Recurrence of pulmonary tuberculosis in India: Findings from the 2019-2021 nationwide community-based TB prevalence survey.

Recurrent Tuberculosis patients contribute to a significant proportion of TB burden in India. A nationwide survey was conducted during 2019-2021 across India among adults to estimate the prevalence of TB. A total of 322480 individuals were screened and 1402 were having TB. Of this, 381 (27.1%) had recurrent TB. The crude prevalence (95% CI) of recurrent TB was 118 (107-131) per 100,000 population. The median duration between episodes of TB was 24 months. The proportion of drug resistant TB was 11.3% and 3.6% in the recurrent group and new TB patients respectively. Higher prevalence of recurrent TB was observed in elderly, males, malnourished, known diabetics, smokers, and alcohol users. (p<0.001). To prevent TB recurrence, all treated tuberculosis patients must be followed at least for 24 months, with screening for Chest X-ray, liquid culture every 6 months, smoking cessation, alcohol cessation, nutritional interventions and good diabetic management.

Prevalence and factors associated with tuberculosis infection in India.

BACKGROUND: The risk of tuberculosis (TB) disease is higher in individuals with TB infection. In a TB endemic country like India, it is essential to understand the current burden of TB infection at the population level. The objective of the present analysis is to estimate the prevalence of TB infection in India and to explore the factors associated with TB infection. METHODS: Individuals aged > 15 years in the recently completed National TB prevalence survey in India who were tested for TB infection by QuantiFERON-TB Gold Plus (QFT-Plus) assay were considered for this sub-analysis. TB infection was defined as positive by QFT-Plus (value >0.35 IU/ml). The estimates for prevalence, prevalence ratio (PR) and adjusted risk ratio (aRR) estimates with 95% confidence intervals (CIs) were calculated. RESULTS: Of the 16864 individuals analysed, the prevalence of TB infection was 22.6% (95% CI:19.4 -25.8). Factors more likely to be associated with TB infection include age > 30 years (aRR:1.49;95% CI:1.29-1.73), being male (aRR:1.26; 95%CI: 1.18-1.34), residing in urban location (aRR:1.58; 95%CI: 1.03-2.43) and past history of TB (aRR:1.49; 95%CI: 1.26-1.76). CONCLUSION: About one fourth (22.6%) of the individuals were infected with TB in India. Individuals aged > 30 years, males, residing in urban location, and those with past history of TB were more likely to have TB infection. Targeted interventions for prevention of TB and close monitoring are essential to reduce the burden of TB in India.

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.

Assessment of Community Behavior and COVID-19 Transmission during Festivities in India: A Qualitative Synthesis through a Media Scanning Technique.

In India during the first wave of COVID-19 infection, the authorities were concerned about the advent of the festive season, which could lead to a surge in cases of SARS-CoV-2 infection. The present study attempted to assess the socio-behavioral aspects of COVID-appropriate behavior (CAB) at individual and community levels, and their impact on the transmission of COVID-19 during festivities in India. Media scanning was conducted to qualitatively assess CAB by analyzing 284 news reports from across India; quantitative data on COVID-19 daily cases from March 2020 to December 2020 were used to determine the trends of the adjusted test positivity (ATP) ratio for six cities. Peaks in ATP were observed in Chandigarh, Delhi-NCR in North India during and after Dussehra and Deepavali, and in Mumbai, in the west, after Navratri. Additionally, a surge in ATP was observed in Trivandrum after Onam and in Chennai around Deepavali in the south; meanwhile, in the eastern city of Kolkata, cases increased following Durga Puja. The major challenges were adherence to CAB viz. social distancing, hygiene, and compliance with the mask mandate. Microlevel CAB indicated relatively higher laxity in maintaining hand hygiene in all cities. Observations from the current study indicate that innovative community-driven initiatives during festivals in each geographical zone are key to the large-scale implementation of disease prevention measures.

Estimation of tuberculosis incidence at subnational level using three methods to monitor progress towards ending TB in India, 2015-2020.

OBJECTIVES: We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India. DESIGN: A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data. SETTING: National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status. PARTICIPANTS: Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district. OUTCOME MEASURES: We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015. RESULTS: The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra. CONCLUSION: TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020.

Seroprevalence of IgG antibodies against SARS-CoV-2 among the general population and healthcare workers in India, June-July 2021: A population-based cross-sectional study.

BACKGROUND: India 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 FINDINGS: We 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. CONCLUSIONS: Nearly 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.

Association between ambient air pollutants and meteorological factors with SARS-CoV-2 transmission and mortality in India: an exploratory study.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic poses a serious public health concern worldwide. Certain regions of the globe were severely affected in terms of prevalence and mortality than other. Although the cause for this pattern is not clearly understood, lessons learned from previous epidemics and emerging evidences suggest the major role of ecological factors like ambient air pollutants (AAP) and meteorological parameters in increased COVID-19 incidence. The present study aimed to understand the impact of these factors on SARS-CoV-2 transmission and their associated mortality in major cities of India. METHODS: This study used secondary AAP, meteorological and COVID-19 data from official websites for the period January-November 2020, which were divided into Pre-lockdown (January-March 2020), Phase I (April to June 2020) and Phase II (July to November 2020) in India. After comprehensive screening, five major cities that includes 48 CPCB monitoring stations collecting daily data of ambient temperature, particulate matter PM2.5 and 10 were analysed. Spearman and Kendall's rank correlation test was performed to understand the association between SARS-CoV-2 transmission and AAP and, meteorological variables. Similarly, case fatality rate (CFR) was determined to compute the correlation between AAP and COVID-19 related morality. RESULTS: The level of air pollutants in major cities were significantly reduced during Phase I compared to Pre-lock down and increased upon Phase II in all the cities. During the Phase II in Delhi, the strong significant positive correlation was observed between the AAP and SARS-CoV-2 transmission. However, in Bengaluru, Hyderabad, Kolkata and Mumbai AAP levels were moderate and no correlation was noticed. The relation between AT and SARS-CoV-2 transmission was inconclusive as both positive and negative correlation observed. In addition, Delhi and Kolkata showed a positive association between long-term exposure to the AAP and COVID-19 CFR. CONCLUSION: Our findings support the hypothesis that the particulate matter upon exceeding the satisfactory level serves as an important cofactor in increasing the risk of SARS-CoV-2 transmission and related mortality. These findings would help public health experts to understand the SARS-CoV-2 transmission against ecological variables in India and provides supporting evidence to healthcare policymakers and government agencies for formulating strategies to combat the COVID-19.

Engaging with the private healthcare sector for the control of tuberculosis in India: cost and cost-effectiveness.

BACKGROUND: The control of tuberculosis (TB) in India is complicated by the presence of a large, disorganised private sector where most patients first seek care. Following pilots in Mumbai and Patna (two major cities in India), an initiative known as the 'Public-Private Interface Agency' (PPIA) is now being expanded across the country. We aimed to estimate the cost-effectiveness of scaling up PPIA operations, in line with India's National Strategic Plan for TB control. METHODS: Focusing on Mumbai and Patna, we collected cost data from implementing organisations in both cities and combined this data with models of TB transmission dynamics. Estimating the cost per disability adjusted life years (DALY) averted between 2014 (the start of PPIA scale-up) and 2025, we assessed cost-effectiveness using two willingness-to-pay approaches: a WHO-CHOICE threshold based on per-capita economic productivity, and a more stringent threshold incorporating opportunity costs in the health system. FINDINGS: A PPIA scaled up to ultimately reach 50% of privately treated TB patients in Mumbai and Patna would cost, respectively, US$228 (95% uncertainty interval (UI): 159 to 320) per DALY averted and US$564 (95% uncertainty interval (UI): 409 to 775) per DALY averted. In Mumbai, the PPIA would be cost-effective relative to all thresholds considered. In Patna, if focusing on adherence support, rather than on improved diagnosis, the PPIA would be cost-effective relative to all thresholds considered. These differences between sites arise from variations in the burden of drug resistance: among the services of a PPIA, improved diagnosis (including rapid tests with genotypic drug sensitivity testing) has greatest value in settings such as Mumbai, with a high burden of drug-resistant TB. CONCLUSIONS: To accelerate decline in TB incidence, it is critical first to engage effectively with the private sector in India. Mechanisms such as the PPIA offer cost-effective ways of doing so, particularly when tailored to local settings.

SARS-CoV-2 seroprevalence among the general population and healthcare workers in India, December 2020-January 2021.

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.

The RATIONS (Reducing Activation of Tuberculosis by Improvement of Nutritional Status) study: a cluster randomised trial of nutritional support (food rations) to reduce TB incidence in household contacts of patients with microbiologically confirmed pulmonary tuberculosis in communities with a high prevalence of undernutrition, Jharkhand, India.

INTRODUCTION: India has the largest burden of cases and deaths related to tuberculosis (TB). Undernutrition is the leading risk factor accounting for TB incidence, while severe undernutrition is a common risk factor for mortality in patients with TB in India. The impact of nutritional supplementation on TB incidence is unknown, while few underpowered studies have assessed its impact on TB mortality. We designed an open-label, field-based cluster randomised trial to assess the impact of nutritional supplementation (with food rations) on TB incidence in a group at higher risk of TB infection and disease, viz household contacts (HHC) of patients with microbiologically confirmed pulmonary TB (PTB) in Jharkhand, a state with a high prevalence of undernutrition. METHODS AND ANALYSIS: We shall enrol 2800 adult patients with PTB of the national TB programme, across 28 treatment units in 4 districts, and their approximately 11 200 eligible contacts. The sample size has 80% power to detect the primary outcome of 50% reduction in incidence of active TB in HHC over 2 years of follow-up. Patients and HHC in both the arms will undergo nutritional assessment and counselling. Patients will receive monthly food rations (supplying 1200 kcal and 52 g proteins/day) and multivitamins along with antitubercular treatment. The HHC in the intervention arm will receive food rations (supplying 750 kcal and 23 g proteins/day) and multivitamins while HHC in control arm will be on usual diet. The secondary outcomes in HHC will include effects on nutritional status, non-TB infections. Secondary outcomes in patients are effects on TB mortality, adherence, adverse effects, nutritional and performance status. Substudies will examine micronutrient status and effects on dietary intake, body composition, muscle strength and immune function. ETHICS AND DISSEMINATION: The institutional ethics committee of ICMR-NIRT, Chennai, approved the study (289/NIRT-IEC/2018). The results will be disseminated in publications and presentations. TRIAL REGISTRATION NUMBER: Clinical Trial Registry of India: CTRI/2019/08/020490.

Feasibility, efficiency & effectiveness of pooled sample testing strategy (pooled NAAT) for molecular testing of COVID-19.

BACKGROUND & OBJECTIVES: During the current COVID-19 pandemic, a large number of clinical samples were tested by real-time PCR. Pooling the clinical samples before testing can be a good cost-saving and rapid alternative for screening large populations. The aim of this study was to compare the performance characteristics, feasibility and effectiveness of pooling nasal swab and throat swab samples for screening and diagnosis of SARS-CoV-2. METHODS: The pool testing was applied on a set of samples coming from low COVID-19 positivity areas. A total of 2410 samples were tested in pools of five samples each. A total of five pools of five samples each were generated and tested for E gene. RESULTS: Of the total of 482 pools (2410 samples) 24 pools flagged positive. Later on pool de-convolution, a total of 26 samples were detected as positive for COVID-19, leading to positivity of about one per cent in the test population. For the diagnosis of individual samples, the pooling strategies resulted in cost savings of 75 per cent (5 samples per pool). INTERPRETATION & CONCLUSIONS: It was observed that testing samples for COVID-19 by reverse transcription (RT)- PCR after pooling could be a cost-effective method which would save both in manpower and cost especially for resource-poor countries and at a time when test kits were short in supply.

SARS-CoV-2 antibody seroprevalence in India, August-September, 2020: findings from the second nationwide household serosurvey.

BACKGROUND: The first national severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey in India, done in May-June, 2020, among adults aged 18 years or older from 21 states, found a SARS-CoV-2 IgG antibody seroprevalence of 0·73% (95% CI 0·34-1·13). We aimed to assess the more recent nationwide seroprevalence in the general population in India. METHODS: We did a second household serosurvey among individuals aged 10 years or older in the same 700 villages or wards within 70 districts in India that were included in the first serosurvey. Individuals aged younger than 10 years and households that did not respond at the time of survey were excluded. Participants were interviewed to collect information on sociodemographics, symptoms suggestive of COVID-19, exposure history to laboratory-confirmed COVID-19 cases, and history of COVID-19 illness. 3-5 mL of venous blood was collected from each participant and blood samples were tested using the Abbott SARS-CoV-2 IgG assay. Seroprevalence was estimated after applying the sampling weights and adjusting for clustering and assay characteristics. We randomly selected one adult serum sample from each household to compare the seroprevalence among adults between the two serosurveys. FINDINGS: Between Aug 18 and Sept 20, 2020, we enrolled and collected serum samples from 29 082 individuals from 15 613 households. The weighted and adjusted seroprevalence of SARS-CoV-2 IgG antibodies in individuals aged 10 years or older was 6·6% (95% CI 5·8-7·4). Among 15 084 randomly selected adults (one per household), the weighted and adjusted seroprevalence was 7·1% (6·2-8·2). Seroprevalence was similar across age groups, sexes, and occupations. Seroprevalence was highest in urban slum areas followed by urban non-slum and rural areas. We estimated a cumulative 74·3 million infections in the country by Aug 18, 2020, with 26-32 infections for every reported COVID-19 case. INTERPRETATION: Approximately one in 15 individuals aged 10 years or older in India had SARS-CoV-2 infection by Aug 18, 2020. The adult seroprevalence increased approximately tenfold between May and August, 2020. Lower infection-to-case ratio in August than in May reflects a substantial increase in testing across the country. FUNDING: Indian Council of Medical Research.

Prevalence of SARS-CoV-2 infection in India: Findings from the national serosurvey, May-June 2020.

BACKGROUND & OBJECTIVES: Population-based seroepidemiological studies measure the extent of SARS-CoV-2 infection in a country. We report the findings of the first round of a national serosurvey, conducted to estimate the seroprevalence of SARS-CoV-2 infection among adult population of India. METHODS: From May 11 to June 4, 2020, a randomly sampled, community-based survey was conducted in 700 villages/wards, selected from the 70 districts of the 21 States of India, categorized into four strata based on the incidence of reported COVID-19 cases. Four hundred adults per district were enrolled from 10 clusters with one adult per household. Serum samples were tested for IgG antibodies using COVID Kavach ELISA kit. All positive serum samples were re-tested using Euroimmun SARS-CoV-2 ELISA. Adjusting for survey design and serial test performance, weighted seroprevalence, number of infections, infection to case ratio (ICR) and infection fatality ratio (IFR) were calculated. Logistic regression was used to determine the factors associated with IgG positivity. RESULTS: Total of 30,283 households were visited and 28,000 individuals were enrolled. Population-weighted seroprevalence after adjusting for test performance was 0.73 per cent [95% confidence interval (CI): 0.34-1.13]. Males, living in urban slums and occupation with high risk of exposure to potentially infected persons were associated with seropositivity. A cumulative 6,468,388 adult infections (95% CI: 3,829,029-11,199,423) were estimated in India by the early May. The overall ICR was between 81.6 (95% CI: 48.3-141.4) and 130.1 (95% CI: 77.0-225.2) with May 11 and May 3, 2020 as plausible reference points for reported cases. The IFR in the surveyed districts from high stratum, where death reporting was more robust, was 11.72 (95% CI: 7.21-19.19) to 15.04 (9.26-24.62) per 10,000 adults, using May 24 and June 1, 2020 as plausible reference points for reported deaths. INTERPRETATION & CONCLUSIONS: Seroprevalence of SARS-CoV-2 was low among the adult population in India around the beginning of May 2020. Further national and local serosurveys are recommended to better inform the public health strategy for containment and mitigation of the epidemic in various parts of the country.

National sero-surveillance to monitor the trend of SARS-CoV-2 infection transmission in India: Protocol for community-based surveillance.

Conducting population-based serosurveillance for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) will estimate and monitor the trend of infection in the adult general population, determine the socio-demographic risk factors and delineate the geographical spread of the infection. For this purpose, a serial cross-sectional survey would be conducted with a sample size of 24,000 distributed equally across four strata of districts categorized on the basis of the incidence of reported cases of COVID-19. Sixty districts will be included in the survey. Simultaneously, the survey will be done in 10 high-burden hotspot cities. ELISA-based antibody tests would be used. Data collection will be done using a mobile-based application. Prevalence from the group of districts in each of the four strata will be pooled to estimate the population prevalence of COVID-19 infection, and similarly for the hotspot cities, after adjusting for demographic characteristics and antibody test performance. The total number of reported cases in the districts and hotspot cities will be adjusted using this seroprevalence to estimate the expected number of infected individuals in the area. Such serosurveys repeated at regular intervals can also guide containment measures in respective areas. State-specific context of disease burden, priorities and resources should guide the use of multifarious surveillance options for the current COVID-19 epidemic.

Strategic planning to augment the testing capacity for COVID-19 in India.

Background & objectives: Nearly 5,500 tests for coronavirus disease 2019 (COVID-19) had been conducted on March 31, 2020 across the Indian Council of Medical Research (ICMR)-approved public and private laboratories in India. Given the need to rapidly increase testing coverage, we undertook an exercise to explore and quantify interventions to increase the daily real-time reverse transcription-polymerase chain reaction (qRT-PCR)-based testing capacity over the next few months. The objective of this exercise was to prepare a potential plan to scale-up COVID-19 testing in India in the public sector. Methods: Potential increase in daily testing capacity of the existing public laboratories was calculated across the three base scenarios of shifts (9, 16 and 24 h). Additional testing capacity was added for each shift scenario based on interventions ranging from procurement of additional qRT-PCR machines, leveraging spare capacity on available qRT-PCR machines not drafted into COVID-19 testing, to in-laboratory process optimization efforts. Results: Moving to a 24 h working model in the existing approved laboratories can enhance the daily testing capacity to 40,464 tests/day. The capacity can be further bolstered by leveraging qRT-PCR and nucleic acid amplification test (NAAT)-based machines available with the Multidisciplinary Research Units (MRUs), National AIDS Control Organisation (NACO) and National Tuberculosis Elimination Programme (NTEP). Using combination/multiplex kits, and provision of automated RNA extraction platforms at all laboratories could also optimize run time and contribute to capacity increase by 1.5-2 times. Interpretation & conclusions: Adopting these interventions could help increase public sector's daily testing capacity to nearly 100,000-120,000 tests/day. It is important to note that utilization of the scaled-up testing capacity will require deployment of additional workforce, procurement of corresponding commodities for testing and scale-up of sample collection and transportation efforts.

The potential deployment of a pan-tuberculosis drug regimen in India: A modelling analysis.

There is increasing interest in future, highly-potent 'pan-TB' regimens against tuberculosis (TB), that may be equally effective in both drug-susceptible and rifampicin-resistant (RR) forms of TB. Taking the example of India, the country with the world's largest burden of TB, we show that adoption of these regimens could be: (i) epidemiologically impactful, and (ii) cost-saving to the national TB programme, even if the regimen itself is more costly than current TB treatment. Mathematical modelling suggests that deployment of a pan-TB regimen in 2022 would reduce the annual incidence of TB in 2030 by 23.9% [95% Bayesian credible intervals [CrI] 17.6-30.8%] if used to treat all TB cases, and by 2.30% [95% CrI 1.57-3.48%] if used to treat only RR-TB. Notably, with a regimen costing less than USD 359 (95% CrI 287-441), treating all diagnosed TB cases with the pan-TB regimen yielded greater cost-savings than treating just those diagnosed with RR-TB. One limitation of our approach is that it does not capture the risk of resistance to the new regimen. We discuss ways in which this risk could be mitigated using modern adherence support mechanisms, as well as drug sensitivity testing at the point of TB diagnosis, to prevent new resistant forms from becoming established. A combination of such approaches would be important for maximising the useful lifetime of any future regimen.

Tuberculosis treatment in the private healthcare sector in India: an analysis of recent trends and volumes using drug sales data.

BACKGROUND: There is a pressing need for systematic approaches for monitoring how much TB treatment is ongoing in the private sector in India: 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. METHODS: We used commercially available data on the sales of rifampicin-containing drugs in the private sector, adjusted for data coverage and indication of use. We examined temporal, statewise trends in volumes (patient-months) of TB treatment from 2013 to 2016. We additionally analysed the proportion of drugs that were sold in combination packaging (designed to simplify TB treatment), or as loose pills. RESULTS: Drug sales suggest a steady trend of TB treatment dispensed by the private sector, from 18.4 million patient-months (95% CI 17.3-20.5) in 2013 to 16.8 patient-months (95% CI 15.5-19.0) in 2016. Overall, seven of 29 states in India accounted for more than 70% of national-level TB treatment volumes, including Uttar Pradesh, Maharashtra and Bihar. The overwhelming majority of TB treatment was dispensed not as loose pills, but in combination packaging with other TB drugs, accounting for over 96% of private sector TB treatment in 2017. CONCLUSIONS: Our findings suggest consistent levels of TB treatment in the private sector over the past 4 years, while highlighting specific states that should be prioritized for intervention. Drug sales data can be helpful for monitoring a system as large, disorganised and opaque as India's private sector.

What would it cost to scale-up private sector engagement efforts for tuberculosis care? Evidence from three pilot programs in India.

BACKGROUND: Private providers dominate health care in India and provide most tuberculosis (TB) care. Yet efforts to engage private providers were viewed as unsustainably expensive. Three private provider engagement pilots were implemented in Patna, Mumbai and Mehsana in 2014 based on the recommendations in the National Strategic Plan for TB Control, 2012-17. These pilots sought to improve diagnosis and treatment of TB and increase case notifications by offering free drugs and diagnostics for patients who sought care among private providers, and monetary incentives for providers in one of the pilots. As these pilots demonstrated much higher levels of effectiveness than previously documented, we sought to understand program implementation costs and predict costs for their national scale-up. METHODS AND FINDINGS: We developed a common cost structure across these three pilots comprising fixed and variable cost components. We conducted a retrospective, activity-based costing analysis using programmatic data and qualitative interviews with the respective program managers. We estimated the average recurring costs per TB case at different levels of program scale for the three pilots. We used these cost estimates to calculate the budget required for a national scale up of such pilots. The average cost per privately-notified TB case for Patna, Mumbai and Mehsana was estimated to be US$95, US$110 and US$50, respectively, in May 2016 when these pilots were estimated to cover 50%, 36% and 100% of the total private TB patients, respectively. For Patna and Mumbai pilots, the average cost per case at full scale, i.e. 100% coverage of private TB patients, was projected to be US$91 and US$101, respectively. In comparison, the national TB program's budget for 2015 averages out to $150 per notified TB case. The total annual additional budget for a national scale up of these pilots was estimated to be US$267 million. CONCLUSIONS: As India seeks to eliminate TB, extensive national engagement of private providers will be required. The cost per privately-notified TB case from these pilots is comparable to that already being spent by the public sector and to the projected cost per privately-notified TB case required to achieve national scale-up of these pilots. With additional funds expected to execute against national TB elimination commitments, the scale-up costs of these operationally viable and effective private provider engagement pilots are likely to be financially viable.

Assessing tuberculosis control priorities in high-burden settings: a modelling approach.

BACKGROUND: In the context of WHO's End TB strategy, there is a need to focus future control efforts on those interventions and innovations that would be most effective in accelerating declines in tuberculosis burden. Using a modelling approach to link the tuberculosis care cascade to transmission, we aimed to identify which improvements in the cascade would yield the greatest effect on incidence and mortality. METHODS: We engaged with national tuberculosis programmes in three country settings (India, Kenya, and Moldova) as illustrative examples of settings with a large private sector (India), a high HIV burden (Kenya), and a high burden of multidrug resistance (Moldova). We collated WHO country burden estimates, routine surveillance data, and tuberculosis prevalence surveys from 2011 (for India) and 2016 (for Kenya). Linking the tuberculosis care cascade to tuberculosis transmission using a mathematical model with Bayesian melding in each setting, we examined which cascade shortfalls would have the greatest effect on incidence and mortality, and how the cascade could be used to monitor future control efforts. FINDINGS: Modelling suggests that combined measures to strengthen the care cascade could reduce cumulative tuberculosis incidence by 38% (95% Bayesian credible intervals 27-43) in India, 31% (25-41) in Kenya, and 27% (17-41) in Moldova between 2018 and 2035. For both incidence and mortality, modelling suggests that the most important cascade losses are the proportion of patients visiting the private health-care sector in India, missed diagnosis in health-care settings in Kenya, and drug sensitivity testing in Moldova. In all settings, the most influential delay is the interval before a patient's first presentation for care. In future interventions, the proportion of individuals with tuberculosis who are on high-quality treatment could offer a more robust monitoring tool than routine notifications of tuberculosis. INTERPRETATION: Linked to transmission, the care cascade can be valuable, not only for improving patient outcomes but also in identifying and monitoring programmatic priorities to reduce tuberculosis incidence and mortality. FUNDING: US Agency for International Development, Stop TB Partnership, UK Medical Research Council, and Department for International Development.

Modelling the impact of effective private provider engagement on tuberculosis control in urban India.

In India, the country with the world's largest burden of tuberculosis (TB), most patients first seek care in the private healthcare sector, which is fragmented and unregulated. Ongoing initiatives are demonstrating effective approaches for engaging with this sector, and form a central part of India's recent National Strategic Plan: here we aimed to address their potential impact on TB transmission in urban settings, when taken to scale. We developed a mathematical model of TB transmission dynamics, calibrated to urban populations in Mumbai and Patna, two major cities in India where pilot interventions are currently ongoing. We found that, when taken to sufficient scale to capture 75% of patient-provider interactions, the intervention could reduce incidence by upto 21.3% (95% Bayesian credible interval (CrI) 13.0-32.5%) and 15.8% (95% CrI 7.8-28.2%) in Mumbai and Patna respectively, between 2018 and 2025. There is a stronger impact on TB mortality, with a reduction of up to 38.1% (95% CrI 20.0-55.1%) in the example of Mumbai. The incidence impact of this intervention alone may be limited by the amount of transmission that has already occurred by the time a patient first presents for care: model estimates suggest an initial patient delay of 4-5 months before first seeking care, followed by a diagnostic delay of 1-2 months before ultimately initiating TB treatment. Our results suggest that the transmission impact of such interventions could be maximised by additional measures to encourage early uptake of TB services.