Process evaluation of a complex, multilevel, multicomponent scheme for the prevention and control of non-communicable diseases in Tamil Nadu, India: A mixed-methods protocol.

Background: Non-communicable diseases (NCDs) are the leading cause of morbidity and mortality in India, necessitating development of multilevel and multicomponent interventions. Makkalai Thedi Maruthuvam (MTM) is a complex multilevel, multicomponent intervention developed and implemented by the south Indian State of Tamil Nadu. The scheme aims to deliver services for preventing and controlling diabetes, and hypertension at doorstep. This paper describes the protocol for planning and conducting the process evaluation of the MTM scheme. Methods and analysis: The process evaluation uses mixed methods (secondary data analysis, key informant interviews, in-depth interviews, conceptual content analysis of documents, facility-based survey and non-participant observation) to evaluate the implementation of the MTM scheme. The broad evaluation questions addressed the fidelity, contexts, mechanisms of impact and challenges encountered by the scheme using the Consolidated Framework for Implementation Research (CFIR) framework. The specific evaluation questions addressed selected inputs and processes identified as critical to implementation by the stakeholders. The CFIR framework will guide the thematic analysis of the qualitative interviews to explore the adaptations and deviations introduced during implementation in various contexts. The quantitative data on the indicators developed for the specific evaluation questions will be cleaned and descriptively analysed.

Face mask use in the city of Chennai, India: Results from three serial cross-sectional surveys, 2021.

INTRODUCTION: The Government of Tamil Nadu, India, mandated wearing face masks in public places to combat the COVID-19 pandemic. We established face mask surveillance and estimated the prevalence of appropriate mask use (covering the nose, mouth, and chin) in the slums and non-slums of Chennai at different time points in 2021. METHODS: We conducted three serial cross-sectional surveys in the outdoors and indoors of Chennai in March, July, and October 2021. We observed the mask wearing among 3200 individuals in the outdoors and 1280 in the indoors. We divided the outdoor and indoor locations into slums and non-slums. In October 2021, we also surveyed 150 individuals from each of the 11 shopping malls in the city. We calculated the proportions and 95% confidence interval (95%CI) for the appropriate mask use in the outdoor, indoor, and malls by age, gender, region, and setting (slum and non-slum). RESULTS: We observed 3200 individuals in the outdoor and 1280 individuals in the indoor setting, each from a slum and non-slum, during the three rounds of the study. In outdoor and indoors, males comprised three-fourths and middle-aged individuals were half the study population. Mask compliance changed significantly with time (p-value <0.001). Males consistently demonstrated better compliance in all rounds. The south region had the highest mask compliance in slums indoors and outdoors in rounds 4 and 5. Young adults had the highest mask compliance in both outdoor slums and non-slums in all rounds. Overall mask compliance in shopping malls was 57% (95% CI: 48-65). CONCLUSION: The mask compliance in Chennai outdoors during the COVID-19 pandemic was less than 50%, with variations across time points by gender, age groups, and geographical locations. We must develop more effective communication strategies for older age groups and crowded indoor settings.

Direct benefit transfer for nutritional support of patients with TB in India-analysis of national TB program data of 3.7 million patients, 2018-2022.

BACKGROUND: Patients with TB have additional nutritional requirements and thus additional costs to the household. Ni-kshay Poshan Yojana(NPY) is a Direct Benefit Transfer (DBT) scheme under the National Tuberculosis Elimination Programme(NTEP) in India which offers INR 500 monthly to all notified patients with TB for nutritional support during the period of anti-TB treatment. Five years after its implementation, we conducted the first nationwide evaluation of NPY. METHODS: In our retrospective cohort study using programmatic data of patients notified with TB in nine randomly selected Indian states between 2018 and 2022, we estimated the proportion of patients who received at least one NPY instalment and the median time to receive the first instalment. We determined the factors associated (i) with non-receipt of NPY using a generalised linear model with Poisson family and log link and (ii) with time taken to receive first NPY benefit in 2022 using quantile regression at 50th percentile. RESULTS: Overall, 3,712,551 patients were notified between 2018 and 2022. During this period, the proportion who received at least one NPY instalment had increased from 56.9% to 76.1%. Non-receipt was significantly higher among patients notified by private sector (aRR 2.10;2.08,2.12), reactive for HIV (aRR 1.69;1.64,1.74) and with missing/undetermined diabetic status (aRR 2.02;1.98,2.05). The median(IQR) time to receive the first instalment had reduced from 200(109,331) days in 2018 to 91(51,149) days in 2022. Patients from private sector(106.9;106.3,107.4days), those with HIV-reactive (103.7;101.8,105.7days), DRTB(104.6;102.6,106.7days) and missing/undetermined diabetic status (115.3;114,116.6days) experienced longer delays. CONCLUSIONS: The coverage of NPY among patients with TB had increased and the time to receipt of benefit had halved in the past five years. Three-fourths of the patients received at least one NPY instalment, more than half of whom had waited over three months to receive the first instalment. NTEP has to focus on timely transfer of benefits to enable patients to meet their additional nutritional demands, experience treatment success and avoid catastrophic expenditure.

Protocol for establishing a model for integrated influenza surveillance in Tamil Nadu, India.

The potential for influenza viruses to cause public health emergencies is great. The World Health Organisation (WHO) in 2005 concluded that the world was unprepared to respond to an influenza pandemic. Available surveillance guidelines for pandemic influenza lack the specificity that would enable many countries to establish operational surveillance plans. A well-designed epidemiological and virological surveillance is required to strengthen a country's capacity for seasonal, novel, and pandemic influenza detection and prevention. Here, we describe the protocol to establish a novel mechanism for influenza and SARS-CoV-2 surveillance in the four identified districts of Tamil Nadu, India. This project will be carried out as an implementation research. Each district will identify one medical college and two primary health centres (PHCs) as sentinel sites for collecting severe acute respiratory infections (SARI) and influenza like illness (ILI) related information, respectively. For virological testing, 15 ILI and 10 SARI cases will be sampled and tested for influenza A, influenza B, and SARS-CoV-2 every week. Situation analysis using the WHO situation analysis tool will be done to identify the gaps and needs in the existing surveillance systems. Training for staff involved in disease surveillance will be given periodically. To enhance the reporting of ILI/SARI for sentinel surveillance, trained project staff will collect information from all ILI/SARI patients attending the sentinel sites using pre-tested tools. Using time, place, and person analysis, alerts for abnormal increases in cases will be generated and communicated to health authorities to initiate response activities. Advanced epidemiological analysis will be used to model influenza trends over time. Integrating virological and epidemiological surveillance data with advanced analysis and timely communication can enhance local preparedness for public health emergencies. Good quality surveillance data will facilitate an understanding outbreak severity and disease seasonality. Real-time data will help provide early warning signals for prevention and control of influenza and COVID-19 outbreaks. The implementation strategies found to be effective in this project can be scaled up to other parts of the country for replication and integration.

Quality of active case-finding for tuberculosis in India: a national level secondary data analysis.

BACKGROUND: India has been implementing active case-finding (ACF) for TB among marginalised and vulnerable (high-risk) populations since 2017. The effectiveness of ACF cycle(s) is dependent on the use of appropriate screening and diagnostic tools and meeting quality indicators. OBJECTIVES: To determine the number of ACF cycles implemented in 2021 at national, state (n = 36) and district (n = 768) level and quality indicators for the first ACF cycle. METHODS: In this descriptive study, aggregate TB program data for each ACF activity that was extracted was further aggregated against each ACF cycle at the district level in 2021. One ACF cycle was the period identified to cover all the high-risk populations in the district. Three TB ACF quality indicators were calculated: percentage population screened (≥10%), percentage tested among screened (≥4.8%) and percentage diagnosed among tested (≥5%). We also calculated the number needed to screen (NNS) for diagnosing one person with TB (≤1538). RESULTS: Of 768 TB districts, ACF data for 111 were not available. Of the remaining 657 districts, 642 (98%) implemented one, and 15 implemented two to three ACF cycles. None of the districts or states met all three TB ACF quality indicators' cut-offs. At the national level, for the first ACF cycle, 9.3% of the population were screened, 1% of the screened were tested and 3.7% of the tested were diagnosed. The NNS was 2824: acceptable (≤1538) in institutional facilities and poor for population-based groups. Data were not consistently available to calculate the percentage of i) high-risk population covered, ii) presumptive TB among screened and iii) tested among presumptive. CONCLUSION: In 2021, India implemented one ACF cycle with sub-optimal ACF quality indicators. Reducing the losses between screening and testing, improving data quality and sensitising stakeholders regarding the importance of meeting all ACF quality indicators are recommended.

The First Differentiated TB Care Model From India: Delays and Predictors of Losses in the Care Cascade.

To reduce TB deaths in resource-limited settings, a differentiated care strategy can be used to triage patients with high risk of severe illness (i.e., those with very severe undernutrition, respiratory insufficiency, or inability to stand without support) at diagnosis and refer them for comprehensive assessment and inpatient care. Globally, there are few examples of implementing this type of strategy in routine program settings. Beginning in April 2022, the Indian state of Tamil Nadu implemented a differentiated care strategy called Tamil Nadu-Kasanoi Erappila Thittam (TN-KET) for all adults aged 15 years and older with drug-susceptible TB notified by public facilities. Before evaluating the impact on TB deaths, we sought to understand the retention and delays in the care cascade as well as predictors of losses. During April-June 2022, 14,961 TB patients were notified and 11,599 (78%) were triaged. Of those triaged, 1,509 (13%) were at high risk of severe illness; of these, 1,128 (75%) were comprehensively assessed at a nodal inpatient care facility. Of 993 confirmed as severely ill, 909 (92%) were admitted, with 8% unfavorable admission outcomes (4% deaths). Median admission duration was 4 days. From diagnosis, the median delay in triaging and admission of severely ill patients was 1 day each. Likelihood of triaging decreased for people with extrapulmonary TB, those diagnosed in high-notification districts or teaching hospitals, and those transferred out of district. Predictors of not being comprehensively assessed included: aged 25-34 years, able to stand without support, and diagnosis at a primary or secondary-level facility. Inability to stand without support was a predictor of unfavorable admission outcomes. To conclude, the first quarter of implementation suggests that TN-KET was feasible to implement but could be improved by addressing predictors of losses in the care cascade and increasing admission duration.

--Eleven tips for operational researchers working with health programmes: our experience based on implementing differentiated tuberculosis care in south India.

Due to the workload and lack of a critical mass of trained operational researchers within their ranks, health systems and programmes may not be able to dedicate sufficient time to conducting operational research (OR). Hence, they may need the technical support of operational researchers from research/academic organisations. Additionally, there is a knowledge gap regarding implementing differentiated tuberculosis (TB) care in programme settings. In this 'how we did it' paper, we share our experience of implementing a differentiated TB care model along with an inbuilt OR component in Tamil Nadu, a southern state in India. This was a health system initiative through a collaboration of the State TB cell with the Indian Council of Medical Research institutes and the World Health Organisation country office in India. The learnings are in the form of eleven tips: four broad principles (OR on priority areas and make it a health system initiative, implement simple and holistic ideas, embed OR within routine programme settings, aim for long-term engagement), four related to strategic planning (big team of investigators, joint leadership, decentralised decision-making, working in advance) and three about implementation planning (conducting pilots, smart use of e-tools and operational research publications at frequent intervals). These may act as a guide for other Indian states, high TB burden countries that want to implement differentiated care, and for operational researchers in providing technical assistance for strengthening implementation and conducting OR in health systems and programmes (TB or other health programmes). Following these tips may increase the chances of i) an enriching engagement, ii) policy/practice change, and iii) sustainable implementation.