarat’s ACF program targets approximately 6.2 million individuals, including those in de-addiction centers and with mental health conditions, enhancing TB detection efforts [ 2 ].

Study population

Quantitative.

We enrolled 82,595 eligible patients diagnosed with pulmonary TB from 249,966 notified cases between January 2019 and December 2020 across 39 diagnosing districts in Gujarat (see Supplementary Table 1 in Additional file 1 for detailed distribution across different diagnosing districts). The exposure group consisted of 1,638 patients diagnosed through ACF, while 80,957 patients diagnosed through PCF served as the unexposed group. We applied strict exclusion criteria to maintain data quality [ 38 ].

Qualitative

We employed a purposive sampling strategy to ensure diverse perspectives from various TB program sectors, with participants’ experience ranging from 2 to 25 years. We conducted 11 interviews with key stakeholders, including the district and city TB officers, a senior treatment supervisor, an additional director from the State TB Training and Demonstration Center (STDC) in Ahmedabad, WHO consultants from the TB cell in Gandhinagar, the head of the TB laboratory at STDC in Ahmedabad, and an epidemiologist from STDC in Ahmedabad. Interview durations ranged from 5 to 22 min. Saturation of responses was monitored throughout, with two additional interviews conducted to confirm that saturation had been reached.

Study variables (quantitative)

Outcome variable.

Successful treatment outcomes encompass patients categorized as “cured” (those with a negative sputum at the end of treatment) and those who have “completed treatment” (patients who have finished the full course of treatment without any radiological or clinical deterioration) [ 36 ]. Conversely, unsuccessful outcomes include individuals categorized as “loss to follow-up” (patients who discontinued treatment for at least one consecutive month), “treatment failure” (patients with sputum positivity at the end of treatment), and “died” (patients who passed away while undergoing treatment) [ 36 ].

Exposure variable

Patients were categorized based on their diagnostic method: ACF (exposed group) and PCF (unexposed group).

Confounding variable

We considered several potential confounding variables, including age, gender, sputum positivity, HIV status, and diabetes status.

Data collection

Data were collected from the Nikshay online portal, managed by the State TB Training and Demonstration Centre (STDC) in Ahmedabad, Gujarat. Detailed district-wise Excel spreadsheets were used, containing information on patients diagnosed through ACF. These were cross-referenced with Nikshay IDs from the notification register to distinguish between ACF and PCF cases. Permission was obtained before the retrospective data collection process. The dataset included age, gender, address, HIV status, diabetes status, TB site, sputum positivity, and treatment outcomes for both ACF and PCF cases, covering Gujarat from January 1, 2019, to December 31, 2020.

In-depth interviews were conducted by the principal investigator and experienced co-investigators using a purposive sampling approach. Interviewees were selected for their ability to offer diverse insights relevant to comparing treatment outcomes between TB patients identified through ACF and PCF. All interviews were conducted face-to-face in a conducive environment, with flexibility in scheduling to accommodate participants’ availability. One initial refusal was resolved by including an alternative participant. To enhance data validity and reliability, the interview guide (see Additional file 2 ) was pilot tested among study authors. The data collection process was meticulously documented, including informed consent and audio recordings.

Statistical analysis

Data analysis was performed using RStudio version 4.3.3, with a significance threshold of p < 0.05. Generalized logistic mixed-effects models (GLMM) were used to estimate both random and fixed effects, employing the glmer() function from the {lme4} package in RStudio. The model included fixed effects (ACF, age, gender, HIV status, diabetes status, and sputum result) and random effects (diagnosing district), accounting for clustering by district. The model used a binomial family with a logit link function, suitable for binary outcome data. The intra-cluster correlation coefficient (ρ) was calculated using the clus.rho() command from the {fishmethods} package in RStudio to measure clustering resemblance within groups. Bootstrap analysis was performed using the boot() function from the {boot} package in RStudio to estimate the uncertainty of predictor coefficients.

All interviews were conducted in Gujarati for cultural sensitivity and participant engagement, then transcribed into English. The transcripts were documented in Microsoft Word (see Additional file 3 ), facilitating efficient data management and analysis. Investigators A.S. and M.M. assigned codes to the transcriptions, which were compiled into a Microsoft Excel sheet. Codes were organized into meaningful categories using an inductive approach, allowing themes to emerge directly from the data. Regular discussions and reviews among investigators M.R., J.D., and M.M. ensured the trustworthiness and reliability of the analysis. Investigator A.S. established a final codebook (see Additional file 4 ) to provide a standardized framework for subsequent data analysis and interpretation.

Selection of study participants

A data of total 249,966 was collected, of which 82,595 eligible patient data was included in the further analysis (Fig. 1 ). Out of the total eligible sample size, 1638 were diagnosed through ACF and the remaining 80,957 were diagnosed through PCF.

Selection of patients notified with pulmonary TB in the public sector in Gujarat during 2019–2020

Characteristics of study participants

ACF patients, with a median age of 43 years (IQR: 29–58), were older than PCF patients, whose median age was 36 years (IQR: 25–52) ( p < 0.001) (Table 1 ). While no significant gender difference was observed between the groups (ACF: 34% female, PCF: 34%, p = 0.738), notable disparities were found in HIV positivity (ACF: 0.4%, PCF: 3%, p < 0.001) and diabetes prevalence (ACF: 5%, PCF: 6%, p = 0.03). Additionally, sputum-positive TB cases were less frequent in ACF (55%) compared to PCF (64%) ( p < 0.001). Treatment success rates were higher in ACF (94%) than in PCF (91%) ( p < 0.001).

Association of ACF with successful TB treatment outcomes

On our generalized logistic mixed-effects model analysis, we found that individuals identified through ACF had 1.4 times higher odds (95% CI: 1.12–1.73, p = 0.002) of achieving successful TB treatment outcomes compared to those identified through PCF (Table 2 ). Furthermore, Each additional year of age was associated with a 3% decrease in the odds of successful TB treatment (adjusted OR: 0.973, 95% CI: 0.971–0.974, p < 0.001). Male individuals exhibited a 30% decrease in odds compared to female individuals (adjusted OR: 0.70, 95% CI: 0.66–0.74, p < 0.001). HIV-positive individuals demonstrated a 76% lower odds of successful TB treatment compared to HIV-negative individuals (adjusted OR 0.24, 95% CI: 0.21–0.26, p < 0.001). Additionally, individuals with sputum-positive TB had a 32% lower odds of successful TB treatment compared to those with sputum-negative results (adjusted OR: 0.68, 95% CI: 0.65–0.72, p < 0.001). Interestingly, diabetic status did not show a significant association with treatment success (adjusted OR: 1.01, 95% CI: 0.92–1.11, p = 0.824).

Moreover, our analysis accounted for variability across districts, revealing a variance of 0.063 attributed to diagnosing facility district, indicating significant variations in successful TB treatment outcomes between different districts. The intra-cluster correlation coefficient (ICC) for the exposure group (ACF vs. PCF) was found to be 0.0101, suggesting a weak resemblance of the units within each particular group (see Additional file 5 ). Furthermore, despite considering multiple districts in our study, the coefficients for all predictors remained consistent, as observed from the bootstrap analysis (see Additional file 5 ).

The median (IQR) years of experience for the 11 participants in the in-depth interviews were 12 (2–25) years. Among the participants, one was a female. Analysis of the codebook resulted in the identification of two fundamental themes: ‘ACF and TB outcomes’ and ‘Strengthening ACF implementation’ (see Fig. 2 and read Additional file 4 for description of each code).

Perceptions of TB program functionaries on active case finding (ACF) and TB treatment outcomes during January-April 2023 in Gujarat

ACF and TB outcomes

Program functionaries highlighted the pivotal role of ACF within the national TB program. ACF was emphasized for its effectiveness in augmenting case detection rates, identifying previously undetected TB cases, and enabling early detection and prompt initiation of TB treatment. This approach helps achieve quicker non-infectious status among patients, facilitates early sputum conversion, and breaks the chain of TB transmission from asymptomatic primary cases to their close contacts. Consequently, ACF reduces the incidence of new cases and prevents the progression of the disease in untreated asymptomatic cases. Within the framework of the national TB program, ACF was viewed as a superior strategy compared to PCF.

“There are research studies that show that the patients getting diagnosed, may likely to get delayed up to 15-20 days as well as they visit around 1-7 facilities before actually diagnosing the TB cases. So, this ACF model is a good implementation to have an early case detection and that is why we are going house-to-house to detect cases early. So overall, ACF is great tool to detect those missing cases, as well as kind of early case detection.” (TB program functionary, 9 years of work experience)

Strengthening ACF implementation

Experts highlighted several avenues for strengthening the implementation of ACF. These include increasing field visits, deploying dedicated staff for comprehensive surveillance, incentivizing healthcare workers, and intensifying supervision. Additional strategies to strengthen national TB program include improving diagnostic capabilities, raising awareness, and optimizing resource allocation. Experts also stressed the importance of screening for latent tuberculosis infection (LTBI) within communities, aiming to identify individuals at risk and facilitate early intervention through preventive treatment. In resource-constrained settings, prioritizing secondary prevention over primary prevention was seen as more practical for TB elimination due to factors such as large family sizes, overcrowding, poor nutrition, limited awareness, restricted healthcare access, and neglect.

“We need to improve and strengthen the supervision. We are training the supervisory staff, so that they can check the quality and number of sputum samples collected by the field worker. Also, the field worker needs to be trained on how to collect the sputum. How to counsel the suspect and his family. It will improve the overall outcome of the program.” (TB program functionary, 25 years of work experience). “Our aim is not only increasing the number of case detection, but also parallelly rule out TB in the same community. Those ruled out, should be put on preventive treatment, by checking for LTBI [latent tuberculosis infection] positivity. So, the objective of the intervention is not only case detection, but also to prevent LTBI.” (TB program functionary, 9 years of work experience).

Summary and brief explanation of findings

Our study underscores the significant impact of active case finding (ACF) on improving TB treatment outcomes in Gujarat. ACF, accounting for 2% of TB cases in our study, aligns with the national average of 2.5% in India [ 18 ], signifying its important role in improving TB treatment outcomes. Program functionaries emphasized the urgency to intensify ACF practices to enhance early case detection and prompt initiation of TB treatment, achieving quicker non-infectious status, and facilitate early sputum conversion, thereby reducing the spread of TB [ 23 ].

The favorable treatment outcomes observed in Gujarat can be attributed to several factors, including the state’s diligent TB care and support infrastructure, characterized by the lowest TB prevalence, a success rate of 89%, low loss to follow-up rates at 1.8%, and a treatment failure rate of 0.7% [ 2 , 37 ]. Notably, the implementation of bi-monthly ACF activities, particularly on Tuesdays, likely played a significant role in these outcomes. The rigorous execution of these ACF practices facilitates early TB case detection and prompt treatment initiation, contributing to the observed improvements in treatment outcomes [ 39 ].

Moreover, our analysis revealed significant variability in successful TB treatment outcomes between different districts, with a variance of 0.063 attributed to diagnosing district. This underscores the importance of considering contextual factors and district-level variations in TB management strategies. While there may be some clustering of treatment outcomes within ACF groups, individual-level factors remain influential, as indicated by the ICC for ACF (0.0101). Despite this variability, the coefficients for all predictors remained consistent across districts, as observed from the bootstrap analysis. This suggests that the effects of predictors on treatment outcomes are robust and reliable across diverse settings, emphasizing the need for tailored interventions to address district-specific challenges while leveraging consistent predictors for TB treatment success.

ACF and TB treatment outcomes

Our study demonstrated that individuals diagnosed with TB through ACF had 1.4 times higher odds of successful treatment outcomes compared to those identified through passive case finding (PCF). In contrast to our findings, a study in Haridwar reported a 2.6 times higher risk of unsuccessful TB treatment outcomes associated with ACF compared to PCF, albeit on a small sample size [ 30 ]. Similarly, another study in the same district, albeit also with a small sample size, reported a much lower treatment success rate of 64% compared to the 94% reported in our study [ 32 ]. A study in South Delhi, again with a limited sample size, did not find a significant association between ACF and TB treatment outcomes, with treatment success rates of 75% for ACF and 82% for PCF [ 33 ]. Furthermore, a larger study across India, although not showing a significant association between ACF and treatment outcomes (ACF 90% vs. PCF 87% successful TB treatment outcomes), suggested a 17% lower chance of unfavorable TB treatment outcomes with ACF, underscoring its potential advantage [ 31 ]. Finally, a study among tribal populations in Madhya Pradesh with a substantial sample size found improvements in TB treatment outcomes due to ACF [ 19 ]. Considering the limitations of previous studies with small sample sizes and the trend of well-conducted studies favoring ACF in improving TB treatment outcomes, our study’s findings on a large sample size unquestionably underscore the value of ACF in enhancing TB treatment outcomes among pulmonary TB patients.

When comparing our study results with international evidence, we observed higher treatment success rates in the ACF group compared with the PCF group, while studies in Myanmar, Ethiopia, Nigeria, and South Africa, including a systematic review, reported similar treatment success rates in these groups [ 14 , 25 , 27 , 28 , 29 ]. Additionally, most existing studies have reported high initial default rates and treatment delays among patients diagnosed through community surveys [ 16 , 25 , 27 , 30 , 32 , 40 ], although one study noted a decrease in the initial default rate due to ACF [ 19 ]. However, our study did not specifically investigate this effect as it focused on TB patients already on treatment. Lastly, exploring the impact of community-based ACF initiatives on TB treatment outcomes in trial settings could provide valuable insights into the effectiveness of ACF in improving TB treatment outcomes [ 41 ].

The observed enhancement in treatment outcomes associated with ACF in our study can be attributed to several potential mechanisms. Firstly, ACF facilitates the early detection of TB cases within the community [ 13 , 21 ], enabling prompt initiation of treatment [ 12 ]. By actively screening individuals who may not present with typical TB symptoms but are still infectious, ACF minimizes delays in diagnosis and treatment initiation [ 19 , 42 , 43 ], crucial factors in preventing disease progression and transmission [ 6 , 8 , 25 , 39 , 44 ], ultimately reducing morbidity, mortality, and the overall burden of TB. Additionally, ACF allows for the identification of TB cases at an earlier stage of the disease, when treatment is more effective and complications are less likely to occur [ 21 , 25 , 42 , 44 , 45 ]. This early detection and treatment initiation may contribute to a higher proportion of cases achieving cure status, thereby improving treatment outcomes.

Furthermore, ACF interventions often involve comprehensive patient management and support services, including counseling, adherence support, and monitoring throughout the treatment process [ 33 ]. By engaging TB patients early in their care journey, ACF programs can address barriers to treatment adherence and facilitate patient-centered care, which are known determinants of treatment success [ 29 , 33 ]. Moreover, ACF activities may contribute to increased awareness and knowledge about TB within the community, leading to reduced stigma, improved health-seeking behavior, and earlier presentation to healthcare facilities among individuals with TB symptoms [ 19 , 24 , 45 , 46 ]. These findings emphasize the critical role of ACF in achieving better TB treatment outcomes, underscoring the need for continued support and implementation of ACF initiatives.

However, it is important to recognize the potential disadvantages of ACF in TB control programs. ACF programs can be resource-intensive, requiring significant financial and human resources for community outreach, screening, and follow-up [ 47 , 48 ]. Additionally, the higher costs associated with ACF interventions compared to traditional PCF approaches can strain already limited healthcare budgets, especially in resource-constrained settings [ 42 , 49 , 50 , 51 ]. To enhance the efficiency and effectiveness of ACF activities in India, two promising approaches can be considered: linking ACF activities with TB preventive treatment for household contacts [ 52 , 53 ] and integrating cost-efficient artificial intelligence (AI) tools into chest X-ray screening for TB [ 54 , 55 , 56 , 57 ]. These approaches offer novel methods of secondary prevention, targeting both latent TB and asymptomatic TB cases, and could help mitigate some of the resource challenges associated with ACF, particularly in vulnerable populations [ 58 ].

Secondary findings

Our analysis identified several significant predictors of favorable TB treatment outcomes. As individuals age, there might be an increased risk of unsuccessful TB treatment outcomes, including death and loss to follow-up, possibly due to challenges in treatment adherence in older populations [ 59 ]. Females demonstrated significantly higher treatment success rates compared to males, in contrast to other studies [ 60 , 61 , 62 , 63 ], possibly influenced by factors such as addiction prevalence and hormonal differences. Additionally, sputum negativity and HIV-negative status were associated with substantially higher treatment success rates, corroborating previous research findings [ 60 , 61 , 64 , 65 , 66 ]. Notably, our study contributes to a deeper understanding of these factors, overcoming limitations observed in prior studies. These findings underscore the critical role of targeted interventions and comprehensive care in improving TB treatment outcomes.

Qualitative findings

In our qualitative analysis, TB program functionaries emphasized the critical role of ACF in improving TB treatment outcomes. This aligns with the quantitative findings, which highlighted the significance of ACF in enhancing treatment success rates. Program functionaries recommend increasing field visits, deploying dedicated staff, and incentivizing healthcare workers to maximize the effectiveness of ACF. By focusing on ACF and its direct impact on TB treatment outcomes, our qualitative findings provide a comprehensive perspective on the effectiveness of ACF strategies. This emphasizes the need for continued efforts to enhance ACF practices to improve TB treatment outcomes in India.

Strengths and limitations

Our study presents significant strengths, including a substantial and representative sample size facilitating a thorough comparison of TB treatment outcomes between active and passive case finding methods. The incorporation of a qualitative component through in-depth interviews provides novel insights and complements the quantitative findings, offering valuable context to the dynamics of active and passive case finding. Adherence to established guidelines for reporting, including STROBE for quantitative findings and COREQ for qualitative findings [ 67 , 68 ], enhances the transparency and credibility of the study, bolstering its scientific validity. Moreover, the generalizability of our findings extends beyond the study region, informing TB management strategies across the broader Indian context. However, certain limitations exist, including the exclusion of drug-resistant cases and extrapulmonary TB, potentially limiting the comprehensiveness of the results. The brief duration of interviews may have restricted the depth of insights obtained from participants, and the lack of data on smoking status and occupation could introduce confounding factors. Additionally, the selection of study years based on data availability and the potential limitations in the representativeness of the qualitative sample pose challenges. To address these concerns, future studies could explore additional years to provide a more comprehensive understanding of the impact of ACF on TB treatment outcomes. Moreover, efforts should be made to enhance the depth and breadth of qualitative data collection, including a more comprehensive sampling strategy and further exploration of contextual factors to improve the validity and reliability of qualitative findings.

Conclusions

Our study sheds light on the potential of active case finding (ACF) to contribute to improved TB treatment outcomes in India. Through a mixed-methods approach, we found evidence suggesting an association between ACF and successful TB treatment outcomes, underscoring its importance in the context of TB control efforts. The insights gleaned from our quantitative analysis, supplemented by qualitative perspectives from TB program functionaries, provide valuable contributions to the understanding of how ACF positively impacts TB treatment outcomes. Notably, our findings suggest that expanding ACF initiatives to vulnerable populations and intensifying efforts such as ring surveys and preventive treatment could further improve the TB control measures. Future studies could explore the combined effectiveness of ACF with other targeted interventions to maximize impact and accelerate progress in TB control. In conclusion, our findings underscore the importance of ACF as a valuable tool in the fight against TB in India. By leveraging targeted strategies and collaborative efforts, we can significantly improve TB treatment outcomes and work towards alleviating the burden of this global health challenge.

Availability of data and materials

The data that support the findings of the quantitative component of the study are available from the Gujarat State TB Cell but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Gujarat State TB Cell. All data generated or analyzed during the qualitative in-depth interviews of the study are included in this published article [and its supplementary information files].

Abbreviations

Active Case Finding

Accredited Social Health Activist

COnsolidated criteria for REporting Qualitative research

Human Immunodeficiency Virus

Indian Council of Medical Research

Interquartile Range

Latent Tuberculosis Infection

National Tuberculosis Elimination Program

Passive Case Finding

State Tuberculosis Training and Demonstration Centre

Strengthening The Reporting of OBservational studies in Epidemiology

Tuberculosis

World Health Organization

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Acknowledgements

We would like to thank the experts who spared their valuable time for the in-depth interviews. We would also like to thank the Gujarat State TB cell and the Gujarat State TB Training and Demonstration Center for granting permission and the data for this study. We are grateful to the Gujarat State TB Operations Research Committee for funding the data collection of this research.

The data collection was funded with a monetary grant of INR 20,000 by State TB Operational Research Committee (Government of Gujarat) [no. TB/382022/OR/2022/1, 17-05-2022].

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Akshat P. Shah, Mohit N. Makwana & Mihir P. Rupani

Department of Respiratory Medicine, Government Medical College Bhavnagar (Maharaja Krishnakumarsinhji Bhavnagar University), Jail Road, Bhavnagar, Gujarat, 364001, India

Jigna D. Dave

Department of Community and Family Medicine, All India Institute of Medical Sciences (AIIMS), Khanderi, Parapipaliya, Rajkot, Gujarat, 360006, India

Mohit N. Makwana

Clinical Epidemiology (Division of Health Sciences), ICMR – National Institute of Occupational Health (NIOH), Indian Council of Medical Research (ICMR), Meghaninagar, Near Raksha Shakti University, Ahmedabad, Gujarat, 380016, India

Mihir P. Rupani

Division of Agricultural Statistics, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir, Jammu & Kashmir, Srinagar, 190025, India

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All authors contributed to the conception, design, and intellectual content definition, conducted literature searches, analyzed data, edited the manuscript, reviewed the manuscript, and approved its final version. A.S. and M.M. assisted with data collection, transcript preparation, and analysis under the guidance of J.D. and M.R. Additionally, I.S. conducted advanced statistical analysis for the study.

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Correspondence to Mihir P. Rupani .

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This study received approval from the Institutional Scientific Review Committee and Institutional Ethics Committee of Government Medical College, Bhavnagar (Bhavnagar, Gujarat) under approval number 1129/2021 dated 29-10-2021. Subsequently, approval was also obtained from the Scientific Advisory Committee and the Institutional Human Ethics Committee of ICMR-National Institute of Occupational Health (Ahmedabad, Gujarat) under approval number EC/2021-22/3.1, dated 10-03-2022. Permission to access the quantitative data was granted by the State TB Operational Research Committee (Government of Gujarat). Written informed consent was obtained from all participants for their involvement in the study and for the audio recording of the in-depth interviews. The study adhered to the principles outlined in the Helsinki Declaration. Throughout the study, the research team maintained complete access to any data accessed and/or gathered. Patient privacy was upheld by utilizing identifiers provided by the national TB program.

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Shah, A.P., Dave, J.D., Makwana, M.N. et al. A mixed-methods study on impact of active case finding on pulmonary tuberculosis treatment outcomes in India. Arch Public Health 82 , 92 (2024). https://doi.org/10.1186/s13690-024-01326-0

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Active case-finding for tuberculosis in India

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1 ICMR-National Institute for Research in Tuberculosis, No. 1, Mayor Sathiyamoorthy Road, Chetpet, Chennai 600031, Tamil Nadu, India.
PMID: 31939405
DOI: 10.4103/0970-258X.275349

Early identification of presumptive tuberculosis (TB) cases through active case-finding (ACF) would be an important complementary strategy to meet the national urgency in accelerating case detection to achieve the goals of 'End TB' strategy. ACF activities have yielded additional cases in different vulnerable groups in India. The yield of cases depends on the screening tool available, the characteristics of the high-risk population being screened, and most importantly, the linkage between effective diagnostic and treatment facilities. The ACF strategy could be both economically and epidemiologically relevant if it could bring down the level of transmission. This needs long-term research focusing on outcomes such as cases averted and reduction in the prevalence of the disease. Available evidence suggests that ACF is likely to be feasible in Indian settings but needs to be scaled up rapidly to create a good impact.

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Research Article

Journey of the tuberculosis patients in India from onset of symptom till one-year post-treatment

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Research Department, George Institute for Global Health, New Delhi, India, Department of Medicine, University of New South Wales, Sydney, New South Wales, Australia, Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, Karnataka, India

Roles Data curation, Formal analysis, Project administration, Supervision, Validation, Writing – review & editing

Affiliation Research Department, George Institute for Global Health, New Delhi, India

Roles Formal analysis, Validation, Writing – review & editing

Affiliation Department of Medicine, University of New South Wales, Sydney, New South Wales, Australia

Roles Supervision, Writing – review & editing

Affiliation Department of Respiratory Medicine, Indira Gandhi Government Medical College, Nagpur, Maharashtra, India

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

Affiliation Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom

Susmita Chatterjee,
Palash Das,
Aaron Shikhule,
Radha Munje,
Anna Vassall

Published: February 10, 2023
https://doi.org/10.1371/journal.pgph.0001564
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Historically, economic studies on tuberculosis estimated out-of-pocket expenses related to tuberculosis treatment and catastrophic cost, however, no study has yet been conducted to understand the post-treatment economic conditions of the tuberculosis patients in India. In this paper, we add to this body of knowledge by examining the experiences of the tuberculosis patients from the onset of symptoms till one-year post-treatment. 829 adult drug-susceptible tuberculosis patients from general population and from two high risk groups: urban slum dwellers and tea garden families were interviewed during February 2019 to February 2021 at their intensive and continuation phases of treatment and about one-year post-treatment using adapted World Health Organization tuberculosis patient cost survey instrument. Interviews covered socio-economic conditions, employment status, income, out-of-pocket expenses and time spent for outpatient visits, hospitalization, drug-pick up, medical follow-ups, additional food, coping strategies, treatment outcome, identification of post-treatment symptoms and treatment for post-treatment sequalae/recurrent cases. All costs were calculated in 2020 Indian rupee (INR) and converted into US dollar (US$) (1 US$ = INR 74.132). Total cost of tuberculosis treatment since the onset of symptom till one-year post-treatment ranged from US$359 (Standard Deviation (SD) 744) to US$413 (SD 500) of which 32%-44% of costs incurred in pre-treatment phase and 7% in post-treatment phase. 29%-43% study participants reported having outstanding loan with average amount ranged from US$103 to US$261 during the post-treatment period. 20%-28% participants borrowed during post-treatment period and 7%-16% sold/mortgaged personal belongings. Therefore, economic impact of tuberculosis persists way beyond treatment completion. Major reasons of continued hardship were costs associated with initial tuberculosis treatment, unemployment, and reduced income. Therefore, policy priorities to reduce treatment cost and to protect patients from the economic consequences of the disease by ensuring job security, additional food support, better management of direct benefit transfer and improving coverage through medical insurances need consideration.

Citation: Chatterjee S, Das P, Shikhule A, Munje R, Vassall A (2023) Journey of the tuberculosis patients in India from onset of symptom till one-year post-treatment. PLOS Glob Public Health 3(2): e0001564. https://doi.org/10.1371/journal.pgph.0001564

Editor: Alice Zwerling, University of Ottawa, CANADA

Received: August 13, 2022; Accepted: January 14, 2023; Published: February 10, 2023

Copyright: © 2023 Chatterjee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data underlying the findings in this article is openly available and submitted with the manuscript as supporting file .

Funding: This work was supported by the DBT/Wellcome Trust India Alliance Clinical and Public Health Intermediate Fellowship [grant number IA/CPHI/17/1/503339] awarded to SC. SC and PD received salary support from the funder. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Tuberculosis (TB) is not only a global public health concern with estimated 10 million people suffered from the disease and 1.4 million people died in 2019 [ 1 ], but it also has societal consequences. TB is a contagious disease that requires long treatment and care and strongly associated with social stigma, poverty, illiteracy, unemployment, and catastrophic cost [ 2 – 7 ]. While much is known about the costs of TB treatment to households, in recent years there has been increasing emphasis on the long-term impact of TB treatment. Menzies et al (2021) estimated the health losses caused by global incidence of TB in 2019 (including the loss in the post-treatment period) and reported 122 million disability adjusted life years (DALYs) attributed to TB, of which, 58 million DALYs attributed to post-treatment sequalae [ 8 ]. Pulmonary TB patients may develop respiratory infections even after cure which may lead to greater morbidity and mortality. Further, TB survivors have a higher risk of disease recurrence. Therefore, the ongoing physical impact of the disease may have a long-term economic impact. A recent study conducted in Malawi examined whether the economic impact of the disease was fully recovered after one-year post-treatment. They concluded that many TB patients experienced limited recovery in income and employment with ongoing dissaving and schooling interruptions in the post- treatment period [ 9 ].

India has the highest TB burden in the world with an estimated incidence of 2.64 million in 2019 [ 10 ]. The government of India provides free diagnosis and treatment to all registered TB patients; however, studies reported high out-of-pocket expenses and catastrophic cost related to TB [ 11 – 15 ]. A recent literature review found that the mean total cost (direct and indirect) to the patients and households for drug-susceptible (DS) TB treatment in public health facilities was US$235 (Standard Deviation [SD] 210) at 2018 prices [ 16 ]. Further, the study showed that 7% to 32% of DS-TB patients in India faced catastrophic cost because of TB (defined as total cost ≥ 20% of total annual household income) [ 16 ]. While studies estimated the patient and household costs related to TB treatment in India, however, the patients for those studies were sampled from only one state/district covering limited geographical area [ 11 – 15 ]. Further, no study has yet been conducted to understand the post treatment economic conditions of the TB patients in India. Understanding the socioeconomic impact of TB patients during treatment and post-treatment will be crucial to develop strategies to reduce the burden and to improve the overall well-being of the TB survivors. In this paper, we add to this body of knowledge by examining the experiences of the TB patients in India for the full course of the disease and beyond: from the onset of symptoms till one year post treatment.

The study design follows a cohort of total 1536 DS-TB patients among three groups: general population and two high-risk groups as identified in the National Strategic Plan for TB: 2017–2025 [ 17 ]: urban slum dwellers and patients from tea garden areas. The high-risk groups were chosen as the treatment seeking behaviour, costs of TB treatment and coping strategies among participants from high-risk groups could be different from general population and different protective measures may be required for them in the process of TB elimination in the country.

As per World Bank 2018 estimates, 35% of India’s urban population live in slum areas [ 18 ]. Apart from having poor housing condition, sanitation, access to safe drinking water, the urban slum dwellers experience illegality and social exclusion, poorly regulated and ineffective health services [ 19 ].

India’s tea industry is one of the largest private employers, and the people living in tea estates entirely rely on estates for employment and other services such as housing, water, health, education [ 20 ]. Because of very poor living condition and extremely low wage rate, the families living in tea garden areas are at high-risk of any disease including TB. Their health service utilization pattern, treatment expenses, employment status in pre-, during and post TB period are unknown. Similar for urban slum dwellers. Hence, the main study aims to report the complete journey of the TB patients from general population as well as from tea garden and urban slum areas.

Sampling strategy

For the costing study, national representativeness can be achieved by considering a limited number of states selected using an appropriately stratified sampling design. The World Health Organization Study on global AGEing and adult health (SAGE) sampling design was followed in this context [ 21 ]. As a first step, 29 states of India were stratified into six levels of development and six geographic locations. A composite development index was constructed using the following indicators at the state level: Infant mortality rate; female literacy rate; full immunization coverage rate; and per capita income. Principal component analysis technique was used to construct the composite index. Quantiles were then used to categorize the states into six levels of development ( S1 Table ). Based on the availability of study budget, Assam, Maharashtra, Tamil Nadu, and West Bengal were selected for this study as these states not only represent different levels of development but also cover different regions of the country. Apart from that, Assam, Tamil Nadu, and West Bengal have substantial land area for tea gardens, and Maharashtra, Tamil Nadu and West Bengal are among the top five states in terms of urban slum population in the country. TB patients from general population were drawn from all four states.

In the next stage of sampling, 3–5 districts from each state were selected purposively based on the dominance of the high-risk groups. From the sampled study districts, TB units (TUs—one TU covers 200,000 population (range 150,000–250,000) for rural and urban areas, 100,000 (range 75,000–150,000) in hilly, tribal, and difficult areas) were then identified which cater to the study high-risk groups. As all TUs cater to general population, there was no specific identification of TUs for covering patients from general population.

Patient recruitment

In the next step, from all identified TUs, adult (18 years and above) TB patients who were at their intensive phase of treatment (DS-TB requires a minimum of six months of treatment, of which the first two months are called the intensive phase and the following four months the continuation phase) during the visit of the study team and gave written informed consent to participate in the study were interviewed.

Sample size for each group for the main study

Present study participants

In this paper, we present the experience of 829 TB patients of whom 435 were from tea garden areas, 260 from general population and 134 from urban slum dwellers scattered across 9 districts, 52 TB units and 182 tea gardens as one-year post-treatment follow-up completed for these patients. This study participants were interviewed between February 2019 to February 2021 by trained researchers under close supervision using the adapted TB patient cost survey tool developed by the World Health Organization [ 23 ]. They were interviewed at their intensive phase (IP) (0–2 months) of treatment, end of continuation phase (CP) of treatment (5–6 months) and about one-year post-treatment.

IP interviews covered their socio-economic conditions and ownership of assets, employment status and patient and household income before onset of TB symptoms and at the time of interview, consumption expenditure of the household before TB, and out-of-pocket expenses (including consultation fees, medicines, laboratory / radiology tests, travel expenses, food and any other expenses) and time spent by the patients and the accompanied persons for outpatient visits, hospitalizations (out-of-pocket expenses included bed charges, consultation fees, medicines, tests, procedures such as biopsy / surgeries, travel expenses, additional food, accommodation and any other expenses) starting from onset of symptoms. Time spent by the patients and accompanied persons for TB drug-pick up / directly observed treatment (DOT), medical follow-ups were collected along with out-of-pocket expenses for travel, food during drug pick-up/DOT, medical follow-ups, additional food/nutritional supplements, and coping strategies (dissaving, borrowing, sold assets) during IP interviews. CP interviews covered time spent and out-of-pocket expenses related to TB treatment, employment and income status and coping strategies since the IP interviews. Post-treatment interviews covered treatment outcome, identification of post-treatment symptoms, expenses and time spent on outpatient visits and hospitalization related to post treatment sequalae, treatment cost of relapse cases, income and employment status, and socioeconomic consequences such as outstanding loan (i.e., the loan the study participants took for TB diagnosis/treatment during pre- and treatment period but could not repay at the time of post-treatment interview), borrowing/sale/mortgage of belongings and others (if any).

Impact of COVID-19 on the present study

In India, to curb the spread of the coronavirus infection, there was a nationwide lockdown from March 25, 2020, till June 8, 2020. The present study participants were severely impacted by the restrictive measures and there was huge loss of employment and income among the study participants [ 24 ]. To understand the impact of TB only, participants were asked to report employment status, individual and household incomes for the month of February 2020 (i.e., the month before the nationwide lockdown started). Further, during the interviews, they were reminded to report about coping strategies used only for TB disease, not for managing the crisis during COVID-19. Reported outstanding loan amounts in the post-treatment period were cross checked with the amounts borrowed during treatment period for consistency.

Cost calculation methods

Pre-treatment cost was defined as the costs (both direct and indirect costs, i.e., actual money spent and time cost) incurred from the onset of TB symptoms till the date of treatment initiation. Total treatment cost was the sum of direct and indirect cost incurred during IP and CP of treatment. For patients whose treatment were extended, costs were calculated till the completion of treatment. For the defaulters, TB drug pick up costs were calculated till the date of last drug pick up. Time costs of patient and accompanied persons were calculated using the ‘human capital approach’ [ 25 ] where hours spent for each activity related to TB treatment was multiplied by the minimum hourly wage rate of the respective states [ 26 ]. Catastrophic cost was calculated as proportion of total TB treatment cost of pre-TB annual household income. Total TB treatment cost, exceeding a given threshold (20%) of the household’s annual pre-TB income, was considered as catastrophe [ 23 ].

Post TB infections present similar features as pulmonary TB such as weight loss, chronic productive cough, coughing up blood, difficulty in breathing and fatigue [ 27 ]. Study participants were asked if they experienced any such symptoms during post-treatment period and whether availed health care for managing those symptoms. Costs of outpatient visits, hospitalization and treatment cost for the relapse cases were calculated using same methodology discussed earlier. All costs were calculated in 2020 Indian rupees (INR) and converted into US dollars (US$) using average exchange rate of 2020 (1 US$ = INR 74.132).

To determine the relationships of post-treatment financial hardship with several predictor variables, we ran two multiple linear regressions for each group. After testing for several models, we selected linear regression model as the best fit. In one regression, outstanding loan amount in the post-treatment period was the dependent variable and direct cost of initial TB treatment, post-treatment household income, treatment cost in the post-treatment period, age, gender, and wealth index were the independent variables. Wealth index is a composite measure of a household’s cumulative living standard. During the IP interviews, data were collected on household type, materials used for house construction, drinking water and sanitation facilities, usage of cooking fuel, and ownership of assets such as television, refrigerator, mobile phone, computer, internet connection, motorcycle, car, jeep etc. Variables were chosen from national demographic and health surveys in India. Principal component analysis was used to create the wealth index for each study participant.

In another regression model, amount of borrowing and sale/mortgage of belongings (i.e., the amount received combining all coping strategies) in the post-treatment period was the dependent variable and post-treatment household income, treatment cost in the post-treatment period, outstanding loan amount in the post-treatment period, age, gender, and wealth index were the explanatory variables. The choice of the independent variables was motivated by the study in Malawi [ 9 ] and from the authors’ understanding of the data. Descriptive statistics of the predictor variables are presented in S2 Table . Preliminary analyses were performed to ensure there was no violation of the assumptions of multicollinearity. The fitted line plots indicating the linear relationship between dependent and independent variables are given in S1 – S6 Figs.

Ethics approval and consent to participate

The study was approved by the Institutional Ethics Committee of the George Institute for Global Health (014/2018). Written informed consent was obtained from each study participant before starting the interview.

Characteristics of the study participants

A total of 829 DS-TB patients were interviewed in IP, however, one year post treatment, 705 participants were interviewed (about 15% loss to follow-up). The reasons of loss to follow up are given in Table 1 . Average recall period from onset of symptoms to treatment initiation ranged from 52 days (SD 57) to 54 days (SD 55) while the recall period from treatment initiation to IP interview ranged from 29 days (SD 17) to 36 days (SD 13). Average recall period for CP interviews was between 120 days (SD 15) and 162 days (SD 35) and for post-treatment interviews, it ranged from 272 days (SD 75) to 314 days (SD 91).

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https://doi.org/10.1371/journal.pgph.0001564.t001

Characteristics of the study participants interviewed in IP and post treatment were similar ( Table 2 ). Most of the participants were male and were in younger age group, 18–34 years. About 40% participants in tea garden areas never attended school, one third in general population attended primary school and 47% in slum areas completed higher secondary education. Average household monthly income before the study participant had TB was between $100-$199 for 38% participants in general population and 45% among slum dwellers while it was less than $100 for 53% of the participants from tea garden areas ( Table 2 ). Most of the study participants had pulmonary bacteriologically confirmed TB while 25% to 35% had extrapulmonary TB with cervical lymph node and plural effusion were the most common forms. Kruskal Wallis test after Bonferroni adjustment showed all variables except type of TB in intensive phase were significantly different among three groups.

https://doi.org/10.1371/journal.pgph.0001564.t002

Employment and income status of the study participants

Changes in employment and income status of the study participants in different phases of treatment and post-treatment period are presented in Figs 1 and 2 respectively. Results are presented for 705 participants who were followed up till the post-treatment period.

https://doi.org/10.1371/journal.pgph.0001564.g001

https://doi.org/10.1371/journal.pgph.0001564.g002

Before TB, approximately 6% (urban slum dwellers) to 10% (tea garden areas) of the study participants were unemployed, however, in IP, the percentage of unemployment ranged from 32% among slum dwellers to 64% among participants in tea garden areas implying that TB had serious impact on participants’ employment ( Fig 1 ). In CP, the situation improved, and unemployment rate ranged from 27%-47%. About one-year post-treatment, however, all study participants could not return to their pre-TB condition. Unemployment rate in post-TB period ranged from 21%-31% as compared to 6%-10% in the pre-TB condition.

Before TB, no households of study participants in general population had zero income ( Fig 2 ). However, in IP, about 13% households had zero income probably indicating that those patients were the sole earning members of the family. In post-treatment period, 3% households had zero income. Proportion of households in higher income groups gradually moved towards lower income group during IP indicating that patients were unable to work fully. In the post-treatment period, proportion improved but was lower as compared to pre-TB proportion. Similar trends were observed for other two groups ( Fig 2 ).

Heath seeking behaviour of the study participants at the pre-treatment phase

Equal proportion of participants in general population first visited private facilities (33%) and government facilities (33%) after the onset of suggestive TB symptoms followed by 23% in drug stores and 5% to unqualified practitioners. The most preferred facility for seeking treatment for the participants in tea garden areas was the tea garden hospitals or dispensaries (42%) followed by government facilities (28%), drug stores (13%) and private facilities (12%). For participants in urban slum areas, first preference was drug stores (26%) followed by private facilities (25%). 19% patients first visited the unqualified practitioners and a similar proportion visited government facilities after the onset of TB symptoms. Hospitalization rate ranged from 16% (participants in slum areas) to 29% (tea garden areas). 52% of those hospitalized in tea garden areas were admitted in tea garden hospitals followed by 35% in government hospitals. For other two groups, 64%-76% hospitalizations were in public. 20% study participants in general population and 34% patients in tea garden areas reported having health insurance while only 2% participants among urban slum dwellers had health insurance. Only couple of hospitalized patients reported that they got benefit from their health insurances.

Average time from the onset of TB symptoms till the start of TB treatment was 8 weeks (SD 8) for participants in general population and slum dwellers (with a range of 1 week to 70 weeks) and for participants in tea garden areas, 7 weeks (SD 8) (ranging from 1 week to 60 weeks). During that time, study participants among slum dwellers made an average of 12 (SD 8) visits at different facilities (ranged from 1 to 52) while participants among general population made 9 (SD 5) visits (range: 1 to 31) and participants from tea garden areas 8 (SD 4) visits (range: 1 to 25).

Post-treatment sequalae and treatment seeking behaviour

After about one-year post-treatment, participants in all categories reported multiple symptoms similar as pulmonary TB. 29% participants in general population (63/221) reported lack of energy, 25% suffering from shortness of breath, 14% was coughing during the interview and 14% having chest pain. 16% participants visited different health facilities for treatment of these symptoms and 46% among them went to the public facilities first while 29% went to the private facilities.

Symptoms were similar for participants in tea garden areas and urban slum dwellers. 30% participants in tea garden areas and 34% in slum areas had at least one symptom. 18% participants in tea garden areas sought treatment for these symptoms and majority (43%) went to the tea garden hospitals first for treatment and 31% went to public health facilities. Preference for health facility changed for urban slum dwellers when compared with pre-treatment phase, 53% of those who made visits during post-treatment period went to government health facilities first instead of visiting drug stores or private facilities. Hospitalization rate was much lower in post-treatment period as compared to pre-treatment, only two participants each among general population and urban slum dwellers were hospitalized while three were hospitalized among tea garden area participants.

Costs of TB treatment

Costs incurred by study participants during TB treatment and for post-treatment sequalae / relapse cases are presented in Table 3 . Total cost of TB treatment since the onset of TB symptom till one-year post-treatment for the general population was US$397 (SD 490) of which 44% was incurred in pre-treatment phase, 17% in IP, 33% in CP and 6% in post-treatment phase. In all phases, direct cost was the major contributor ranging from 63% of total costs of pre- and post-treatment phases to 84% of IP total cost. The reasons of high direct costs during IP and CP were purchase of additional nutritional food and supplements while in pre- and post-treatment phases, major direct cost was for outpatient visits.

https://doi.org/10.1371/journal.pgph.0001564.t003

For participants in tea garden areas, total treatment cost (starting from TB symptom till one-year post-treatment) was US$359 (SD 744) with 44% cost incurred in CP, 40% in pre-treatment, 11% in IP and 6% in post-treatment phase. Indirect cost dominated in all phases except in IP and it ranged from 63% to 84% of total costs of those phases respectively. Time cost for hospitalization was the reason of high indirect cost.

TB treatment cost for participants in urban slum areas was US$413 (SD 500). 40% of total cost was incurred in CP followed by 32% in pre-treatment phase, 21% in IP and 7% in post-treatment period. Direct cost was the major cost in all phases except in post-treatment ranging from 52% of total cost incurred in pre-treatment phase to 74% in IP. In pre-treatment phase, costs incurred for outpatient visits were the major direct cost, while in IP and CP, costs incurred for buying additional food were the major contributors. Indirect cost contributed 89% of total post-treatment phase cost and time cost for hospitalization was the major cost contributor. Kruskal Wallis test after Bonferroni adjustment showed significant difference in treatment cost among three groups (p<0.001).

Catastrophic cost by wealth quintile

35% patients from general population, 38% among urban slum dwellers and 40% among tea garden areas faced catastrophic cost because of TB. The proportions remain the same using pre-TB household expenditure as denominator of catastrophic cost. Among patients who faced catastrophe in general population, the cost burden was the highest for the poorest quintile (48%) ( Fig 3 ), however, for the other two groups, cost burden was the highest for the richest quintile.

https://doi.org/10.1371/journal.pgph.0001564.g003

Treatment outcome

13 out of 260 study participants in general population died during the follow up period, majority deaths occurred during treatment phase. Similar proportion of participants in slum areas died, however, majority death occurred after completing their treatment. Death rate was higher for participants in tea garden areas (about 7%) and majority death occurred during IP. (9/260) participants in general population and (7/435) in tea garden areas were defaulters, there were no defaulters among participants in urban slum areas. About 4% participants both in general population (8/221) and tea garden areas (16/379) had TB again after completing their treatment whereas only two participants had relapse cases in slum areas.

Coping strategies during treatment and post-treatment period

High rate of unemployment during TB treatment along with expenses incurred for treatment forced study participants to borrow, sell/mortgage of assets and withdraw money from financial institutions. Details of coping strategies are presented in Table 4 . Proportion of borrowing and sale during IP was the highest among general population while a significant proportion of participants in tea garden areas (54%) withdrawn from savings during IP. The borrowing and sale were the highest for them in CP. Types of items sold/mortgaged differed among the groups, while the participants from general population sold/mortgaged gold and jewellery (42%) followed by livestock (40%), land (17%) during treatment period, participants from tea garden areas mostly sold/mortgaged livestock (45%) followed by land (21%), farm produce (13%) and household items (11%). For the participants in slum areas, the most common item available for sell/mortgage was gold or jewellery (87%) followed by transport/vehicle, household items and business property (4% each).

https://doi.org/10.1371/journal.pgph.0001564.t004

During post-treatment period, 29% to 43% study participants reported having outstanding loan with average amount ranged from US$103 to US$261 ( Table 4 ) and the proportion having outstanding loan was significantly different among three groups (p<0.001). 20%-28% participants borrowed during post-treatment period and 7%-16% sold/mortgaged household items. Like treatment period, gold/jewellery was the most common item for sale/mortgage for the general population (38%) followed by livestock (34%) and land (17%). Items for sale/mortgage for participants from tea garden areas were also similar as during treatment period, most common item being livestock (65%), followed by farm produce (17%) and land (13%). For participants from urban slum areas, mostly used item for sell/mortgage was gold/jewellery (57%) followed by household items (29%) and transport/vehicle (14%).

Coping strategies by wealth quintile

Even though catastrophic cost was the highest among the richest quintiles for tea garden families and urban slum dwellers, highest proportion of participants in poorest quintiles in both groups used various coping strategies both during treatment and post-treatment ( Table 5 ). Proportion of participants with outstanding loan in the post-treatment period was also highest among the poorest quintiles in each group.

https://doi.org/10.1371/journal.pgph.0001564.t005

Other economic consequences

Apart from borrowing, selling, and withdrawing money from banks / other financial institutions, patients also had other economic consequences such as cut down consumption for other family members, run up account in grocery shops, unable to pay electricity / mobile / gas / cable bills, could not contribute to family / social events not only during treatment period but also during post-treatment period ( Table 6 ).

https://doi.org/10.1371/journal.pgph.0001564.t006

Predictors of post-treatment financial hardship

We present the regression coefficients with all explanatory variables for each group in Table 7 . We found that total direct cost of TB treatment (including direct cost incurred in pre-treatment phase) was significantly associated with outstanding loan amount in the post-treatment period for all groups. On the other hand, outstanding loan amount was significantly associated with borrowing / sale / mortgage in the post-treatment period implying that those who had outstanding loan, had to use various coping strategies in the post-treatment period. Treatment cost for post-treatment sequalae and relapse cases also forced the study participants in tea garden areas for distress financing in the post-treatment period. There were no association of financial hardship with socio-economic or demographic characteristics (except age which was marginally associated with dissaving for participants among general population and tea garden areas) implying that all categories of patients had distress financing in the post-treatment period. Dropping the socio-economic and demographic variables from the regression models from all groups did not affect the overall goodness-of-fit of the models.

https://doi.org/10.1371/journal.pgph.0001564.t007

The present study reports the journey of 705 TB patients in India from the onset of TB symptoms till one-year post-treatment. 829 patients were interviewed in IP however because of loss to follow up, post-treatment follow up interviews were completed with 705 TB patients. To the best of the authors’ knowledge, this is the first study in India that examined the economic condition of the TB patients beyond treatment completion. Another unique feature of the study is that the study covered wide range of patients: general population from both urban and rural areas as well as high-risk groups such as patients in tea garden areas and urban slum areas sampled from 52 TB Units and 182 tea gardens across 9 districts.

The study found that financial hardship that started from pre-treatment phase continued in the post-treatment period. Unemployment rate among the patients were higher in post-treatment phase as compared to pre-treatment phase indicating that they were unable to return to the pre-TB condition even after one-year post-treatment. Patients from higher income groups gradually moved to lower income groups during IP, situation improved during CP but could not completely revive during post-treatment. Further, patients used several coping strategies (borrowing/selling belongings) and faced other economic consequences even during post-treatment period. Therefore, not only the physical morbidity continues after treatment completion, economic impact of TB also persists way beyond treatment completion.

The present study findings corroborate with another study conducted in Malawi which reported that substantial financial hardship experienced during TB treatment extended to 12 months post-treatment completion [ 9 ]. The study found that although the proportion of participants working in the post-treatment period increased but it did not reach the baseline and persistent dissaving was widely observed. The study also reported ongoing respiratory morbidity after treatment completion like present study findings. 30%-34% participants among all groups in the present study reported having at least one symptom like pulmonary TB. It is therefore obvious that there will be additional treatment cost even during post-treatment period as observed in the present study.

The Malawi study noted that the reasons of lower recovery after treatment completion were ongoing financial insecurity from initial TB disease, reduced social capital, TB related stigma and ongoing respiratory morbidity [ 9 ]. The present study also found statistically significant association between financial hardship in the post-treatment period and higher direct cost of initial TB treatment and treatment cost for post-treatment sequalae. This clearly emphasized the need of reducing the treatment cost of TB in the country. Further, there was no significant association between post-treatment financial distress and socio-economic and demographic characteristics implying that financial insecurity continued for all categories of patients.

Costs of initial TB treatment reported in this study (ranging from US$341 –US$386) were substantially higher than the costs estimated in a recent literature review (US$235 at 2018 prices) [ 16 ]. The reason of high cost could be because the present study covered patients from different groups and scattered across many TB Units while most of the previous studies focused only in one district covering similar population group and locality. Indirect cost was the major contributor of total cost for patients in tea garden areas because of continuation of directly observed treatment (DOT) in most tea gardens and high hospitalization rate among the patients. On the other hand, direct cost was the major contributor for other two groups and buying nutritional food was the major expense for them during treatment period, a finding like other studies [ 16 , 28 , 29 ]. The Nikshay Poshan Yojana [ 30 ] introduced by the government of India in 2018 to provide nutritional support to the TB patients will be helpful in this regard if all TB patients receive the benefit on time. However, only 26%-39% study participants reported receiving the benefit during CP interviews while 9%-13% mentioned that they did not check or unaware about the receipt of the benefit in their bank accounts. The low percentage of receipt of benefit could be because of implementation challenges at its early phase, however, a better implementation in future may be helpful in reducing the costs on nutritional supplements during treatment phase. Further, patients in remote areas (especially patients in tea garden areas) found it difficult to visit banks for withdrawing the benefits, hence, any alternative method to reach the patients at the remotest corners of the country needs consideration.

Proportion of households faced catastrophic cost in the present study (35%-40%) was also significantly higher than reported in the recent literature review (7%-32%) using the same method of catastrophic cost calculation. The reason could be the same as mentioned earlier that the present study covered a wide range of TB patients as compared other studies. The cost burden for urban slum dwellers and tea garden areas was highest among the richest while one recent study using national survey data found that the burden of catastrophe for hospitalization was higher among the poor quintiles [ 31 ]. Even though the cost burden was higher among the richest, the burden of dissaving was the highest among the poorest quintile for all group of patients both during treatment and post-treatment period. This implies that even for a lower treatment cost, the poorest quintile had to use various coping methods to cover their treatment costs.

The study has few limitations. First, this study is a part of an ongoing study where we aim to interview the representative sample of 1536 DS-TB patients from three groups. As the present study covered 829 participants for whom one-year post-treatment follow up interviews were completed, the estimates are not as precise as expected. Hence, results should be interpreted with caution. However, because of clear dearth of data on post-treatment experience of TB patients in India, we decided to present an interim analysis of the available data. Second, during the follow-up interviews of the study participants, COVID-19 nationwide lockdown was ongoing and hence, it had impact on the study participants’ income and employment [ 24 ]. Keeping this in mind, we added few questions to separate out impact of COVID-19 from impact of TB. For example, to understand the employment status and income in the CP, participants were asked to report employment status and income just before lockdown started to understand only the impact on TB [ 24 ]. Finally, participants were asked to report treatment costs, health seeking behaviour, income retrospectively which were subject to some recall bias, however, biases were minimized by verifying medical records wherever available.

The study findings have implications on TB programme and policies. Major reason of continued financial hardship during the post-treatment period was high cost associated with TB treatment, treatment cost associated with post-treatment sequalae, unemployment, and reduced income. To reduce costs associated with TB treatment, post-treatment sequalae and related economic consequences, the delay from symptom to treatment initiation needs to be reduced as costs incurred in pre-treatment phase contributed a significant proportion of total TB treatment cost. Awareness generation around symptoms of TB and facilities available for free diagnosis and treatment will play an important role in this context. During COVID-19 pandemic, massive awareness campaigns were conducted in the country–similar types of initiatives may be planned along with several other ongoing activities such as active case findings, private sector engagements to achieve the target of eliminating this centuries old disease.

TB care should be designed in such a way so that it does not disrupt the livelihood of the patients and therefore, job security for the TB patients should be considered. A policy priority must continue to protect TB patients from the economic consequences of the disease by introducing paid sick leave, additional food support, better management of direct benefit transfer and improving coverage through medical insurances.

The high rate of catastrophic cost for all groups of patients clearly indicates that India has a long way to go to achieve the zero catastrophic cost target as envisioned in the END TB Strategy. Further, burden of dissaving, a potential proxy of catastrophe, was the highest among the poorest quintile which highlighted that the disease had devastating effect on the financial security of these households. This further emphasized the need of introduction of the above-mentioned risk protection measures for the TB patients in India.

Supporting information

S1 table. states stratified based on levels of development and regions..

https://doi.org/10.1371/journal.pgph.0001564.s001

S2 Table. Descriptive statistics of explanatory variables in regression analysis.

https://doi.org/10.1371/journal.pgph.0001564.s002

S1 Fig. Fitted line plots with amount of outstanding loan as dependent variable (general population, N = 220).

https://doi.org/10.1371/journal.pgph.0001564.s003

S2 Fig. Fitted line plots with amount of borrowing / selling as dependent variable (general population, N = 220).

https://doi.org/10.1371/journal.pgph.0001564.s004

S3 Fig. Fitted line plots with amount of outstanding loan as dependent variable (tea garden families, N = 379).

https://doi.org/10.1371/journal.pgph.0001564.s005

S4 Fig. Fitted line plots with amount of borrowing / selling as dependent variable (tea garden families, N = 379).

https://doi.org/10.1371/journal.pgph.0001564.s006

S5 Fig. Fitted line plots with amount of outstanding loan as dependent variable (urban slum dwellers, N = 104).

https://doi.org/10.1371/journal.pgph.0001564.s007

S6 Fig. Fitted line plots with amount of borrowing / selling as dependent variable (urban slum dwellers, N = 105).

https://doi.org/10.1371/journal.pgph.0001564.s008

S1 Data. Complete dataset.

https://doi.org/10.1371/journal.pgph.0001564.s009

Acknowledgments

We thank the State and District TB Officers and Senior Treatment Supervisors of the study states and districts for their support and co-operation during data collection. We extend our deepest thanks to the data collection team for their sincere efforts. Finally, we are grateful to all TB patients who participated in this study for their time with us despite being sick.

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NIHR Leicester Biomedical Research Centre

Dipesh Patel’s journey from TB patient to research advocate

Tuberculosis (TB) remains one of the most stigmatized diseases globally, often associated with misconceptions and fears that can lead to isolation and shame for those affected. Despite advances in medical treatment, the social stigma surrounding TB continues to be a significant barrier to diagnosis, treatment, and support for patients.

According to a World Health Organization (WHO) report , TB is the second leading infectious killer worldwide, after COVID-19, surpassing even HIV and AIDS. In 2022, an estimated 10.6 million people, including 5.8 million men, 3.5 million women, and 1.3 million children, fell ill with TB globally. Despite its prevalence, TB is still seen as a disease associated with shame and backwardness, effecting people physically, mentally, emotionally, and financially.

Among the struggling TB patients was Dipesh Patel, a young 27 year old man of Gujarati Indian descent from Leicester, diagnosed in July 2015.

At the time, he was 18 years old and in his final year of college. His diagnosis came as a shock, not only because TB seemed like a disease of the past but also because it came with the added burden of stigma.

Physically, the disease left him weak and frail, resulting in significant weight loss. He was admitted to Leicester Royal Infirmary, where his treatment lasted for nine months. During this time, he faced a challenging treatment regimen that caused liver complications, requiring adjustments, and ultimately prolonging his recovery. Even simple tasks, like picking up a cup of water, became monumental efforts. Dipesh described TB as debilitating, “It was really strange when you sort of lose that connection with your body in a way. It won’t do what it’s told.”

The long-term hospitalization was a significant challenge for him, particularly as it was his first extended stay away from home. He adapted to the routine of hospital life, but the experience was isolating and difficult, especially for someone so young.

The social stigma associated with TB affected Dipesh, though within his Gujarati Indian community was somewhat understood due to its prevalence. Nonetheless, he initially kept his diagnosis private, only informing close friends and family, when necessary due to the stigma.

After his recovery, Dipesh chose to turn his experience into something positive by participating in the EVENT TB research study investigating how the immune system responds to TB. By volunteering, he contributed to advancements in TB diagnosis and treatment, recognizing the importance of such research for public health and society. His participation also provided him with reassurance, knowing that his health was being closely monitored through the study. As Dipesh put it, “What was initially a very negative, maybe devastating traumatic event, you know, you’re putting it to good use to further whatever research needs doing.”

His experience of both having TB and witnessing a loved one struggle with the same disease deepened his understanding of the critical need for awareness and prevention. To further this cause, he volunteered to participate in a film for an art installation focused on the stigma surrounding TB. This project allowed him to share his story and help raise awareness about the challenges TB patients face, particularly the social stigma that can accompany the disease.

Dipesh’s participation in the EVENT study was valuable for society because it helped researchers better understand the immune response in TB patients, which is crucial for developing more effective ways to identify and treat those at risk of progressing from latent TB infection to active TB disease. His involvement contributed to advancements that could lead to more targeted and effective TB prevention and treatment strategies.

Open access
Published: 09 September 2024

Tuberculosis patients’ satisfaction with directly observed treatment short course strategy and associated factors in Southern Ethiopia: a mixed method study

Simeon Meskele Leyto ORCID: orcid.org/0000-0003-4428-5776 1 ,
Lankamo Ena Digesa 2 ,
Serawit Lakew 2 ,
Habtamu Wondmagegn 1 ,
Kusse Urmale Mare 3 ,
Tesfahun Simon Hadaro 4 ,
Eshetu Zerihun Tariku 5 , 6 &
Mustefa Glagn 5

BMC Public Health volume 24 , Article number: 2452 ( 2024 ) Cite this article

Metrics details

Tuberculosis (TB) is a second major global public health problem and the leading infectious cause of death in Ethiopia. Patients under directly observed treatment short-courses (DOTs) have a higher treatment success rate and reduced drug resistance. A successful treatment outcome and adherence to the treatment are related to patient satisfaction with the DOT strategy. Client satisfaction is one of the indicators of the quality of care. In this perspective, there were limited studies in Ethiopia related to patient satisfaction with the DOTs strategy in the prevention and control of TB to achieve the ‘’END TB Strategy.’’ Therefore, this study was aimed at identifying the TB patients’ satisfaction with the DOTs strategy and associated factors in Gamo Zone, Southern Ethiopia.

An institutional-based cross-sectional study design for quantitative data and a phenomenological approach were employed for qualitative data. The calculated sample size was 374. A systematic random sampling method was used to select study participants. A pre-tested structured interviewer-administered questionnaire for quantitative data and focus group discussions (FGDs) for qualitative data were used for data collection. Bivariable and multivariable analyses were used. The determinants with a p-value < 0.05 were declared to have a significant association with the outcome variable, and an adjusted odd ratio with a 95% confidence interval (CI) was used.

A total of 358 patients participated in the study, with a response rate of 95.72%. The majority of study participants’ ages ranged between 25 and 34 years. The tuberculosis DOT satisfaction rate was 61.17% [56.10-66.25%, 95%CI]. The TB patients who took treatment for 20 weeks or more were 3.97 times [AOR = 3.97; 95% CI (1.55–10.16)] more likely to be satisfied with the DOTs service provided. However, the participants who perceived transport costs as high were 79% [AOR = 0.21; 95% CI (0.06–0.71)] less likely to be satisfied with DOTs. Qualitatively, the participants reported that there was a major problem with laboratory services, which resulted in delays and long appointments to get the results in addition to lack of clean toilets and safe water to swallow medications.

The satisfaction rate for tuberculosis DOTs observed in this study appears to be relatively lower in comparison to other studies. Availing DOTs service nearby patients to enhance the accessibility of the service is crucial to improving patients’ satisfaction with DOTs service. Reducing laboratory result delays by improving laboratory service is essential to enhancing patients’ satisfaction with DOTs. Moreover, improving toilet services, and availing safe water to swallow medications is recommended to enhancing patients’ satisfaction with DOTs service.

Peer Review reports

Introduction

Worldwide, Tuberculosis (TB), curable and preventable disease, is the second leading infectious killer after COVID-19 (above HIV and AIDS) [ 1 ].

According to the World Health Organization’s (WHO) global TB report, an estimated 10 million people were ill with TB, with an estimated 1.2 million and 251,000 deaths among HIV-negative and HIV-positive people, respectively [ 1 ].

It is estimated that 2.5 million people fell ill with TB in the African and continues to be a significant public health problem which accounts for 23% of new case and 31% of TB-related deaths [ 2 ].

Ethiopia is among the countries with the highest TB burden [ 3 ]. Even though TB deaths have dropped significantly, it is still continued to be the leading infectious killer in Ethiopia [ 4 , 5 ].

The Directly Observed Treatment Short-course (DOTs) strategy is a global and effective TB control approach that was declared in 1994 [ 6 ], has been believed to be a cornerstone, and remains a central pillar in improving treatment success, enhancing treatment adherence, controlling drug resistance, strengthening the health system, and engaging health care providers [ 7 , 8 ]. The DOTS strategy has five-component package: political commitment, diagnosis using sputum smear microscopy, regular supply of TB drugs and laboratory, short-course chemotherapy, and standard system for recording and reporting the number of cases and treatment outcome [ 9 ].

According to the studies that were conducted in India, the level of satisfaction of the study participants towards TB services ranged from 76 to 87% [ 10 , 11 , 12 ]. Other studies in Uganda showed that 91% of the study participants were satisfied with the TB services provided to them [ 13 ]. Besides, studies in Ethiopia pointed out that the satisfaction level of DOTs ranged from 67 to 91% [ 14 , 15 , 16 ].

Health facility structure-related, process-related (facility service delivery system)-related, and outcome-related factors can affect satisfaction with DOTs service [ 17 ]. Accordingly, previous studies revealed that structure-related factors such as access to TB services nearby [ 12 , 15 , 18 ]. treatment room privacy, safety of the facility, and easy access to refill drugs [ 13 , 15 ] were associated with the DOTs satisfaction. In addition, process-related factors such as a friendly and caring attitude of health care providers [ 19 ], waiting time, explanation and response to the questions, and skills of the health care providers have been associated with patient satisfaction with the DOTs strategy, according to reports from Ethiopia [ 15 ], Uganda [ 13 ], and Nigeria [ 12 ]. Symptom reduction after taking the treatment was also related to satisfaction with DOTs [ 15 ]. On the other hand, treatment interruption, poor adherence to the treatment, and deviance from the treatment were related to dissatisfaction with the DOTs strategy [ 13 , 14 ].

Measuring a patient’s satisfaction with a health care service is a major concern for a treatment that requires long follow-up [ 10 ]. However, there was limited evidence with regards to TB patients’ satisfaction with the DOTs strategy in Ethiopia, particularly in southern Ethiopia. Thus, this study was aimed at identifying the level of TB patients’ satisfaction with the DOTs strategy and associated factors in public health facilities in Gamo Zone, Southern Ethiopia.

Methods and materials

The study was conducted in public health facilities in Gamo Zone, South Ethiopia Regional state. According to the 2007 census conducted by the Central Statistical Agency of Ethiopia, the zone has a total population of 1,123,388 with 558,297 (49.7%) of men, 565,091 (50.3%) women [ 20 ]. The Zone is composed of 14 districts with administrative town of Arba Minch, which is located 495 km (km) from Addis Ababa. There were one general hospital, four primary hospitals, and fifty-six health centers in the Gamo zone.

Study design and period

A facility-based cross-sectional study design for quantitative data and a phenomenology study approach for qualitative data were used from January 1 to June 30, 2021.

Source population

All TB patients under DOTs service in public health facilities in the Gamo zone.

Study population

All TB patients who had been registered for DOTs service in public health facilities in the Gamo zone and fulfilled inclusion criteria were study population.

Eligibility criteria

All TB patients aged 15 years and older and those under directly observed treatment for at least two weeks were included. And seriously ill patients were excluded from the study.

Sample size determination for quantitative data

The sample size was determined by a single population formula with the following assumptions: 5% margin of error, 95% confidence level, and satisfaction level from the previous study in Addis Ababa [ 15 ]. Based on these assumptions, the calculated sample size was 374 after considering a 10% non-response rate.

n = desired sample size.

p = assumed proportion of satisfaction level from the previous study.

α (level of significance or committing type one error = 5%).

Z (The standard normal curve at 95% CI and 5% level of significance = ± 1.96 (two sided).

W (Margin of error or the deference in population and sample estimates = 5%).

n = (1.96) 2 * 0.67 * 0.33)/ (0.05) 2 .

Expecting a 10% non-response rate, the final sample size calculated was 374.

Sampling procedure for quantitative data

Gamo Zone has four town administrations and 14 districts. In this zone, there was one general hospital, four primary hospitals, and 56 health centers providing DOTs service. About 40% of the facilities were selected randomly from each level. The proportional allocation of the sample was made in selected health facilities. For a proportional allocation of the sample for each health facility, the facility’s annual patient load was obtained from the preceding year. Accordingly, a monthly patient flow was estimated. The study respondents were selected using a systematic random sampling method as follows in (Fig. 1 ).

Sampling procedure for selecting study participants in public health facilities Gamo zone, Ethiopia 2021

Study design for qualitative data

A qualitative study method was employed to gain a comprehensive understanding of DOTs strategies by gathering insights from multiple viewpoints within a group setting to complement the quantitative study.

Sample size determination for qualitative data

A total of 48 participants were involved in eight FGDs, each group containing six participants.

Operational definitions and measurements

Directly observed treatment (dot).

is watching the patient taking every recommended or scheduled dose in the right combinations, on the correct schedule for the appropriate duration though help of TB treatment supporters [ 15 , 21 ].

Patient satisfaction

the feeling of the TB patient and his or her perception of TB care services with the DOTS strategy [ 15 ].

Donabedian model

The modern model for improving health care quality is used to measure health care quality by categorizing it into three categories [ 17 ].

Health facility structure:

an environment in which health care is provided.

A health facility service delivery system (process)

is a method of providing health care services.

a result of health care.

Satisfaction measurement

It was measured by a Likert scale which contains 23 items. Each item contains a score of a five-point scale ranging from 1 (very dissatisfied) to 5 (very satisfied) i.e. (1 = strongly dissatisfied, 2 = dissatisfied, 3 = neutral, 4 = satisfied, 5 = strongly satisfied). The respondents with a score of less than the mean were classified as dissatisfied, and those with a score of mean value and above were considered satisfied [ 15 , 22 ].

Seriously ill patients

Included TB patients with; life-threatening disease = acute disseminated miliary TB, TB meningitis or TB peritonitis; Risk of severe disability = spinal TB, TB pericarditis, bilateral TB pleural effusion, renal TB; Extensive X-ray lesions without cavitation in immune-compromised patients, e.g., diabetics, HIV-positives, or patients with other concomitant disease.

Data collection methods and tools

For quantitative data.

A pre-tested, structured interviewer-administered questionnaire adopted from the previous study [ 15 ] was used for data collection. Amharic version of the questionnaire was used for data collection. The data were collected by BSc nurses and BSc public health care personnel, and experienced MSc public health personnel supervised the data collection. Two days of training were given to data collectors and supervisors on the purpose of the study and how to interview study participants. The data collection instrument contains 23 items with a 5-point Likert’s scale, where the level of satisfaction ranges from strongly dissatisfied to strongly satisfied, 1 to 5. The items were categorized into three based on the Donabedian quality healthcare model [ 17 ]. Accordingly, 10 items focus on the structure, 10 items on the process, and 3 items on the outcome.

For qualitative data

The data were collected through focused group discussions (FGDs). The FGDs were conducted by the investigators. FGDs were recorded both on audiotape and in handwriting. The audiotape was then transcribed.

Data processing and management

The data were collected using the Kobo Toolbox and analyzed by Stata 14. The descriptive statistics were performed. Frequency and percent were used to present categorical predictors. Binary logistic regression analysis was performed to see the combined effect of predictors on patients’ satisfaction and to select potential candidates for the final model; variables with a P-value of ≤ 0.25 in the bivariable analysis were passed to the multivariable logistic regression analysis. A multivariable logistic regression analysis was performed to identify the independent effects of predictors on outcome variables. The factors with P < 0.05 were considered to have a significant association with satisfaction with the DOTS strategy, and adjusted odd ratios with a 95% confidence interval (CI) were used to measure the degree of association.

The field notes and audio that were collected in Amharic were translated and transcribed verbatim to English by the investigators and other TB experts. The collected data were transcribed, and emerging ideas were listed without strict sequences. The codes and subthemes/categories for the listed ideas were created. Themes were generated from those categories. Thematic analysis was done.

Data quality assurance

A pre-test was conducted by taking 5% of the sample size outside of the study area before the actual study. Based on the pre-test results, the questionnaire was adjusted contextually and terminologically and administered to the study population. Collected data were checked for completeness, and consistency; daily close supervision was maintained.

Socio-demographic characteristics

A total of 358 patients participated in the study, with a response rate of 95.72%. Of the total study participants, 233 (65.1%) and 125 (34.9%) were males and females, respectively. The majority of study participants’ ages ranged between 25 and 34 years. Two hundred ten (58.66%) of the study participants were rural residents, and 99 (27.65%) of the participants had no formal education, whereas nearly one-third of participants had secondary education (Table 1 ).

Health and treatment-related characteristics

Nearly two-thirds of the study participants, 233 (65.08%) traveled ≤ 30 min to get service from a nearby health facility. Among study participants, 41.06% and 41.62% were on TB treatment for 2–8 weeks and 9–19 weeks, respectively. Three hundred and fifteen patients (87.99%) had treatment supporters. Of those, 173 (54.92%) chose a family member as their treatment supporter (Table 2 ).

Factors related to TB treatment service satisfaction

Among the three service categories (structure, process, and outcome) used to assess the overall satisfaction of the DOT strategy, the majority of the patients were satisfied with the services provided to them and the health care providers’ interactions, facility-related information, and treatment outcomes they gained after starting TB treatment.

Health facility structure-related factors

More than two-thirds of the participants were satisfied with the availability of the necessary equipment, drugs, and laboratory reagents to treat TB. The highest level of patient satisfaction was recorded regarding the treatment room’s privacy. However, a relatively lower level of satisfaction was noted for the availability of signage and directions on where to go in the health facility (Table 3 ).

Health facility service delivery system (process) related factors

The findings revealed that the lowest level of satisfaction was documented on ‘’health care providers (HCPs) used medical terms without explaining what they meant.‘’ However, the highest level of participant satisfaction was recorded in the explanation and response of HCPs to patient questions and HCPs’ ability to diagnose, treat, and care for TB (Table 4 ).

Outcome related factors

A nearly comparable proportion of the study participants were satisfied with the TB symptoms reduction rate and physical and psychological well-being gained due to TB treatment (Fig. 2 ).

Outcome measuring item of tuberculosis patients with DOTs strategy in selected health facilities, 2021

Factors associated with TB patient’s satisfaction with the DOTS strategy

In binary logistic analysis, age, occupation, time to travel to the health facility, duration of the treatment, perceived transport cost, TB treatment supporter, type of TB, and perceived time spent with a health care provider were associated with the outcome variable at a p-value of ≤ 0.25. However, only the duration of treatment and perceived transport cost were significantly associated with the outcome variable at p < 0.05 in the multivariable logistic regression model.

The TB patients who took treatment for 20 weeks or more were 3.97 times [AOR = 3.97; 95% CI (1.55–10.16)] more likely to be satisfied with the DOTs service provided in public health facilities compared to their counterparts. On the other hand, the patients who spent high transportation costs to get service to the health facilities were 79% [AOR = 0.21; 95% CI (0.06–0.71)] less likely to be satisfied with DOTs as compared with those who spent low and medium costs to travel (Table 5 ).

Qualitative study findings

Characteristics of focus group participants in qualitative study.

A phenomenological approach was employed to generate qualitative data, where eight focus group discussions (FGD) were conducted, with each group consisting of six members. The mean age of the FGD was 35 years. Each group was composed of males and females. A total of 20 female participants were involved in the FGDs. The participants were selected from the intensive and continuation phases of the treatment. The interview guide questions, or probing questions, were “What do you explain about your comfortableness with the registration room, laboratory, and treatment room? How do you explain the TB care you received at this health facility? What do you tell us about health care workers welcoming and respecting you when you receive care? How do you feel now after taking anti-TB medicine? And what do you suggest for TB treatment service improvement?” These provoking or leading questions, initially developed in English from different literatures [ 14 , 15 , 17 ] were translated and transcribed verbatim by the researcher and other TB experts into Amharic versions before conducting the interview. Since the qualitative interview in the current study was aimed at providing supplementary information, the researchers mainly relied on quantitative work to discuss the current study findings.

DOT satisfaction

Five themes were identified by the focus group participants. Theme I : deals with registration and laboratory service. Theme II : reviews facilities stand in the selected healthcare institutions (toilets and safe water). Theme III : discusses TB clinic care and service. Theme IV : emphasizes improvement after starting to take anti-TB medication. Theme V : explores suggestions for service improvement to enhance TB DOT satisfaction.

Theme I: Registration and laboratory service

From Five themes of FGD identified to assess patients’ satisfaction with DOTs Strategy, major problems were reported regarding registration rooms and laboratory service. The Patients generally indicated there were long waiting times at the registration areas, long appointment systems, and result delays were the frequent problems.

One participant explained: “There is a problem in the laboratory. The lab result was not given on time. I stayed for 12 days to get the result and suffered a lot for a single result.”

The other respondent added, “I agree with what he said… I came here on the first day of December, and until the 12th of the month, they gave me an appointment for the laboratory result, but they didn’t solve my problem.”

Theme II: Facilities stand in the selected healthcare institutions (toilets and safe water)

The focus study participants explained that the main problem related with facilities was getting clean toilets and the availability of safe water to swallow medications. A few participants argued that they did not know where the toilet was and where the water avails for swallowing the medications. The respondent explained the inconvenience as: “The toilet condition is not good. I prefer not to use the toilet because, post-toilet, most of the time even it causes me abdominal discomfort.

The focus study participants explained lack of clean toilets and safe water to swallow medications. The respondents explained that though there were improvements in symptom reduction after onset of TB treatment but there is no water to take the drugs and clean toilet, which enables us to use near to the treatment room. The respondent explained the premise inconvenience as: “For truth, nobody can use the toilet because of its unpleasant smell and uncleanness. I can assure it is not good for patients even for those healthy personnel. I should have to go to Cafeteria or hotel to empty my colon since there was no convenient toilet.”

The respondent also added “The other problem is lack of water to clean hands, and to take medicine.”

Another respondent explained the water problem as follows: “They add water into the tanker where many people put their hands on it. There is no clean water to take medicine, and to clean hands after rest room.”

Theme III: TB clinic care and service

The discussants stated that the healthcare providers in TB clinics were welcoming and friendly.

Most patients reported having friendly relationships with health care service providers at the TB clinics. Participants further said they benefited from the information they obtained from professionals on duration and side effects of treatment, risks of non-adherence as well as dietary practices to follow and habits to avoid. Many of the participants declared that “the care we get here is wonderful, and the providers gave us the advice we wanted in a way we understood.” A few discussants stated that “even if the clinics get closed during regular appointments after the phone call, they will come soon after they call to provide the service and counseling they require.”

Theme IV: Improvement after starting anti-TB medication

The study focus group participants stated, “We get symptom relief; the symptoms reduced from day to day, our weight increased, our appetite improved, and we are psychologically well soon after starting the medications.‘’ Besides, many of the participants reported that they did not experience major problems associated with taking medications.

Theme V: Suggestion for service improvement

The discussants suggested the services at registration and the laboratory should be improved to enhance TB-DOT client satisfaction. They forwarded the idea that priority should be given to TB patients, or if possible a separate TB laboratory service room established or considered. The suggestions were explained by the respondent: “I’m still going to request the lab service improvement and water availability. Another discussant added, “I am satisfied from the side of HCPs because I don’t stay for more than 15 minutes. I took my medicine and advice they give within 10 minutes”. “My main comment would be regarding Laboratory service delivering system I kindly request concerning bodies to improve and give priority to the lab.”

This study was aimed at assessing tuberculosis patients’ satisfaction with directly observed treatment short-course strategy, and associated factors in southern Ethiopia, with a total of 358 participants included. The study findings showed that the proportion of the patient satisfaction rate was 61.17% [56.10-66.25%, 95%CI], and the TB patients who took treatment for 20 weeks or more were satisfied with DOT service. However, those who perceived high transport costs were less likely to be satisfied with the service.

The finding of this revealed that the satisfaction rate of DOTS service was 61.17% [56.10-66.25%, 95% CI]. This finding was lower when compared to other study findings in Ethiopia, [ 13 , 14 ], Uganda [ 13 ], and India [ 9 , 10 , 15 ]. The discrepancy may be due to study health facility variations, where the current study included peripheral health centers that were sited in different geographic locations in the zone. Besides, the variation may be due to health care workers’ capacity and motivation level [ 19 ].

Similar to the previous study finding [ 22 ], waiting areas, safety of seats, and easy access of the HCPs to refill patients’ medication were identified as structure-related factors that lead to patient satisfaction.

However, the lack of signage and direction guidance on where to go in the health facility, 66 (18.44%), and the lack of cleanliness and poor working order of latrines, 46 (12.85%), were attributes of patient dissatisfaction. In contrast to the study conducted in Kampala, Uganda [ 13 ], the current study showed the highest patient satisfaction regarding treatment room privacy (66.76%).

Different study findings [ 11 , 12 , 14 ] revealed that the friendly and caring attitude of health care workers, short waiting times, explanations, and responses to the questions and skills of HCPs were stated as factors for the highest patient satisfaction. However, in this study, the appointment system to follow up and the allotted time of HCPs to check clinical conditions were found to be attributes of patient satisfaction, whereas using medical terms without explaining their meanings and spending an extensive amount of time with registration were stated as process-related causes of dissatisfaction in this study.

Like other studies [ 14 , 18 ], in this study, the duration of treatment for 20 weeks and above and perceived transport cost were significantly associated with patients’ satisfaction with directly observed treatment short course strategy.

The TB patients who took treatment for 20 weeks or more [AOR = 3.97; 95% CI (1.55–10.16)] were 3.97 times more likely to be satisfied with the DOTS service compared to their counterparts. This study finding is supported by previous study findings [ 13 , 15 , 23 ] where patients with increased treatment duration and those with improvement in symptom reduction are more likely to be satisfied with DOTS services.

The patients who spent high transportation costs to get service to the health facilities were 79% [AOR = 0.21; 95% CI (0.06–0.71)] less likely to be satisfied with DOTS as compared with those who spent low and medium costs. The possible explanation for this is the fact that since the study area included hospitals and health centers with different geographical locations and less road accessibility, the patients might be exposed to high transport costs, which may lead to patients’ dissatisfaction with the DOT strategy. This finding is also supported by study conducted in Addis Ababa Ethiopia where participants dissatisfied due to making a daily visit to health facilities for DOT service due to the distance of the facilities from their residences, lack of or high transportation cost [ 21 ].

Another possible reason could be, although TB services are supposed to be provided free of charge, TB affected families spend different types of costs in the process of seeking care, which might include health and non-health related costs which might lead them to dissatisfaction [ 24 ].

The quantitative approaches highlighted, similar to the study conducted in Ethiopia [ 14 , 15 ], the study shows that satisfaction level of patients with TB are influenced by on time availability and good reception of HCP, provision of information and respect to the patients and waiting time.

However, current study shows delay in laboratory result, lack of clean toilets and safe water to swallow medications as major factors of tuberculosis DOTs strategy dissatisfaction.

The tuberculosis DOTs satisfaction rate in this study was lower than in other studies. The TB patients who took treatment for 20 weeks or more were more likely to be satisfied with DOTs. However, the participants who reported a perceived high transport cost were less likely to be satisfied with DOTs. In the qualitative report, the participants indicated that there was a major problem with laboratory services, which resulted in delays and long appointments to get the results besides lack of clean toilets and safe water to swallow medications. Enhance the accessibility of the DOTs service to the community level and minimizing laboratory result delays is crucial to improve patients’ satisfaction with DOTs strategy. Moreover, improving toilet sanitation, and availing safe water in health facilities to swallow medications is recommended to enhancing patients’ satisfaction with DOTs service.

Data availability

All relevant data in the current study is available in the submitted manuscript.

Abbreviations

Arba Minch University

College of Medicine and Health Sciences

Confidence Interval

Directly Observed Treatment

Directly Observed Treatment, Short-course strategy

Health Care Providers

Tuberculosis

World Health Organization

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Acknowledgements

We are thankful to AMU CMHSs research coordination office for giving us this opportunity to fund this research. We would also like to extend our gratitude to the staff of health institutions for their necessary information and support.

This research work was supported by AMU, CMHSs research coordination office.

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SM, LE, EZT, MG, and SL designed the study and collected data. HW, TSH and KUM wrote the first draft manuscript. SM, LE, EZT, MG, SL, and KUM analyzed the data; and critically read and modified the drafted manuscript. SM, LE, EZT, MG, SL, HW, TSH and KUM read and approved the final draft.

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Leyto, S.M., Digesa, L.E., Lakew, S. et al. Tuberculosis patients’ satisfaction with directly observed treatment short course strategy and associated factors in Southern Ethiopia: a mixed method study. BMC Public Health 24 , 2452 (2024). https://doi.org/10.1186/s12889-024-19940-6

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Published: 09 September 2024

Developing a framework for identifying risk factors and estimating direct economic disease burden attributable to healthcare-associated infections: a case study of a Chinese Tuberculosis hospital

Nili Ren 1 na1 ,
Xinliang Liu 2 , 3 na1 ,
Guofei Li 1 ,
Ying Huang 1 ,
Desheng Ji 1 ,
Cheng Peng 1 ,
Jing Sun 4 &
Hao Li ORCID: orcid.org/0000-0002-5155-4033 2

Global Health Research and Policy volume 9 , Article number: 33 ( 2024 ) Cite this article

Metrics details

Healthcare-associated infections (HAIs) represent a major global health burden, which necessitate effective frameworks to identify potential risk factors and estimate the corresponding direct economic disease burden. In this article, we proposed a framework designed to address these needs through a case study conducted in a Tuberculosis (TB) hospital in Hubei Province, China, using data from 2018 to 2019. A comprehensive multistep procedure was developed, including ethical application, participant inclusion, risk factor identification, and direct economic disease burden estimation. In the case study, ethical approval was obtained, and patient data were anonymized to ensure privacy. All TB hospitalized patients over the study period were included and classified into groups with and without HAIs after screening the inclusion and exclusion criteria. Key risk factors, including gender, age, and invasive procedure were identified through univariate and multivariate analyses. Then, propensity score matching was employed to select the balanced groups with similar characteristics. Comparisons of medical expenditures (total medical expenditure, medicine expenditure, and antibiotics expenditure) and hospitalization days between the balanced groups were calculated as the additional direct economic disease burden measures caused by HAIs. This framework can serve as a tool for not only hospital management and policy-making, but also implementation of targeted infection prevention and control measures. Moreover, it has the potential to be applied in various healthcare settings at local, regional, national, and international levels to identify high-risk areas, optimize resource allocation, and improve hospital management and governance, as well as inter-organizational learning. Challenges to implement the framework are also raised, such as data quality, regulatory compliance, considerations on unique nature of communicable diseases and other diseases, and training need for professionals.

Introduction

Healthcare-associated infections (HAIs) pose a major global health burden. The World Health Organization (WHO) reported that in 2022, globally in acute-care hospitals, about 7 out of every 100 hospitalized patients in high-income countries (HICs) and 15 out of every 100 hospitalized patients in low- and middle-income countries (LMICs) obtained at least one HAI, and an average of 1 in every 10 hospitalized patients with HAIs died [ 1 ]. HAIs also lead to the increased occurrence of antimicrobial resistance (AMR)—another major global health issue [ 2 ]. However, from the perspective of the economic disease burden attributable to HAIs, the updated evidence is scant, especially in settings with limited resources. A framework is required to estimate the direct economic burden attributable to HAIs at minimum level-in individual hospitals, providing empirical evidence and support targeted interventions. In response to the global challenge of HAIs, the WHO announced its first-ever global strategy on infection and prevention control (IPC) at the 76th World Health Assembly in 2023, and an associated global action plan and monitoring framework will be completed by 2024 [ 3 ]. Effective and tailored IPC measures are formulated based on identifying the risk factors associated with HAIs within hospitals. The set of risk factors associated with HAIs could be different in different hospitals. Therefore, a general framework should be developed to identify the risk factors associated with HAIs unique to each hospital setting.

The framework on estimating the direct economic disease burden attributable to HAIs was developed before by our team and applied within general hospitals in China and Nepal [ 4 , 5 , 6 ]. However, it has yet to be used in specialized hospitals, such as those focusing on Tuberculosis (TB). Specialized hospitals, particularly TB hospitals, face unique challenges that general hospitals may not encounter, such as managing patients with complex and prolonged treatment needs, making them more vulnerable to HAIs. Applying the framework in such setting is important to address these specific challenges and refine infection control strategies. While the framework itself remains consistent, its application in TB hospitals allow for the adaptation of infection control measures tailored to the unique needs of TB patients. The risk of HAIs is further compounded by the nature of TB itself-a deadly respiratory infectious disease, which remains a significant global health issue. According to the latest estimates reported by the WHO in 2023, around 10.6 million population were estimated to be infected with TB worldwide, and 1.3 million of them died in 2022 [ 7 ]. This highlights the ongoing need for effective management and control of TB, making it a relevant focus for investigating HAIs. Particularly, the South-East Asia Region had the highest number of population infected with TB at 4.85 million, followed by the African Region at 2.48 million [ 7 ]. These figures emphasize the global burden of TB and the necessity for targeted interventions in high-prevalence areas. The high incidence and the complex nature of TB treatment environment can increase the vulnerability of patients to HAIs, thus escalating the economic and health burden on healthcare systems. TB treatment often involves prolonged hospital stays [ 8 ], intensive antibiotics use [ 9 ], and invasive procedures [ 10 ], all of which elevate the risk of HAIs. Implementing the framework in specialized hospitals helps gather data that are more relevant to these settings, providing insights into the specific economic burden of HAIs in TB hospitals and offering a clearer picture of the financial impact and resource requirements for effectively managing HAIs in specialized care environments.

To address above situation, a framework was developed by our team based on the case study conducted in a Chinese TB hospital to analyze the potential risk factors and estimate the direct economic burden attributable to HAIs. Furthermore, this framework aims to provide healthcare stakeholders with a tool for implementing effective IPC measures and evaluating the financial impact of HAIs. The Chinese TB hospital is located in Hubei Province of China, which is a tertiary pulmonary and tuberculosis control hospital that focuses on the prevention and control of TB, clinical diagnosis and treatment of pulmonary diseases, and medical/health education and research. This TB hospital specifically handles complex cases of TB, including multi-drug-resistant TB (MDR-TB), which require prolonged treatment and intensive care. It is a specialty hospital at a city level. Compared to other TB hospitals at a city level in Hubei Province, it is the only tertiary hospital, while others are secondary hospitals. Table 1 shows the information of the operational and treatment efficacy about the hospital from 2018 to 2019. The number of beds and average hospitalization days remained stable at 406 and 9.73 days, respectively. The mortality rate of hospitalized patients increased from 0.45 to 0.72%, and the number of outpatient and emergency patients rose significantly from 113,819 to 129,905 in this TB hospital. The annual HAIs prevalence decreased from 0.53 to 0.34%.

Framework development

Figure 1 presents that a framework analyzes the impact of HAIs within a hospital setting, which includes four steps. The first step is an ethical application, ensuring that all data collection and analysis adhere to the highest standards of research ethics. The first step secures the approval of relevant ethics committees and establishes a foundation of trust and legality for research. Then, the second step is the inclusion of participants, which involves a detailed screening process to select all eligible hospitalized patients based on specific criteria. This selection process ensures that the data extracted are relevant and robust, providing a solid base for further analysis. The third step is that the framework identifies risk factors associated with HAIs, which involves a thorough analysis of patient data to ascertain factors that may increase the likelihood of HAIs, such as the length of hospitalization, the use of invasive procedure, or the presence of comorbid conditions. Understanding these risk factors is pivotal for developing targeted strategies to reduce the incidence of HAIs. Finally, the fourth step is the estimation of the direct economic disease burden attributable to HAIs. By identifying the significant risk factors in the third step, we could accurately calculate the additional medical expenditures and hospitalization days, using these identified risk factors as covariates. The economic burden analysis helps to quantify the financial impact of HAIs, highlighting the economic incentives for hospitals to invest in effective IPC measures. Overall, the framework employs a retrospective cross-sectional study design, allowing for the analysis of data from previously hospitalized patients. This approach is advantageous as it provides a snapshot of hospital performance over a specific period, enabling hospital managers and policy decision-makers to implement evidence-based improvements in patient care and IPC measures. This comprehensive and methodical approach ensures that every aspect of the impact of HAIs is captured and addressed, including from ethical considerations to risk factor analysis and economic burden analysis.

Flow chart of the framework on identification of risk factors and estimation of the direct economic disease burden attributable to HAIs

Step 1: ethical application

Before extracting data from hospitals, it is essential to secure approval from the hospitals’ ethics committees, particularly when the data involve personal information about hospitalized patients. This case study obtained the approval from the TB hospital’s ethic committee (Wuhan Pulmonary Ethic Committee (2021) 28). To ensure anonymity, original hospital numbers were replaced with unique identifiers created by a staff member from the Department of Medical Records. Personal information pertaining to the hospitalized TB patients was omitted during data extraction from the hospital information systems (HIS). As a result, there was no need for informed or verbal consent from the TB hospitalized patients.

Step 2: inclusion of participants

This phrase primarily involves the inclusion of all hospitalized patients, followed by their classification into groups with and without HAIs for subsequent analysis of risk factors and economic burden. The specific steps taken in this TB hospital were as follows, with Fig. 2 illustrating the entire participant inclusion flowchart:

All TB hospitalized patients who were discharged from 0:00 1st January 2018 to 23:59 31st December 2019 were included. TB hospitalized patients information was retrieved from the HIS. Due to the COVID-19 pandemic, the local government placed strict restrictions on data sharing among local hospitals, resulting in inaccessible data from 2020 to 2022. As demonstrated in Fig. 2 , a total of 23,080 TB hospitalized patients were included during the study periods, with 11,332 patients in 2018 and 11,748 in 2019.

Those TB hospitalized patients staying in hospital less than 48 h were excluded, since the criteria for HAIs require a minimum hospital stay of more than two days [ 11 ]. After applying this exclusion criterion, the total number of included TB hospitalized patients was reduced to 21,148.

The remaining TB hospitalized patients were then categorized based on whether they had acquired HAIs, according to the inclusion and exclusion criteria detailed in Additional file 1 : Table S1. Following this categorization, 78 TB hospitalized patients were identified with HAIs, while 21,070 TB hospitalized patients did not have HAIs.

Flow chart of the included participants from the Chinese TB hospital in 2018 and 2019

Step 3: identification on risk factors associated with HAIs

The risk factors analysis on association with HAIs among hospitalized patients typically involves selecting potential risk factors, conducting univariate analysis, and performing logistic regression analysis. Here are the specific steps taken at this TB hospital:

Our research team has conducted a systematic review and meta-analysis to identify risk factors associated with HAIs among TB hospitalized patients in China [ 12 ]. This systematic review concluded a list of significant risk factors, including age older than 60 years, presence of complications, diabetes mellitus, invasive procedure, longer than 15 hospitalization days, secondary TB, smoking, presence of underlying disease, and use of antibiotics [ 12 ]. This comprehensive review provided a robust foundation for identifying potential risk factors in the TB hospital to collect data. Considering the data availability from this TB hospital, gender, age older than 60 years, diabetes mellitus, invasive procedure, more than 15 hospitalization days, presence of underlying disease, and used of antibiotics were selected as potential risk factors in this case study. Descriptions and assigned values of the selected potential risk factors are listed in Additional file 1 : Table S2.

A univariate analysis was conducted to examine the association between the selected risk factors and HAIs among the TB hospitalized patients. The chi-squire test was used for those categorical variables with expected frequencies above five, while the Fisher exact probability test was used for those with frequencies below five. The codes for conducting the univariate analysis can be found in Additional file 2 . Table 2 demonstrates that gender, longer than 15 hospitalization days, invasive procedure, and the use of antibiotics were consistent risk factors, each showing a statistically significant association with HAIs among TB hospitalized patients in both 2018 and 2019 ( P < 0.05).

A binary logistic regression model was applied to investigate the severity of potential risk factors associated with HAIs among TB hospitalized patients. To avoid ‘Table 2 Fallacy’ where multiple adjusted odds ratios (aOR) derived from a single logistic regression model misinterpret the impact of primary risk factors due to covariate heterogeneity [ 13 , 14 ], several separate binary logistic regression models were conducted by adjusting gender and age, as both are general socio-demographic characteristics and are common and likely to be prognostic. The codes for this binary logistic regression analysis are available the in Additional file 2 . Table 3 shows that consistently, the significant risk factors associated with HAIs were invasive procedure (aOR 7.41 in 2018; 4.29 in 2019), longer than 15 hospitalization days (aOR 13.15 in 2018; 39.76 in 2019), and use of antibiotics (aOR 8.99 in 2018; 33.46 in 2019) ( P < 0.05).

Step 4: estimation on the direct economic disease burden attributable to HAIs

In order to accurately estimate the direct economic disease burden attributable to HAIs, the approach adopted involves a 1:1 matching method to compare medical expenditures and hospitalization durations between hospitalized patients with and without HAIs. This method focuses on various medical expenditures including total medical expenditure, medicine expenditure, and antibiotics expenditure, as well as hospitalization days. These measures comprehensively reflect the economic burden and resource consumption associated with HAIs during hospitalization. By providing a detailed view of the additional costs incurred by hospitalized patients with HAIs, these measures highlight the financial impact on the healthcare system. The following specific steps were implemented in this TB hospital, as illustrated in Fig. 1 :

Prior to the data analysis, we adjusted the medical expenditure data from 2018 to reflect 2019 values using the Consumer Price Indices (CPI) for medicines and healthcare services in Hubei Province [ 15 ]. The adjustment formula is expressed as follows: $E_{{Y_{{\text{b}}} }} { = }E_{{{\text{Y}}_{{\text{a}}} }} {\text{(1 + n}}_{{Y_{{{\text{a}} + 1}} }} {\text{\% )( 1 + n}}_{{Y_{{{\text{a}} + 2}} }} {)} \cdots {\text{ (1 + n}}_{{Y_{{\text{b}}} }} {\text{\% )}}$ . Specifically, E represents the medical expenditures; Y denotes the year; and n indicates the annual increase in CPI.

Fig. 2 displays the respective numbers of TB hospitalized patients diagnosed with HAIs in the years 2018 and 2019, which were 44 and 34, respectively. Additional file 1 : Table S3 provides an overview of the medical expenditures and hospitalization days for TB hospitalized patients with HAIs. Given that the data on medical expenditures and hospitalization days were skewed, the median, interquartile range (IQR), and the overall range (minimum to maximum values) were used to present the average levels of these variables. The average total medical expenditure increased from ¥30,730.70 in 2018 to ¥37,669.07 in 2019. Similarly, the average medicine expenditure rose by 77.83%, while the average hospitalization days increased slightly. The range of antibiotics expenditure broadened considerably, despite the average costs remaining stable. These trends highlighted an upward shift in healthcare spending and resource utilization for TB hospitalized patients with HAIs over 2018 and 2019.

Propensity Score Matching (PSM) was utilized to select a balanced cohort of TB hospitalized patients with and without HAIs. PSM has been extensively applied in medical research to mitigate selection bias and estimate the effects of exposure in observational studies [ 16 , 17 ]. It operates by matching two groups with similar propensity scores (PS), which represent the likelihood of a patient being exposed to HAIs based on predefined patient characteristics, with scores ranging from 0 to 1 [ 18 , 19 ]. In this TB hospital, the Generalized Boosted Model (GBM) was used to generate the PS [ 20 ]. A PSM method employing a caliper of 0.25 standard deviations (SD) of the PS facilitated the 1:1 matching without replacement, thus achieving a balanced comparison between TB hospitalized patients with and without HAIs. Based on the third step, which focuses on identification of the risk factors associated with HAIs, the covariates included in the models were gender, age, and use of invasive procedures such as central venous catheter, urine tube intubation, arteriovenous cannula, endotracheal intubation, mechanical ventilation, drainage, and tracheostomy. The variables including longer than 15 hospitalization days and use of antibiotics were excluded, since the antibiotics expenditure and hospitalization days were selected as measures for estimating the additional direct disease burden attributable to HAIs. The codes for the PSM analysis are available in Additional file 2 . The resulting matched pairs were 44 and 34 for the years 2018 and 2019, respectively. Additional file 1 : Table S4 displays the comparisons of covariates between the two groups before and after performing PSM, confirming the effectiveness of the matching in balancing the covariates.

After selecting the balanced groups of TB hospitalized patients with and without HAIs, the Wilcoxon matched-pairs signed-rank test was conducted to compare differences in medical expenditures and hospitalization days, thus assessing the additional direct economic disease burden attributable to HAIs. The codes for this statistical test are also included in Additional file 2 . Table 4 shows that in both years of 2018 and 2019, TB hospitalized with HAIs consistently incurred much higher medical expenditures across all categories compared to those without HAIs. In 2018, the additional total medical expenditure was ¥15,417.31, with similar disparities in medicine and antibiotics expenditures, at ¥5754.74 and ¥2421.63 respectively ( P < 0.01). The trend continued in 2019, where the additional total medical expenditure increased to ¥26,978.70, indicating a rising cost burden associated with HAIs. The additional medicine and antibiotics expenditures also increased, rising to ¥10,595.32 and ¥2218.66, respectively. Hospitalization days also reflected significant disparities, with HAIs patients hospitalized for much longer periods. In 2018, the additional hospitalization days were 11.5 days, and this gap widened in 2019 to 21.5 days. These indicate that HAIs were associated with substantially higher medical expenditures and longer hospital stays, with these disparities growing from 2018 to 2019. This underscores the critical financial and operational impacts of HAIs on healthcare systems.

Rosenbaum bounds for robust test has been widely applied to assess the sensitivity to hidden bias in observational studies [ 21 ]. Specifically, it is used to quantify the impact of unobserved confounding factors after performing the PSM analysis. In this case study, the sensitivity parameter Gamma (Γ) ranged from 1 to 2, which represents the degree of departure from random assignment due to an unobserved confounding factor. The codes for calculating Rosenbaum bounds are attached in Additional file 2 . As indicated in Table S5, for all measures in both years 2018 and 2019, even when Gamma (Γ) equaled to a large value, such as 2, the P values (Sig +) were still lower than 0.05. These results indicated that the analyses on the additional direct economic disease burden were robust to hidden biases.

Different matching methods including 1: 2, 1: 3, and 1: 4, when conducting the PSM analysis, were employed to conduct the sensitivity analysis in order to test the robustness of the results generated from 1: 1 matching method in this case study. Table S6 shows that the additional total medical expenditure per TB hospitalized patient was ¥22,784.37 using 1: 3 matching method in 2018. It had a highest level of differences at 47.78%, compared to the remaining matching methods and measures. The lowest level of differences was 0.87% for the additional medicine expenditure per TB hospitalized patient using 1: 2 matching method in the same year. Additionally, as indicated in Additional file 1 : Table S7, the results of Rosenbaum bounds for robust test showed that for different matching methods, the analyses on the additional direct economic disease burden for all measures were still robust to hidden biases.

Possible applications

First, the application of this framework could be applied in single hospitals at the local level. Results generated from this framework could be applied for internal hospital management, providing critical insights for hospital managers. These generated results directly help hospital managers clearly understand the specific areas at high risk for HAIs, enabling targeted interventions, such as enhanced hand hygiene protocols, environmental cleaning, and disinfection procedures, as well as improved sterilization of medical equipment. This data-driven approach allows for the refinement of IPC measures, including isolation protocols for infected patients and antimicrobial stewardship programs, thereby improving patient safety and reducing the incidence of HAIs. Besides, by quantifying the economic burden attributable to HAIs, hospital managers can better allocate resources to areas that yield the highest return on investment in terms of infection prevention and patient care. Besides, integration of this framework into HIS could enable dynamic tracking and monitoring of HAIs, facilitating timely interventions, such as outbreak response and continuous staff training on IPC practices. Particularly, if such framework could be implemented in an established alliance of hospitals, it is able to more effectively consolidate and share critical data, just as the function of real-time surveillance of existing HAIs systems [ 22 , 23 ]. Additionally, optimizing resources allocation and tailoring IPC measures could be significantly enhanced based on the insights provided by this framework, such as the deployment of rapid diagnostic tests and the use of personal protective equipment.

Second, the application of this framework could be applied at the regional and national levels. Results generated from this framework can also be used for hospital governance, particularly for benchmarking across multiple hospitals [ 24 , 25 ]. Benchmarking can enable hospitals to determine the most cost-effective IPC measures and share best practices by comparing their values. For example, if one of the compared hospitals exhibits a significantly lower direct economic disease burden attributable to HAIs compared to others, it can be identified as a model of best practice. Hospital managers and policy decision-makers can then figure out the measures or management mechanism formulated by the best practice, and promote them in a broader way to enhance healthcare outcomes. Such applications of benchmarking can improve patient safety and reduce the economic impact of HAIs, thereby benefiting the broader society. Additionally, results generated from this framework can be applied for inter-organizational learning [ 26 ]. Hospitals can use these results as basis of training or intervention programs to improve the awareness of infection control among health professionals. Health professionals can learn the latest updates about theory, methodology, and technology on controlling HAIs via regular workshops, training sessions, and feedback meetings, so that they can enhance their own capacity to implement relevant measures. This needs the involvement of third-party agencies to provide professional evaluation of hospital performance [ 27 ]. These agencies can perform regular monitoring, ensuring compliance with established IPC standards and effectiveness of implemented strategies.

Third, at the international level, the adaptability of this framework allows for its potential applications in other countries, especially in settings with limited resources. More empirical evidence and experience could be generated to help local hospitals enhance the efficiency of infection control strategies, thereby reducing the attributable medical expenditures and improving quality of health. Moreover, this framework can be continuously refined and adjusted through its application across various international countries, leading to advancements in global health standards and policies. This can also be implemented by non-profit organizations, such as WHO. This collaborative international approach could address the global challenge of HAIs effectively and enhance the resilience and responsiveness of health systems around the world, as supported by the WHO recent reports on global IPC initiatives [ 3 ].

Challenges to implement this framework

First, the challenge to implement this framework is quality of data extracted from hospitals. Data extraction is highly related to the HIS capabilities within each hospital, since data for different variables are sourced from different subsystems of the HIS. Inconsistencies in data management and integration across these subsystems can lead to inaccuracies that compromise the reliability of the framework. The variance in technological infrastructure between hospitals, especially in lower-resource settings, can pose significant challenges as well [ 28 ]. Moreover, not all hospitals are equipped with advanced HIS systems that can provide the detailed and accurate data necessary for effective application of the framework. This technological disparity can result in significant differences in data quality and accessibility, complicating the implementation process and potentially skewing results.

Second, the adoption of this framework in other countries need to navigate varying levels of regulatory compliance, data privacy standards, and government support. For instance, data protection regulations in some countries may restrict the types of data that can be collected and how it can be used, which may limit the framework’s applicability and effectiveness [ 29 ]. Cultural differences in the management and operation of hospitals can also influence the consistency and completeness of data collection. Training and capacity building are also crucial for successful implementation of this framework. Hospital staff need to be trained in how to use the system and in understanding the importance of accurate data entry. Without proper training and a clear understanding of the framework’s objectives, the risk of data entry errors increases, which could compromise data quality and the subsequent analyses.

Third, the special feature of TB may pose challenges to implement this framework. For example, since the medical expenditures for hospitalized patients with MDR-TB are usually significantly higher than those for hospitalized patients with single-drug-resistant TB (SDR-TB), when conducting the PSM analysis, the covariate should include the status whether a hospitalized patient has MDR-TB or SDR-TB. This ensures that the PSM analysis can accurately account for the medical expenditures associated with different types of TB resistance. Besides, for TB hospitalized patients, use of antibiotics is a common treatment. The intensity of antibiotics use, the type of antibiotics, and whether they are used reasonably can all be possible aspects to consider. Although in our systematic review, we identified several risk factors for HAIs, it is essential to continually consult relevant experts/doctors and review the latest literature to ensure that all significant TB-specific risk factors are included as covariates in the PSM analysis. Thus, the analysis can more precisely attribute the estimated direct economic disease burden solely to HAIs. This can be also applied to other communicable diseases or special diseases. While this case study only focused on the burden of direct medical expenditures, the burden of direct non-medical expenses, such as transportation, caregiver time, and lost income, is also significant. Future research should incorporate these non-medical costs to provide a more comprehensive assessment of the economic burden of HAIs. Patient surveys and cost diaries can be futher applied to capture these additional expenses.

Availability of data and materials

Data and materials are accessible upon the reasonable request to the research team.

Abbreviations

Antimicrobial resistance

Consumer Price Indices

Generalized Boosted Model

Healthcare-associated infections

High-income countries

Hospital information system

Infection and prevention control

Interquartile range

Low- and middle-income countries

Multi-drug-resistant tuberculosis

Propensity score

Propensity Score Matching

Standard deviations

Single-drug-resistant tuberculosis

Tuberculosis

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Acknowledgements

The authors thank Ms Jiaxin He (PhD student from Wuhan University) for her support in drawing the flow charts of the framework and participant selection.

This study was funded by the Wuhan City Medical Scientific Research Program (2021) (Grant Number: WG21D10) and China Academic Degrees and Graduate Education Development Center (2023) (Grant Number: ZT-231048623).

Author information

Nili Ren and Xinliang Liu have the same contributions to the manuscript and are co-first authors.

Authors and Affiliations

Wuhan Pulmonary Hospital/Wuhan Institute for Tuberculosis Control, No28 Baofengyilu Road, Wuhan, 430030, China

Nili Ren, Yi Luo, Guofei Li, Ying Huang, Desheng Ji & Cheng Peng

School of Public Health/Global Health Institute, Wuhan University, No. 115 Donghu Road, Wuhan, 430071, China

Xinliang Liu & Hao Li

Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Sciences Centre, Oxford Road, Manchester, M13 9PL, UK

Xinliang Liu

School of Health Policy and Management, Dongcheng District, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 9 Dongdan Santiao, Beijing, 100730, China

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Contributions

HL and JS conceptualized the framework and supervised the whole work. NR applied the ethics application. NR, YL, GL, YH, DJ, and CP extracted the data from the TB hospital. NR, XL, and DJ processed the data. NR and XL analyzed the data. All authors reviewed the final manuscript and agreed on the submission.

Corresponding authors

Correspondence to Jing Sun or Hao Li .

Ethics declarations

Ethics approval and consent to participate.

The ethics committee of the TB hospital approved this study [Wuhan Pulmonary Ethic Committee (2021) 28]. Anonymized data were adopted by replacing the original hospital number with the linkage between hospital number and sequence of admission. Information relevant to the personal information of TB hospitalized patients was removed from the hospital system. Therefore, informed and verbal consent was not required for patients hospitalized for TB in this study.

Consent for publication

All authors listed in this paper have read the manuscript and agreed to submit the manuscript for publication.

Competing interests

The authors declare that they have no competing interests. The co-first author, Xinliang Liu is Managing Editor , and the co-corresponding author, Hao Li is Editor in Chief from Global Health Research and Policy . Both of them were not involved in the review of decision related to this manuscript.

Supplementary Information

Additional file 1: table s1.

. Inclusion and exclusion criteria for TB hospitalized patients with and without HAIs. Table S2 . Description and assigned values of the potential risk factors associated with HAIs among TB hospitalized patients. Table S3 . Summaries of medical expenditures and hospitalization days among TB hospitalized patients with HAIs from 2018 to 2019. Table S4. Comparisons of covariates between TB hospitalized patients with and without HAIs before and after performing PSM. Table S5 . Rosenbaum bounds for robust test on the additional direct economic disease burden attributable to HAIs in 2018 and 2019. Table S6 . Sensitivity analysis using different matching methods in 2018 and 2019. Table S7. Rosenbaum bounds for robust test across different PSM matching methods in 2018 and 2019.

Additional file 2:

Codes for conducting univariate analysis in STATA software. Codes for conducting multiple logistic regression analysis in STATA software. Codes for performing PSM analysis in STATA software. Codes for conducting Wilcoxon matched-pairs signed-rank tests in STATA software. Codes for conducting Rosenbaum bounds for robust test in STATA software.

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Ren, N., Liu, X., Luo, Y. et al. Developing a framework for identifying risk factors and estimating direct economic disease burden attributable to healthcare-associated infections: a case study of a Chinese Tuberculosis hospital. glob health res policy 9 , 33 (2024). https://doi.org/10.1186/s41256-024-00375-w

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Received : 03 June 2024

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Published : 09 September 2024

DOI : https://doi.org/10.1186/s41256-024-00375-w

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Can mobile phones cause brain cancer new who-backed study explained.

Curated By : News Desk

Edited By: Shilpy Bisht

Last Updated: September 09, 2024, 17:10 IST

New Delhi, India

Not only did the review find no overall association between mobile phone use and cancer, it overruled any risk with prolonged use and frequency. (Getty Images)

Radio waves emitted by mobile phones and wireless technology don’t have enough energy to damage the body directly, as per a study commissioned by WHO and published in Environment International

A new study has debunked the myth that the electromagnetic radiation from mobile phones and wireless technologies can cause cancer. The radio waves wireless technologies transmit are very weak. They do not have enough energy to damage DNA and are unlikely to cause cancer, the study said.

The study is the largest review on the issue to date and was commissioned by the World Health Organization (WHO) and published in Environment International .

“For the main issue, mobile phones and brain cancers, we found no increased risk, even with 10+ years exposure and the maximum categories of call time or number of calls,” said Mark Elwood at the University of Auckland in New Zealand, who was a co-author in the study.

No Brain Cancer From Mobile Phones

“We concluded the evidence does not show a link between mobile phones and brain cancer or other head and neck cancers. Even though mobile phone use has skyrocketed, brain tumour rates have remained stable,” said lead author Ken Karipidis in a release. The systematic review, led by the Australian Radiation Protection and Nuclear Safety Agency (Arpansa), examined more than 5,000 studies on the subject.

The evidence is clear that the radio waves emitted by mobile phones and wireless technology don’t have enough energy to damage the body directly. So far, no studies have found links between mobile phone use and cancer, so it can be “confidently” said that wireless technologies do not cause cancer.

How Do Mobile Phones Work?

Mobile phones exchange signals using radiofrequency (RF) waves. This is a form of energy in the electromagnetic spectrum, which is why mobile phones are said to give off electromagnetic radiation.

Radiofrequency waves used by mobile phone networks are a form of non-ionising radiation. Non-ionising radiation uses tiny amounts of energy to transmit data, nowhere near enough energy to damage the human body or DNA (genes).

Although all 4G, 5G, Wi-fi and Bluetooth rely on radio waves for transmitting data, but none have enough energy to heat body tissues or damage cells or DNA, the study pointed out.

In fact, the radiofrequency waves are different from ionizing radiations used in X-rays, gamma rays and ultraviolet rays. Thus, high levels of sun exposure can cause skin cancers.

India has over 1.2 billion mobile phone users, and 600 smartphone users. The number is expected to reach 1.55 billion in the smartphone category.

Why is the Study Significant?

The WHO’s International Agency for Research on Cancer (IARC) had designated radio frequency and electromagnetic fields as a possible carcinogen in 2011. The study was largely based on positive associations seen in case-control studies, which might have been biased based on what the participants recalled, the new analysis said.

Not only did the review find no overall association between mobile phone use and cancer, it overruled any risk with prolonged use (for those using their mobile phones for 10 years or more) and frequency (the number of calls made or the time spent per call).

The study, which stemmed from concerns that phones held against the head emit radio waves into the brain, analysed more than 5,000 studies, focusing on 63 studies from 22 countries most relevant for their analysis.

“For this report, cancers of the brain (three types, and in children), pituitary gland, salivary glands, and leukemias were included,” said Elwood, as quoted by Deutsche Welle .

What are Experts Saying?

AIIMS oncologist Dr Abhishek Shankar said mobile phone usage was never really thought of as a preventive strategy for cancer. “The radiation from cell phones is non-ionising — the ones that don’t cause cancer. The radiation from say an X-ray machine, on the other hand, is ionising and can cause cancer. Ionising radiation has enough energy to break chemical bonds, remove electrons from atoms like in nuclear power plants and damage cells in organic matter,” The Indian Express quoted Dr Shankar as saying.

Dr Shankar, like many experts, recommends preventive screening and limiting risk factors like smoking. He also recommends limiting the use of mobile phones, which can still lead to headaches, anxiety and hearing loss.

What Did the Previous Research Say?

Many studies on mobile phone use and cancer have been done over the past three decades. The FDA regularly monitors studies and statistics involving the issue. Some of the more recognised studies include:

COSMOS Study : The Cohort Study on Mobile Phones and Health (COSMOS) published in 2024 includes data involving more than 250,000 users of mobile phones, many of whom had 15 or more years of regular mobile phone use. It found participants did not have a higher risk of developing a brain tumor compared with light users of mobile phones.

INTERPHONE Study : Researchers from 13 countries looked at mobile phone use in more than 5,000 people who got brain tumors and a similar group without brain tumors. Overall, no link was found between the risk of brain tumors and mobile phones, how often calls were made, longer call times. The researchers did find a small increase in the risk of a certain type of brain tumor in the 10% of people who used their cell phones the most.

2019 Analysis : Looking at the results of multiple studies, researchers found no suggestion that mobile phone use led to a higher risk of tumors of the brain or salivary gland (in the jaw). But they were not certain whether the risk might go up 15 or more years later. They also were not sure whether children who use mobile phones might have a higher risk of these tumors later on.

50-year Review : A review of 22 studies done between 1966 and 2016 suggested that people who had used cell phones for 10 years or longer had a higher risk of brain tumors.

2018 Trend Research : Australian researchers compared mobile phone use with brain tumor trends over three different decade-long periods. They found no link between brain tumors and cell phones.

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Status and challenges for tuberculosis control in India – Stakeholders' perspective

Gargi thakur.

a DAV Public School, Airoli, Navi Mumbai, India

Shalvi Thakur

b Indian Institute of Science, Education and Research, Bhopal, India

Harshad Thakur

c School of Health Systems Studies, Tata Institute of Social Sciences, Mumbai, India

d National Institute of Health and Family Welfare, New Delhi, India

Tuberculosis is one of the ten major causes of mortality worldwide. The trend of increasing TB cases and drug resistance in India is very disturbing. The objectives of the study were to study the perspectives and opinions of different stakeholders on the status, challenges and the ways to tackle the issues of TB in India.

The online survey was done for the data collection from national and international experts. The data collection took place during October 2017. We received 46 responses.

The experts had varied answers as to the menace of TB in India, effect of TB on individuals, family and society, failure of government plans in India, TB awareness campaign and ways to create awareness. Everyone believed that urgent action needs to be taken against the disease like improving the healthcare infrastructure of the country (improving the quality and quantity of medical facilities and doctors) and creating awareness about the TB.

Government of India is making lot of efforts to bring down the problems associated with TB through. In spite of this, there is a long way to go to achieve significant reduction in high incidence and prevalence of TB in India. Factors like lack of awareness and resources, poor infrastructure, increasing drug resistant cases, poor notification and overall negligence are the major challenges. If we eradicate poverty and undernourishment, educate the masses and eliminate the stigma attached with TB, we can hope for a disease free future.

• Tuberculosis is one of the ten major causes of mortality worldwide.
• Many government plans have failed in bringing down the high incidence and prevalence of TB in India.
• Major challenges: Lack of awareness, poor infrastructure, drug resistance, poor notification and overall negligence.
• Eradication of poverty and undernourishment, education of people and elimination of stigma are must for a TB free future.
• Current Covid-19 has given us an excellent opportunity to create awareness about TB in the community at various levels.

1. Introduction

Tuberculosis (TB), one of the most ancient diseases of mankind, is one of the ten major causes of mortality worldwide. 1 It is an infectious disease caused by bacteria Mycobacterium tuberculosis . It usually affects lungs (Pulmonary TB) but can also affect other organs of the body. Pulmonary TB is an air borne disease. TB can be diagnosed by chest X-ray, sputum and other tests. Combinations of antibiotics are given for more than 6 months as a treatment. Vaccination with BCG (Bacille-Calmette-Guerin), early diagnosis and detection, proper and complete treatment, awareness, etc. can lower the burden of TB.

Poor socioeconomic status and living conditions are considered as strong risk factors linked with Latent Tuberculosis Infection in addition to malnourishment. 2 BCG is the vaccine commonly available against TB. It does offer some protection against serious forms of TB in childhood but its protective effect wanes with age. 1 Latent TB is also becoming a major issue in ageing population.

All countries and age groups are affected by TB but most cases (90%) in 2016 were in adults. Almost two-third was accounted for by eight developing countries with India contributing 27% of 10.4 million cases. 3 , 4 In 2017, only 64% of the global estimated incident cases of TB were reported, the remaining 36% of ‘missing’ cases was undiagnosed, untreated or unreported. These ‘missing TB cases' have generated much hype for the challenges they present in achieving the End TB Strategy. 5 Many people with TB (or TB symptoms) do not have access to adequate initial diagnosis. In many countries, TB diagnosis is still reliant on sputum microscopy, a test with known limitations. 6

Wide spread misuse of anti-tubercular drugs has also resulted in emergence of drug resistant TB including Multi Drug Resistant TB (MDR-TB) and Extensively Drug Resistant TB (XDR-TB) globally. India has the highest incidence of new and MDR-TB cases in the world. It is difficult to diagnose MDR-TB and XDR-TB as compared to regular TB. 7 , 8 TB treatment default, missing medical appointments for two consecutive months or more, is a serious problem not only for individuals but also for societies and health-care systems. 9 An increasing burden of MDR-TB patients, especially in the young population with increased risk of transmission posing a major challenge in achieving TB elimination targets. 10 In India, major challenges to control TB include poor primary health-care infrastructure in rural areas of many states, unregulated private health care, lack of political will and corrupt administration. WHO with its “STOP TB” strategy has given a vision to eliminate TB as a public health problem from the face of this earth by 2050. 11

Since 2000, there has seen the emergence of new diagnostics and drugs for TB. A new and potent drugs such as Bedaquiline, Delamanid, Teixobactin have been evolved which may serve as a nice step forward, with a better outcome. 12 However, these are yet to reach community, and access remains a major challenge for patients in low and middle income countries. 13

The National Strategic Plan (2017–25) of India proposes bold strategies with commensurate resources to rapidly decline TB in the country by 2030. This is in line with the Global End TB targets and Sustainable Development Goals to attain the vision of a TB free India. The goal is to achieve a rapid decline in burden of TB, morbidity and mortality while working towards elimination of TB in India by 2025. 14 India achieved the MDG targets of reducing the prevalence by half in 2015. In spite of this the trend of increasing TB cases and drug resistance in India is very disturbing. After collecting preliminary secondary information from the internet, journals, etc. about the disease, it was felt that there is a need to compile opinions of different stakeholders working in the healthcare field especially related to status and challenges of TB in India.

The objectives of the study were to study the perspectives and opinions of different stakeholders on the status, challenges and the ways to tackle the issues of TB in India. We decided to contact the clinicians, policy implementers and academic researchers as they play a pivotal role in controlling and preventing the disease. These stakeholders are also pioneers in reducing TB burden in India and their opinions will be useful in developing effective strategies.

A questionnaire for the survey was prepared and later on data was collected using available modern technology. The questionnaire was created on the online platform of www.surveymonkey.com . This online questionnaire made it easy for the survey to reach national and international experts. Social media (like email, Facebook, WhatsApp, etc) was utilized to send survey all across the world. The survey link ( https://www.surveymonkey.com/r/H67S3YV ) was sent to more than 1000 national as well as international experts and doctors working in diverse medical fields related to TB (academicians, researchers, clinicians, policymakers, implementers, etc). The online survey fulfilled the purpose of reaching out to many experts with variety of expertise like with the help of limited resources.

The data collection took place during October 2017. The responses were collected over the period of next 7–10 days. A semi-structured interview schedule was used comprising nine questions and mainly focusing on the effects of TB on society, the opinions of experts regarding what they felt was lacking in the country's efforts to reduce TB prevalence and the ways of creating more and better awareness about TB. The consent of each respondent was taken and the confidentiality was maintained as we did not ask them for their personal information.

The data was analyzed manually using MS Excel software. Data analysis largely followed the framework approach. The answers were entered in the worksheet. Data was coded, indexed and charted systematically to seek meaning from all of the data that was available. The data was categorized and sorted into patterns as the primary basis for organizing and reporting the study findings.

We received 46 responses. The respondents consisted of people from all age groups ranging from 24 years to 68 years and belonged to categories like Clinicians, Policy makers/implementers, Academic Researchers and others. Table 1 presents number of people belonging to various categories.

The category of respondents.

Categories	No. of people
Clinician	12
Policy maker/implementer	9
Academician	12
Researcher	8
Other	5

Out of the 46 respondents, two were distinguished professors and academic researchers from USA. Three were from The World Health Organization (WHO) – Chief Medical Officer (TB) from an Asian country and two Medical Consultants from WHO–RNTCP (Revised National TB Control Program) India. The response was received from experts and specialists belonging to the Municipal Corporation of Greater Mumbai hospitals, District Health Officers, National Health Mission, The United Nations Children's Fund (UNICEF) and various other national and international organizations working actively in India. Apart from this, others were from diverse fields such as Neurologist, Laryngologist, Obstetrician and Gynecologists, Pathologists, Medical Students, PhD students, etc. from various reputed institutions like King's College (London), Holy Spirit Hospital, Bombay Hospital, Jaslok Hospital, Breach Candy Hospital, SRCC NH Children's Hospital, Wadia Children Hospital and so on.

The experts had varied answers as to the menace of TB in India, effect of TB on individuals, family and society, failure of government plans in India, TB awareness campaign and ways to create awareness. The perspectives of policy makers, implementers and clinicians differed from that of the academicians and researchers but they also converged at a lot of points.

The respondents gave various perspectives to answer what made TB a menace all over the country. They mentioned social reasons like overcrowding, urbanization leading to congested cities, social problems like smoking and alcoholism, poor living conditions, unhygienic habits and poor nutrition are the major causes. On the other hand, few respondents stated that there are concerns related to health systems and services and said that poor public health conditions, lack of awareness about the TB amongst the masses, lack of universal access to healthcare, private sector malpractices, poor implementation of government health programs and poor drug supplies are the major problems. Few cited drug resistance as the cause of TB becoming a menace.

Effects of TB could be felt at individual, family, society and country level. Immunity of the person contracted with TB reduces which makes him/her susceptible to other diseases as well and reduces life expectancy. According to the respondents, the main effect of TB on the family was loss of income of the family due to which the family is slipped into poverty and their quality of life is affected. If the sole breadwinner of the family contracts the disease, then the family loses its only source of income and is forced to spend all its meager monetary resources on the treatment of the person. The family of the infected person also is at a high risk of contracting the contagious disease. Also, the social stigma attached to the disease can't be ignored. The effect of TB on society and country is such that it affects the National Economy at the macro level mainly due to decreased workforce. This leads to lower per capita income and a lower GDP.

According to the experts, the TB eradication programme of government has failed because of inadequate budgetary allocation to the programs, lack of proper infrastructure and manpower and poor implementation of programs. The various policies of the government fail to address the root cause of the problem. Also, the corruption in the healthcare system is hindering the policies from reaching the population. The Government policies need proper management. The TB program of the government will sink or swim with the Primary health program. Unless Primary Healthcare is improved and the problem of malnutrition is addressed, the program will fail to make any difference.

The experts say that each and every person in the country needs TB awareness and no section of the population must be exempted. But they feel that a special emphasis must be given on the poor and the marginalized sections of the society as these sections survive in poor and congested living conditions and the rate of malnutrition is high among them. The respondents feel that for the TB Awareness Campaign to reach every nook and corner of the country, innovative and creative methods have to be used so that the campaign catches everyone's attention. Use of mass media and social media will help in reaching the whole country. The use of local language for promoting the campaign will help in reaching out to the remotest places of India. The Awareness Campaign needs to be promoted by a celebrity or a famous personality so that people respond to the campaign. Also, awareness workshops should be held in schools and colleges so that the young generation is well informed about the disease. As one respondent mentioned, “The government should start an educational series on TB along the lines of “Mann ki Baat” by the Prime Minister of India.”

The additional efforts required to reduce the menace of TB include improving the overall scenario of public and primary healthcare in India. Universal access to healthcare and treating MDR-TB efficiently can substantially reduce the prevalence of TB. Improving the general health facilities, improved standard of living conditions, proper nutrition are some of the ways to tackle this deadly disease. Access to free or cheaper drugs and treatment, usage of quicker and more accurate diagnosis technology, involving private sector in the management of the TB Program will help to improve the existing infrastructure and healthcare services. These are some of the measures which will help tackle the problem of TB in the long run.

Finally, all the experts believe that urgent action needs to be taken against the disease. Improving the healthcare infrastructure of the country (improving the quality and quantity of medical facilities and doctors) should be the main motto the Government. Awareness and mass education about the various killer diseases is the need of the hour. TB is just like any other communicable disease. It needs to be tackled in a rational and scientific way. This is possible only if the whole country takes part in the campaign against TB menace.

4. Discussion

TB along with Acquired Immune Deficiency Syndrome (AIDS) and malaria rank among the top three fatal infectious diseases which pose threat to global public health, especially in middle and low income countries. 15 Asia has the highest burden of TB in the world. Optimizing the diagnosis and treatment of TB is one of the key strategies for achieving the WHO ‘End TB’ targets. 16 Majority of TB cases of resource-poor settings experience food insecurity, which impacts treatment adherence and outcomes. Additional food or cash assistance for this subgroup might improve food insecurity and thereby nutritional status. 17 But again, this is a temporary measure. The root causes of TB, like poverty, poor socio-economic conditions, and improper hygienic practices are still neglected. Most of the developed countries have eliminated diseases like TB before the advent of anti-tubercular drugs through socio-economic improvement. India is earmarking funding for prevention and control of TB, but it is still mainly for diagnosis and treatment and not for primary prevention.

A significant proportion of the general population has incomplete knowledge on the routes of the spread of TB infection. Social stigma, such as reluctance to disclose about a family member being infected with the disease to others, also remains high. Imminent need for appropriate policy mechanisms for involving the private sector and raising consciousness through suitable advocacy measures is re-emphasized. 18 Quality of TB care is suboptimal and must urgently be addressed; merely focusing on coverage of TB services is no longer sufficient. While the world awaits revolutionary vaccines, drugs and diagnostics, programmatic data indicate that much can be done to accelerate the decline of TB. 5 Efforts are also being made to understand the genetic/molecular basis of target drug delivery and mechanisms of drug resistance. 19

TB during childhood is also quite under diagnosed and under reported in India. Increased detection of childhood TB cases is essential to control TB in general population. 20 Social determinants like overcrowding, lack of awareness and knowledge about TB, and malnutrition have to be tackled in order to combat TB. There is urgent need for advocating educational activities among the patients and the more vulnerable population about the cause, transmission, preventive measures, duration and dosage of therapy of TB with the help of DOTS providers and apt IEC (Information Education and Communication) materials. Very few patients i.e., only 3 lakh out of estimated 15 lakh are notified by private sector making the issue underrated. 21 The current National Strategic Plan for TB Elimination (NSP 2017–25) has been worked out to provide nutrition support and reduce out of pocket expenditure of the patients and is aimed at ending TB by 2025. 14 , 22

Successful control of TB globally will depend on strengthening TB control programs, wider access to rapid diagnosis and provision of effective treatment. Therefore, political and fund provider commitment is essential to curb the spread of TB. 7 There is a pressing need for systematic monitoring of ongoing TB treatment in the private sector: both to cast light on the true scale of the problem, and to help monitor the progress of interventions currently being planned to address this problem. 23 While transformative tools are being developed, high-burden countries like India will need to improve the efficiency of their health care delivery systems and ensure better uptake of new technologies. National TB programs must scale up the best diagnostics currently available, and use implementation science to get the maximum impact. 6 It has been shown that Active Case Finding (ACF) as compared to Passive case finding significantly averts catastrophic costs due to TB among patients. ACF as a strategy could ensure financial protection of TB patients and limit their risk of poverty. 24 In addition, TB elimination efforts need to focus on all forms of TB, including Extra Pulmonary TB, leaving no one behind, in order to realise the dream of ending TB. 25

The End TB Strategy by WHO envisions a world free of tuberculosis by 2035. This requires reducing the global tuberculosis incidence from >125 cases per lakh people to <10 cases per lakh people within the next 15 years, which is quite a herculean task. Expanding testing and treatment of tuberculosis infection is critical to achieving this goal. India will require cost-effective and sustainable interventions aimed at tuberculosis. 26 The WHO End TB Strategy also calls for a global reduction in the case fatality ratio below 5%. India accounts for a third of global TB deaths. Case fatality is a critical measure of the quality of TB care. Increased high-quality reporting on patient outcomes will help improve the evidence base on this topic. 27

The foundation of end TB strategy includes integrated patient centric care and prevention, bold policies, supportive statement, intensified research and innovation which requires engaging a wide range of collaborators across government, communities and private sector. 28 India needs to sustain the existing DOTS based program while introducing new components including services to address TB/HIV, treatment for MDR-TB, strengthening laboratory services and integrating TB services in both public and private healthcare sectors. Fig. 1 summarizes the strategies given by all the stakeholders/experts to Fight and End TB in India. The effectiveness of the program can be increased with focused efforts undertaken by Government of India in strengthening the primary healthcare system under National Health Mission through careful planning, thorough implementation, stable funding and innovations.

Experts' opinion on fight TB in India.

In India, TB is still one of the most commonly prevalent diseases as far as both morbidity and mortality is concerned. The incidence is quite high but it is only the tip of the iceberg. There are many missed cases either due to non-reporting by private sector or due to misdiagnosis. The next issue is inadequate and improper treatment of identified cases leading to increasing burden of drug resistant TB. Availability and affordability of sound diagnostic technology which helps in early diagnosis of TB cases (both non DR-TB and DR-TB cases) is missing from many parts of country. TB has a tremendous effect at individual, family and community level. This way it even affects the economy of a country. Also it is still neglected as India is more concentrating towards other conditions like Non Communicable Diseases and other emerging health issues.

5. Conclusion

Government of India is making lot of efforts to bring down the problems associated with TB through revised plans and their implementation across the country. In spite of this, there is a long way to go to achieve significant reduction in high incidence and prevalence of TB in India. Factors like lack of awareness and resources, poor infrastructure, increasing drug resistant cases (MDR TB and XDR TB), poor notification and overall negligence are the major challenges. Contagious disease like TB can victimize anyone. Even vaccinations do little to reduce its impact. If we eradicate poverty and undernourishment, educate the masses and eliminate the stigma attached with TB, we can hope for a disease free future. The current Coronavirus pandemic in 2020 has also given us excellent opportunity to create awareness about TB in the community at various levels.

Conflicts of interest

The authors have none to declare.

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New Delhi, Sep 7 (PTI) Underlining critical occupation risks in the health sector, a new study has found that cases of tuberculosis are a lot more prevalent among healthcare workers in India in comparison to the general population.

The analysis of 10 separate studies conducted in the last two decades between 2004 and 2023 found an average prevalence of 2,391.6 cases per 1,00,000 healthcare workers in India, far higher than the rate of 300 cases per 1 lakh population.

The study, titled “Prevalence of Tuberculosis Among Healthcare Workers in India: A Systematic Review and Meta-Analysis,” is a collaborative effort by Dr Ravindra Nath from Teerthanker Mahaveer University, Moradabad, along with Dr Jugal Kishore, Dr Pranav Ish, Dr Aninda Debnath, and Dr Nitin Panwar, from VMMC and Safdarjung Hospital, and Dr Anirban Bhaumik from Dr Baba Saheb Ambedkar Medical College and Hospital, Delhi.

Tuberculosis (TB) remains one of the most critical public health challenges globally, particularly in countries with high endemic rates such as India, which alone accounts for approximately one-fourth of the global TB burden, the study said.

This infectious disease, caused by Mycobacterium tuberculosis, is predominantly spread through airborne particles, making it a significant occupational hazard, especially in healthcare settings.

The incidence of TB among healthcare workers (HCWs) is alarmingly high, reflecting broader systemic vulnerabilities within healthcare infrastructures.

The frequency of exposure to the pathogen is often compounded by the presence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB strains. These strains not only complicate treatment but also highlight the critical need for stringent infection control measures in healthcare facilities.

Studies have indicated that TB incidence rates in HCWs are three times higher than those observed in the general population.

Despite the acknowledged risks, comprehensive epidemiological data on TB among HCWs in India is sparse and often inconsistent, Dr Jugal Kishore, Director and Professor in the Department of Community Medicine at Safdarjung Hospital highlighted.

The analysis, which reviewed ten studies conducted between 2004 and 2023, identified particularly high TB prevalence rates among laboratory technicians (6,468.31 cases per 100,000), doctors (2,006.18 per 100,000), and nurses (2,726.83 per 100,000).

This data points to significant occupational hazards that are often overlooked in the healthcare sector, Dr Kishore said.

The study’s findings highlighted several factors contributing to the high TB rates among HCWs. These include inadequate ventilation and underlying poor air circulation in healthcare facilities significantly increasing the risk of airborne transmission of TB.

Also, despite the high risks, many HCWs do not consistently use PPE, such as N95 masks, particularly in high-exposure areas, the study pointed out.

HCWs frequently encounter patients with multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB, further complicating their occupational risks.

Given these findings, the authors strongly recommend immediate action to protect HCWs which includes ensuring consistent use of PPE and other infection control measures in all healthcare settings.

They also stressed routine TB screening for all HCWs, especially those in high-risk roles, to facilitate early intervention and reduce transmission besides, holding ongoing training programs to raise awareness about TB risks and the importance of preventive practices.

They also called for investing in better ventilation systems and dedicated isolation rooms to reduce the spread of TB in healthcare environments and providing access to adequate nutrition, mental health services, and support for managing work-related stress, which is crucial for reducing vulnerability to TB.

The authors have advocated for the development and implementation of national guidelines for routine TB screening and surveillance among HCWs.

These guidelines should focus on high-risk groups such as medical trainees and those working in high-exposure departments. Moreover, there is an urgent need for mandatory infection control training programs and investment in healthcare infrastructure to create safer work environments.

“As India strives to eliminate TB by 2025, this study serves as a stark reminder that protecting our healthcare workers is essential to achieving this goal. The findings not only highlight the occupational risks faced by HCWs but also call for a collective effort to “Save the Saviours” who dedicate their lives to caring for others,” Dr Kishore said. PTI PLB HIG HIG

This report is auto-generated from PTI news service. ThePrint holds no responsibility for its content.

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