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Abstract Background Ni-kshay Poshan Yojana (NPY) is a direct benefit transfer scheme of the Government of India introduced in 2018 to support the additional nutritional requirements of persons with TB (PwTB). Our recent nationwide evaluation of implementation and utilization of NPY using programmatic data of PwTB from nine randomly selected Indian states, reported a 70% coverage and high median delay in benefit credit. We undertook a qualitative study between January and July 2023, to understand the detailed implementation process of NPY and explore the enablers and barriers to effective implementation and utilization of the NPY scheme. Methods We followed a grounded theory approach to inductively develop theoretical explanations for social phenomena through data generated from multiple sources. We conducted 36 in-depth interviews of national, district and field-level staff of the National Tuberculosis Elimination Programme (NTEP) and NPY beneficiaries from 30 districts across nine states of India, selected using theoretical sampling. An analytical framework developed through inductive coding of a set of six interviews, guided the coding of the subsequent interviews. Categories and themes emerged through constant comparison and the data collection continued until theoretical saturation. Results Stakeholders perceived NPY as a beneficial initiative. Strong political commitment from the state administration, mainstreaming of NTEP work with the district public healthcare delivery system, availability of good geographic and internet connectivity and state-specific grievance redressal mechanisms and innovations were identified as enablers of implementation. However, the complex, multi-level benefit approval process, difficulties in accessing banking services, perceived inadequacy of benefits and overworked human resources in the NTEP were identified as barriers to implementation and utilization. Conclusion The optimal utilization of NPY is enabled by strong political commitment and challenged by its lengthy implementation process and delayed disbursal of benefits. We recommend greater operational simplicity in NPY implementation, integrating NTEP activities with the public health system to reduce the burden on the program staff, and revising the benefit amount more equitably.

Background Ni-kshay Poshan Yojana (NPY), a direct benefit transfer scheme under the National Tuberculosis Elimination Program (NTEP) in India, provides a monthly benefit of INR500 for nutritional support of persons with TB (PwTB). Objectives To determine the proportion of PwTB receiving at least one NPY instalment and pattern of utilisation; to ascertain factors associated with NPY non-receipt and association of NPY receipt with TB treatment outcome. Methods In our cross-sectional study, we used multi-stage sampling to select PwTB whose treatment outcome was declared between May 2022 and February 2023. A cluster-adjusted, generalized linear model was used to identify factors associated with the non-receipt of NPY and determine association between NPY receipt and TB treatment outcome. Results Among 3201 PwTB, 2888 (92.7%; 95% CI 89.8%, 94.8%) had received at least one NPY instalment, and 1903 (64.2%; 95% CI 58.9%, 69.2%) self-reported receipt of benefit. The median (IQR) time to receipt of first instalment was 105 (60,174) days. Non-receipt was significantly higher among PwTB from states with low TB score (aPR = 2.34; 95%CI 1.51, 3.62), who do not have bank account (aPR = 2.48; 95%CI 1.93, 3.19) and with unknown/missing diabetic status (aPR = 1.69; 95%CI 1.11, 2.55). Unfavorable treatment outcomes were associated with non-receipt of NPY (aPR 4.93; 95%CI 3.61,6.75) after adjusting for potential confounders. Conclusion Majority of the PwTB received at least one NPY instalment, but they experience significant delays. Most of the recipients utilised NPY for nutrition. Longitudinal follow-up studies are required to study the impact of NPY on treatment outcomes.

In India, the incidence of mucormycosis reached high levels during 2021–2022, coinciding with the COVID-19 pandemic. In response to this, we established a multicentric ambispective cohort of patients hospitalised with mucormycosis across India. In this paper, we report their baseline profile, clinical characteristics and outcomes at discharge. Patients hospitalized for mucormycosis during March–July 2021 were included. Mucormycosis was diagnosed based on mycological confirmation on direct microscopy (KOH/Calcofluor white stain), culture, histopathology, or supportive evidence from endoscopy or imaging. After consent, trained data collectors used medical records and telephonic interviews to capture data in a pre-tested structured questionnaire. At baseline, we recruited 686 patients from 26 study hospitals, of whom 72.3% were males, 78% had a prior history of diabetes, 53.2% had a history of corticosteroid treatment, and 80% were associated with COVID-19. Pain, numbness or swelling of the face were the commonest symptoms (73.3%). Liposomal Amphotericin B was the commonest drug formulation used (67.1%), and endoscopic sinus surgery was the most common surgical procedure (73.6%). At discharge, the disease was stable in 43.3%, in regression for 29.9% but 9.6% died during hospitalization. Among survivors, commonly reported disabilities included facial disfigurement (18.4%) and difficulties in chewing/swallowing (17.8%). Though the risk of mortality was only 1 in 10, the disability due to the disease was very high. This cohort study could enhance our understanding of the disease’s clinical progression and help frame standard treatment guidelines.

Abstract 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.

BackgroundIn 2022, India's national tuberculosis (TB) elimination program (NTEP) commissioned a national level evaluation of active case finding (ACF) for TB to guide evidence-based strategic planning. As part of this evaluation, based on secondary data analysis we observed that the quality of ACF was suboptimal in 2021. Hence, this study aimed to understand the enablers, barriers, and suggested solutions to improve ACF for TB in India from NTEP staff (provider) perspective.MethodsThis was a descriptive qualitative study involving key informant interviews from six districts and eight states, conducted between February and August 2023. We purposively selected key state- district- and sub-district-level program managers and implementers who were experienced and vocal. The interviews were audio recorded and transcribed verbatim by research interns and investigators. Two investigators independently did manual descriptive thematic analysis, and a third investigator resolved inconsistencies. The themes and categories emerged by collating together the results of the coding process.ResultsA total of 34 key informant interviews were conducted and of these, four were repeat interviews. Adequate budgets for ACF including incentives, performance review mechanism, engagement of all stakeholders, adopting a community friendly approach, use of rapid diagnostic tests and digitalization were the perceived enablers. In some states ACF was implemented in general population (not restricted to high-risk population) following directives at state level. There were limited mechanisms to ensure ACF quality indicators were met before disbursing incentives and cross-verification of the aggregate ACF care cascade numbers that were reported in Ni-kshay (electronic TB information management system under NTEP). In addition to the state and district level implementers having limited understanding of concepts around ACF (quality indicators, number needed to screen and yield), we also inferred the presence of a 'know-do' gap for many activities under ACF. The suggested solutions were around capacity building and quality improvement strategies.ConclusionThe existing national ACF guidance should be revised to emphasize capacity building, need to carry out ACF in high-risk (not general) population, quality control-linked incentives, and regular implementation monitoring of the activities. This should contribute towards better coverage and improved quality translating into better ACF outcomes.

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.

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.

Objectives: India introduced BBV152/Covaxin and AZD1222/Covishield vaccines in January 2021. We estimated the effectiveness of these vaccines against severe COVID-19 among individuals aged ≥45 years. Methods: We did a multi-centric, hospital-based, case-control study between May and July 2021. Cases were severe COVID-19 patients, and controls were COVID-19 negative individuals from 11 hospitals. Vaccine effectiveness (VE) was estimated for complete (2 doses ≥ 14 days) and partial (1 dose ≥ 21 days) vaccination; interval between two vaccine doses and vaccination against the Delta variant. We used the random effects logistic regression model to calculate the adjusted odds ratios (aOR) with a 95% confidence interval (CI) after adjusting for relevant known confounders. Results: We enrolled 1143 cases and 2541 control patients. The VE of complete vaccination was 85% (95% CI: 79-89%) with AZD1222/Covishield and 71% (95% CI: 57-81%) with BBV152/Covaxin. The VE was highest for 6-8 weeks between two doses of AZD1222/Covishield (94%, 95% CI: 86-97%) and BBV152/Covaxin (93%, 95% CI: 34-99%). The VE estimates were similar against the Delta strain and sub-lineages. Conclusion: BBV152/Covaxin and AZD1222/Covishield were effective against severe COVID-19 among the Indian population during the period of dominance of the highly transmissible Delta variant in the second wave of the pandemic. An escalation of two-dose coverage with COVID-19 vaccines is critical to reduce severe COVID-19 and further mitigate the pandemic in the country.

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.

Monkeypox (MPX) is a zoonotic infection caused by the monkeypox virus (MPXV) and is primarily characterized by rash or pox marks and lymph node enlargement. The recent MPX has quickly spread across the globe and is now declared a global public health emergency. Being a contact illness, sexual encounters have been identified as the most common mode of transmission in the 2022 multicountry MPX outbreak. Data suggest that MPX is highly concentrated in men who have sex with men (MSM) networks and among those who had a recent sexual encounter with one or more partners. In India, the estimated MSM population was 569,346 in 2019. An analysis of the sexual partnerships among MSM suggests a potential highly interconnected MSM network in India, increasing the risk of MPX burden. The viewpoint emphasizes the need for community-level awareness and surveillance for the early detection and prevention of MPX infection in India.

ObjectivesThe present study was planned to estimate the prevalence of dental fluorosis in 6–12 years of children and its association with various drinking water sources, water, and urine fluoride levels among the subset of children under the umbrella of a larger study to address iodine deficiency disorders and iron deficiency anemia in 17 villages of Manvi and Devadurga talukas of Raichur district of Karnataka.MethodsAnalysis of subset of data and urine samples of children under the umbrella of a larger cross-sectional community-based study was conducted in 17 villages of Manvi and Devadurga taluks of Raichur district. House to house survey was carried out to collect data using a semi-structured questionnaire in ODK software. Demographic details, source of drinking water, clinical assessment of dental fluorosis, and height and weight measurements were performed by trained staff. Urine and water samples were collected for fluoride level estimation. The overall prevalence of dental fluorosis and its severity-wise prevalence were estimated. Association between dental fluorosis and age, gender, type of diet, source of drinking water, height for age, BMI for age, water fluoride level, and urine fluoride level were carried out using logistic regression analysis.ResultsThe prevalence of dental fluorosis was 46.0%. Mild, moderate, and severe dental fluorosis was found in 37.9, 7.8, and 0.3% of children. With the increasing age of participants, the odds of dental fluorosis were found to increase by 2–4 folds. The odds of having dental fluorosis were significantly increased with increasing water fluoride levels of 3 to 5 ppm [AOR = 3.147 (1.585–6.248); P = 0.001] in comparison with water fluoride levels of < 1 ppm. The similar trend was found with urine fluoride level > 4 ppm [AOR = 3.607 (1.861–6.990); P < 0.001]. As compared to river water, other sources of drinking water were significantly associated with higher odds of dental fluorosis.ConclusionsPrevalence of dental fluorosis was high in 6 to 12 years due to overexposure of fluoride from drinking water. High water and urine fluoride levels in children indicate the chronic exposure to fluoride and suggest that the population is at high risk of developing chronic fluorosis.

Introduction: India experienced 2 waves of COVID-19 pandemic caused by SARS-CoV-2 and reported the second highest caseload globally. Seroepidemiologic studies were done to track the course of the pandemic. We systematically reviewed and synthesized the seroprevalence of SARS-CoV-2 in the Indian population.Methods: We included studies reporting seroprevalence of IgG antibodies against SARS-CoV-2 from March 1, 2020 to August 11, 2021 and excluded studies done only among patients with COVID-19 and vaccinated individuals. We searched published databases, preprint servers, and government documents using a combination of keywords and medical subheading (MeSH) terms of “Seroprevalence AND SARS-CoV-2 AND India”. We assessed risk of bias using the Newcastle-Ottawa scale, the appraisal tool for cross-sectional studies (AXIS), the Joanna Briggs Institute (JBI) critical appraisal tool, and WHO's statement on the Reporting of Seroepidemiological Studies for SARS-CoV-2 (ROSES-S). We calculated pooled seroprevalence along with 95% Confidence Intervals (CI) during the first (March 2020 to February 2021) and second wave (March to August 2021). We also estimated seroprevalence by selected demographic characteristics.Results: We identified 3821 studies and included 53 studies with 905379 participants after excluding duplicates, screening of titles and abstracts and full-text screening. Of the 53, 20 studies were of good quality. Some of the reviewed studies did not report adequate information on study methods (sampling = 24% (13/53); laboratory = 83% [44/53]). Studies of ‘poor’ quality had more than one of the following issues: unjustified sample size, nonrepresentative sample, nonclassification of nonrespondents, results unadjusted for demographics and methods insufficiently explained to enable replication. Overall pooled seroprevalence was 20.7% in the first (95% CI = 16.1 to 25.3) and 69.2% (95% CI = 64.5 to 73.8) in the second wave. Seroprevalence did not differ by age in first wave, whereas in the second, it increased with age. Seroprevalence was slightly higher among women in the second wave. In both the waves, the estimate was higher in urban than in rural areas.Conclusion: Seroprevalence increased by 3-fold between the 2 waves of the pandemic in India. Our review highlights the need for designing and reporting studies using standard protocols.

A complete sampling frame (CSF) is needed for the development of probability sampling structures; utilisation of a spatial sampling frame (SSF) was the objective of the present study. We used two sampling methods, simple random sampling (SRS) and stratified random sampling (STRS), to compare the prevalence estimates delivered by a CSF to that by a SSF when applied to self-reported hypertension and diabetes mellitus in a semi-urban setting and in a rural one. A CSF based on Geodatabase of all households and all individuals was available for our study that focused on adults aged 18-69 years in the two settings. A single digitized shapefile of solely household regions/structures as SSF was developed using Google Earth and employed for the study. The results from the two sampling frames were similar and not significantly different. All 95%CI calculations contained the prevalence rates of the two medical conditions except for one occasion based on STRS and CSF. The SRS based on CSF showed a minimum 95% CI width for diabetes mellitus, whereas SSF showed a minimum 95% CI width for hypertension. The coefficient of variation exceeded 10.0% on six occasions for CSF but only once for SSF, which was found to be as efficient as CSF.

Background: Earlier serosurveys in India revealed seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) of 0.73% in May–June 2020 and 7.1% in August–September 2020. A third serosurvey was conducted between December 2020 and January 2021 to estimate the seroprevalence of SARS-CoV-2 infection among the general population and healthcare workers (HCWs) in India. Methods: The third serosurvey was conducted in the same 70 districts as the first and second serosurveys. For each district, at least 400 individuals aged ≥10 years from the general population and 100 HCWs from subdistrict-level health facilities were enrolled. Serum samples from the general population were tested for the presence of immunoglobulin G (IgG) antibodies against the nucleocapsid (N) and spike (S1-RBD) proteins of SARS-CoV-2, whereas serum samples from HCWs were tested for anti-S1-RBD. Weighted seroprevalence adjusted for assay characteristics was estimated. Results: Of the 28,598 serum samples from the general population, 4585 (16%) had IgG antibodies against the N protein, 6647 (23.2%) had IgG antibodies against the S1-RBD protein, and 7436 (26%) had IgG antibodies against either the N protein or the S1-RBD protein. Weighted and assay-characteristic-adjusted seroprevalence against either of the antibodies was 24.1% [95% confidence interval (CI) 23.0–25.3%]. Among 7385 HCWs, the seroprevalence of anti-S1-RBD IgG antibodies was 25.6% (95% CI 23.5–27.8%). Conclusions: Nearly one in four individuals aged ≥10 years from the general population as well as HCWs in India had been exposed to SARS-CoV-2 by December 2020.

Background: Two suspected shellfish poisoning events were reported in Cuddalore District in Tamil Nadu, India, between January and April 2015. Objectives: The study was conducted to confirm the outbreaks and to identify the source and risk factors. Methods: For both outbreaks, a case was defined as a person with nausea, vomiting, or dizziness. Sociodemographic details and symptoms were noted down. Data were also collected in a standard 3-day food frequency questionnaire, along with a collection of clam samples. A case–control study was initiated in the April outbreak. Stool samples were collected from cases, and clam vendors were interviewed. Results: In an outbreak that happened in January, all the twenty people reported to be consumed clams were diagnosed as cases (100% attack rate, 100% exposure rate). In the April outbreak, we identified 199 cases (95% attack rate). In both outbreaks, the clams were identified as genus Meretrix meretrix. The most common reported symptoms were dizziness and vomiting. The clams heated and consumed within 30–60 min. No heavy metals or chemicals were detected in the clams, but assays for testing shellfish toxins were unavailable. All 64 selected cases reported clam consumption (100% exposure rate) as did 11 controls (17% exposure rate). Illness was associated with a history of eating of clams (odds ratio = 314, 95% confidence interval = 39–512). Of the six stool samples tested, all were culture negative for Salmonella, Shigella, and Vibrio cholerae. The water at both sites was contaminated with garbage and sewage. Conclusion: Coordinated and timely efforts by a multidisciplinary team of epidemiologists, marine biologists, and food safety officers led to the outbreaks' containment.

Introduction: India introduced a hepatitis-B (HB) vaccine in the Universal Immunization Program in 2002–2003 on a pilot basis, expanded to ten states in 2007–2008 (phase-1), and the entire country in 2011–2012 (phase-2). We tested sera from a nationally representative serosurvey conducted duing 2017, to estimate the seroprevalence of different markers of HB infection among children aged 5–17 years in India and to assess the impact of vaccination. Methods: We tested sera from 8273 children for different markers of HB infection and estimated weighted age-group specific seroprevalence of children who were chronically infected (HBsAg and anti-HBc positive), and immune due to past infection (anti-HBc positive and HBsAg negative), and having serological evidence of HB vaccination (only anti-HBs positive). We compared the prevalence of serological markers among children born before (aged 11–17 years) and after (aged 5-10 years) introduction of HB-vaccine from phase-1 states. Results: Among children aged 5–8 years, 1.1% were chronic carriers, 5.3% immune due to past infection, and 23.2% vaccinated. The corresponding proportions among children aged 9–17 years were 1.1%, 8.0%, and 12.0%, respectively. In phase-1 states, children aged 5–10 years had a significantly lower prevalence of anti-HBc (4.9% vs. 7.6%, p

Background & objectives: The Department of Health Research and the Indian Council of Medical Research, Government of India, have established Virus Research and Diagnostic Laboratory Network (VRDLN) to strengthen the laboratory capacity in the country for providing timely diagnosis of disease outbreaks. Fifty-one VRDLs were functional as on December 2017 and had reported about dengue fever across Indian states. The objectives of the study were to detect space time clusters and purely temporal clusters of dengue using Kulldorff's SaTScan statistics using patient level information; and to identify regions at greater risk of developing the disease using Kriging technique aggregating at district level. Methods: A total of 211,432 patients from 51 VRDLs were investigated for IgM antibodies or NS1 antigen against dengue virus during the period from 1 January 2014 to 31 December 2017 and among them 60,096 (28.4%) were found to be positive. Kulldorff's space time analysis was used to identify significant clusters over space and time. Kriging technique was used to interpolate dengue data for areas not physically sampled using the relationship in the spatial arrangement of the data set. Maps obtained using both the methods were overlaid to identify the regions at greater risk of developing the disease. Results: Kulldorff Space time Scan Statistics using the Bernoulli model with monthly precision revealed eight statistically significant clusters (P

BackgroundIndia began COVID-19 vaccination in January 2021, initially targeting healthcare and frontline workers. The vaccination strategy was expanded in a phased manner and currently covers all individuals aged 18 years and above. India experienced a severe second wave of COVID-19 during March-June 2021. We conducted a fourth nationwide serosurvey to estimate prevalence of SARS-CoV-2 antibodies in the general population aged ≥6 years and healthcare workers (HCWs).Methods and findingsWe did a cross-sectional study between 14 June and 6 July 2021 in the same 70 districts across 20 states and 1 union territory where 3 previous rounds of serosurveys were conducted. From each district, 10 clusters (villages in rural areas and wards in urban areas) were selected by the probability proportional to population size method. From each district, a minimum of 400 individuals aged ≥6 years from the general population (40 individuals from each cluster) and 100 HCWs from the district public health facilities were included. The serum samples were tested for the presence of IgG antibodies against S1-RBD and nucleocapsid protein of SARS-CoV-2 using chemiluminescence immunoassay. We estimated the weighted and test-adjusted seroprevalence of IgG antibodies against SARS-CoV-2, along with 95% CIs, based on the presence of antibodies to S1-RBD and/or nucleocapsid protein. Of the 28,975 individuals who participated in the survey, 2,892 (10%) were aged 6-9 years, 5,798 (20%) were aged 10-17 years, and 20,285 (70%) were aged ≥18 years; 15,160 (52.3%) participants were female, and 21,794 (75.2%) resided in rural areas. The weighted and test-adjusted prevalence of IgG antibodies against S1-RBD and/or nucleocapsid protein among the general population aged ≥6 years was 67.6% (95% CI 66.4% to 68.7%). Seroprevalence increased with age (p < 0.001) and was not different in rural and urban areas (p = 0.822). Compared to unvaccinated adults (62.3%, 95% CI 60.9% to 63.7%), seroprevalence was significantly higher among individuals who had received 1 vaccine dose (81.0%, 95% CI 79.6% to 82.3%, p < 0.001) and 2 vaccine doses (89.8%, 95% CI 88.4% to 91.1%, p < 0.001). The seroprevalence of IgG antibodies among 7,252 HCWs was 85.2% (95% CI 83.5% to 86.7%). Important limitations of the study include the survey design, which was aimed to estimate seroprevalence at the national level and not at a sub-national level, and the non-participation of 19% of eligible individuals in the survey.ConclusionsNearly two-thirds of individuals aged ≥6 years from the general population and 85% of HCWs had antibodies against SARS-CoV-2 by June-July 2021 in India. As one-third of the population is still seronegative, it is necessary to accelerate the coverage of COVID-19 vaccination among adults and continue adherence to non-pharmaceutical interventions.

Objective To describe the characteristics of contacts of patients with COVID-19 case in terms of time, place and person, to calculate the secondary attack rate (SAR) and factors associated with COVID-19 infection among contacts.Design A retrospective cohort studySetting and participants Contacts of cases identified by the health department from 14 March 2020to 30 May 2020, in 9 of 38 administrative districts of Tamil Nadu. Significant proportion of cases attended a religious congregation.Outcome measure Attack rate among the contacts and factors associated with COVID-19 positivity.Results We listed 15 702 contacts of 931 primary cases. Of the contacts, 89% (n: 14 002) were tested for COVID-19. The overall SAR was 4% (599/14 002), with higher among the household contacts (13%) than the community contacts (1%). SAR among the contacts of primary cases with congregation exposure were 5 times higher than the contacts of non-congregation primary cases (10% vs 2%). Being a household contact of a primary case with congregation exposure had a fourfold increased risk of getting COVID-19 (relative risk (RR): 16.4; 95% CI: 13 to 20) than contact of primary case without congregation exposure. Among the symptomatic primary cases, household contacts of congregation primaries had higher RR than household contacts of other cases ((RR: 25.3; 95% CI: 10.2 to 63) vs (RR: 14.6; 95% CI: 5.7 to 37.7)). Among asymptomatic primary case, RR was increased among household contacts (RR: 16.5; 95% CI: 13.2 to 20.7) of congregation primaries compared with others.Conclusion Our study showed an increase in disease transmission among household contacts than community contacts. Also, symptomatic primary cases and primary cases with exposure to the congregation had more secondary cases than others.

Dried blood spot (DBS) collection offers various advantages over conventional methods of blood collection, especially when collecting and transporting samples for a serosurvey. Yet use of DBS requires additional processing steps in the laboratory that can add to variability in results.

Background: Early detection of symptoms of loss of smell and taste lately added for Coronavirus disease 2019 (COVID-19) has the potential for improving pandemic response. In the Indian context, we compared proportion experiencing new loss of smell or taste among COVID-19 positive and negative individuals in Chennai city, Southern India. Methods: We did an analytical cross-sectional study among individuals aged 18–80 years undergoing testing at COVID-19 sample collection centres. We ascertained loss of smell and taste using standardised self-reporting and clinical examination procedures. We administered Sino Nasal Outcome (SNOT 22) questionnaire for comprehensive understanding of these symptoms. We compared proportion having symptoms between COVID-19 positive and negative persons. We compared the two assessment methods to compute diagnostic validity indicators. Results: Of the 277 participants, 169 (61%) were men and mean age of 40.7 years [SD = 13.3]. Fifty eight (21%) had COVID-19 and 12 (36%) of them were asymptomatic. Predominantly reported symptoms were fever (30%), headache (18%) and cough (18%). Self-reported or clinically identified new loss of smell or taste was higher among COVID-19 positive (n = 13; 22%) than negative persons (n = 23; 11%) [p = 0.02]. Sensitivity was higher for self-reported or clinically identified loss of smell (17.2%) than that of loss of taste (6.9%). Negative predictive value for loss of smell or taste, self-reported or clinically identified was 81%. Likelihood ratio of positive test was 2.13. Conclusion: Loss of smell or taste are predominantly reported by COVID-19 confirmed individuals. Objective and subjective assessments of smell and taste may be required to identify those requiring COVID-19 testing.

BackgroundIndia has set a goal to eliminate measles and rubella/Congenital Rubella Syndrome (CRS) by 2023. Towards this goal, India conducted nationwide supplementary immunization activity (SIA) with measles-rubella containing vaccine (MRCV) targeting children aged between 9 months to MethodsWe conducted serosurveys in 2019-20 among pregnant women attending antenatal clinics of 6 hospitals, which were also sentinel sites for CRS surveillance, to estimate the prevalence of IgG antibodies against rubella. We systematically sampled 1800 women attending antenatal clinics and tested their sera for IgG antibodies against rubella. We used rubella seroprevalence data from the current survey and the survey conducted in 2017 among antenatal women from another 6 CRS surveillance sites to construct a catalytic models to estimate the incidence and burden of CRS.ResultThe seroprevalence of rubella antibodies was 82.3% (95% CI: 80.4-84.0). Rubella seropositivity did not differ by age group and educational status. Based on the constant and age-dependent force of infection models, we estimated that the annual incidence of CRS in India was 225.58 per 100,000 live births (95% CI: 217.49-232.41) and 65.47 per 100,000 live births (95% CI: 41.60-104.16) respectively. This translated to an estimated 14,520 (95% CI: 9,225-23,100) and 50,028 (95% CI: 48,234-51,543) infants with CRS every year based on age-dependent and constant force of infection models respectively.ConclusionsOur findings indicated that about one fifth of women in the reproductive age group in India were susceptible for rubella. The estimates of CRS incidence will serve as a baseline to monitor the impact of MRCV SIAs, as well progress towards the elimination goal of rubella/CRS.

We conducted a serosurvey of 155 healthcare workers and 124 household and community members who had close contact with 18 patients who had laboratory-confirmed Nipah virus infections in Kerala, India. We detected 3 subclinical infections; 2 persons had IgM and IgG and 1 only IgM against Nipah virus.

BackgroundRisk factors for the development of severe COVID-19 disease and death have been widely reported across several studies. Knowledge about the determinants of severe disease and mortality in the Indian context can guide early clinical management.MethodsWe conducted a hospital-based case control study across nine sites in India to identify the determinants of severe and critical COVID-19 disease.FindingsWe identified age above 60 years, duration before admission >5 days, chronic kidney disease, leucocytosis, prothrombin time > 14 sec, serum ferritin >250 ng/mL, d-dimer >0.5 ng/mL, pro-calcitonin >0.15 μg/L, fibrin degradation products >5 μg/mL, C-reactive protein >5 mg/L, lactate dehydrogenase >150 U/L, interleukin-6 >25 pg/mL, NLR ≥3, and deranged liver function, renal function and serum electrolytes as significant factors associated with severe COVID-19 disease.InterpretationWe have identified a set of parameters that can help in characterising severe COVID-19 cases in India. These parameters are part of routinely available investigations within Indian hospital settings, both public and private. Study findings have the potential to inform clinical management protocols and identify patients at high risk of severe outcomes at an early stage.

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings.

Summary: Background: The burden of dengue virus (DENV) infection across geographical regions of India is poorly quantified. We estimated the age-specific seroprevalence, force of infection, and number of infections in India. Methods: We did a community-based survey in 240 clusters (118 rural, 122 urban), selected from 60 districts of 15 Indian states from five geographical regions. We enumerated each cluster, randomly selected (with an Andriod application developed specifically for the survey) 25 individuals from age groups of 5–8 years, 9–17 years, and 18–45 years, and sampled a minimum of 11 individuals from each age group (all the 25 randomly selected individuals in each age group were visited in their houses and individuals who consented for the survey were included in the study). Age was the only inclusion criterion; for the purpose of enumeration, individuals residing in the household for more than 6 months were included. Sera were tested centrally by a laboratory team of scientific and technical staff for IgG antibodies against the DENV with the use of indirect ELISA. We calculated age group specific seroprevalence and constructed catalytic models to estimate force of infection. Findings: From June 19, 2017, to April 12, 2018, we randomly selected 17 930 individuals from three age groups. Of these, blood samples were collected and tested for 12 300 individuals (5–8 years, n=4059; 9–17 years, n=4265; 18–45 years, n=3976). The overall seroprevalence of DENV infection in India was 48·7% (95% CI 43·5–54·0), increasing from 28·3% (21·5–36·2) among children aged 5–8 years to 41·0% (32·4–50·1) among children aged 9–17 years and 56·2% (49·0–63·1) among individuals aged between 18–45 years. The seroprevalence was high in the southern (76·9% [69·1–83·2]), western (62·3% [55·3–68·8]), and northern (60·3% [49·3–70·5]) regions. The estimated number of primary DENV infections with the constant force of infection model was 12 991 357 (12 825 128–13 130 258) and for the age-dependent force of infection model was 8 655 425 (7 243 630–9 545 052) among individuals aged 5–45 years from 30 Indian states in 2017. Interpretation: The burden of dengue infection in India was heterogeneous, with evidence of high transmission in northern, western, and southern regions. The survey findings will be useful in making informed decisions about introduction of upcoming dengue vaccines in India. Funding: Indian Council of Medical Research.

Outbreaks of acute encephalitis syndrome (AES) have been occurring in Gorakhpur Division, Uttar Pradesh, India, for several years. In 2016, we conducted a case–control study. Our findings revealed a high proportion of AES cases with Orientia tsutsugamushi IgM and IgG, indicating that scrub typhus is a cause of AES.

INTRODUCTION:Dengue is the most extensively spread mosquito-borne disease; endemic in more than 100 countries. Information about dengue disease burden, its prevalence, incidence and geographic distribution is critical in planning appropriate control measures against dengue fever. We conducted a systematic review and meta-analysis of dengue fever in India. METHODS:We searched for studies published until 2017 reporting the incidence, the prevalence or case fatality of dengue in India. Our primary outcomes were (a) prevalence of laboratory confirmed dengue infection among clinically suspected patients, (b) seroprevalence in the general population and (c) case fatality ratio among laboratory confirmed dengue patients. We used binomial-normal mixed effects regression model to estimate the pooled proportion of dengue infections. Forest plots were used to display pooled estimates. The metafor package of R software was used to conduct meta-analysis. RESULTS:Of the 2285 identified articles on dengue, we included 233 in the analysis wherein 180 reported prevalence of laboratory confirmed dengue infection, seven reported seroprevalence as evidenced by IgG or neutralizing antibodies against dengue and 77 reported case fatality. The overall estimate of the prevalence of laboratory confirmed dengue infection among clinically suspected patients was 38.3% (95% CI: 34.8%-41.8%). The pooled estimate of dengue seroprevalence in the general population and CFR among laboratory confirmed patients was 56.9% (95% CI: 37.5-74.4) and 2.6% (95% CI: 2-3.4) respectively. There was significant heterogeneity in reported outcomes (p-values

We investigated a Kyasanur Forest disease outbreak in Karnataka, India during December 2013–April 2014. Surveillance and retrospective study indicated low vaccine coverage, low vaccine effectiveness, and spread of disease to areas beyond those selected for vaccination and to age groups not targeted for vaccination. To control disease, vaccination strategies need to be reviewed.

Globally, 1 billion people live in slums. There are few reports of high prevalence of noncommunicable disease (NCD) risk factors among the urban poor. The prevalence of NCD risk factors in the slums in North 24 Parganas, West Bengal, India was estimated. Cross-sectional survey in 24 slums selected using cluster sampling method was conducted. Questionnaire for behavioral risk factors was used and anthropometric and blood pressure measurements were done. The study population included 1052 participants aged 25-64 years, 528 (50%) were males. Among males, 206 (39%) were current smokers and 154 (29%) were current alcohol users. Central obesity was prevalent among 32.8% males and 56.1% females and 115 (10.9%) had body mass index ≥27.5 kg/m 2 . Hypertension was prevalent among 35% males and 33% females. We observed high prevalence of NCD risk factors among urban slum dwellers that need to be addressed with health promotion programs and strengthening of primary health care system.

Objective: To estimate the prevalence of usage, unsafe practices and risk perception regarding household pesticides in a rural community of Tamil Nadu, India. Materials and Methods: In a cross-sectional survey we used a pre-tested questionnaire and trained interviewers to collect information on household pesticide use for the past 6 months from any adult member of randomly selected households. Results: Out of 143 households, 95% used at least one household pesticide (95% CI: 93.5-99.5) and 94% used at least one household pesticide specifically for mosquito control. The most commonly used pesticides were mosquito coils (75%), mosquito liquid vaporizers (36%), ant-killing powder (24%) and moth/naphthalene balls (18%). The major non-chemical methods of pest control were rat traps (12%) and mosquito bed nets (7.5%). Out of the mosquito coil users, 61% kept the windows and doors closed while the coil was burning. Out of the moth ball users, 88% left them in the place of use till they fully vaporized. Nearly half of the users did not know that household pesticides were harmful to their health and the health of their children. Conclusions: The use of household pesticides was highly prevalent in this rural community. The prevalence of unsafe practices while handling them was also high. We recommend that the users of household pesticides be educated about the health hazards and about safe practices and non-chemical methods of pest control be promoted.

To determine the cause of the recent upsurge in Kyasanur Forest disease, we investigated the outbreak that occurred during December 2011–March 2012 in India. Male patients >14 years of age were most commonly affected. Although vaccination is the key strategy for preventing disease, vaccine for boosters was unavailable during 2011, which might be a reason for the increased cases.

Background: The first case of pandemic Influenza A (H1N1) in India was reported from Hyderabad, Andhra Pradesh on 16 th May 2009. Subsequently, all suspected cases seeking treatment from A (H1N1) treatment centers and their contacts were tested. Laboratory confirmed cases were hospitalized and treated with antivirals according to national guidelines. We reviewed the surveillance data to assess the morbidity and mortality due to A (H1N1) in the state of Andhra Pradesh (population-76,210,007) during the period from May 2009 to December 2010. Materials and Methods: We obtained the line-list of suspected (influenza like illness as per World Health Organization case definition) and laboratory confirmed cases of A (H1N1) from the state unit of integrated disease surveillance project. We analyzed the data to describe the distribution of case-patients by time, place and person. Results: During May 2009 to December 2010, a total of 6527 suspected (attack rate: 8.6/100,000) and 1480 (attack rate: 1.9/100,000) laboratory confirmed cases were reported from the State. Nearly 90% of the suspected and 93% of the confirmed cases was from nine districts of Telangana region, which includes Hyderabad. Nearly 65% of total confirmed cases were reported from Hyderabad. The attack rate was maximum (2.6/100,000) in the age group of 25-49 years. The cases peaked during August-October. 109 case-patients died (Case fatality ratio: 7%) and most (80%) of these patients had comorbid conditions such as diabetes (24%), chronic obstructive pulmonary disease (20%), hypertension (11%) and pregnancy (11%). Case fatality was higher (16%) among patients who were older than 60 years of age compared with other age groups. Conclusions: In Andhra Pradesh, H1N1 transmission peaked during August-October months and predominately affected adults. Case fatality was higher in patients older than 60 years with comorbid conditions.