4.7 Article

SARS-CoV-2 infection and mortality during the first epidemic wave in Madurai, south India: a prospective, active surveillance study

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LANCET INFECTIOUS DISEASES
卷 21, 期 12, 页码 1665-1676

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ELSEVIER SCI LTD
DOI: 10.1016/S1473-3099(21)00393-5

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  1. Bill & Melinda Gates Foundation
  2. National Science Foundation
  3. National Institute of General Medical Sciences

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A large-scale SARS-CoV-2 surveillance programme in Madurai, India revealed equal risk of asymptomatic infection among children, teenagers, and working-age adults, with increasing risk of infection and death associated with older age and comorbidities.
Background SARS-CoV-2 has spread substantially within India over multiple waves of the ongoing COVID-19 pandemic. However, the risk factors and disease burden associated with COVID-19 in India remain poorly understood. We aimed to assess predictors of infection and mortality within an active surveillance study, and to probe the completeness of case and mortality surveillance. Methods In this prospective, active surveillance study, we used data collected under expanded programmatic surveillance testing for SARS-CoV-2 in the district of Madurai, Tamil Nadu, India (population of 3 266 000 individuals). Prospective testing via RT-PCR was done in individuals with fever or acute respiratory symptoms as well as returning travellers, frontline workers, contacts of laboratory-confirmed COVID-19 cases, residents of containment zones, patients undergoing medical procedures, and other risk groups. Standardised data collection on symptoms and chronic comorbid conditions was done as part of routine intake. Additionally, seroprevalence of anti-SARS-CoV-2 immunoglobulin G was assessed via a cross-sectional survey recruiting adults across 38 clusters within Madurai District from Oct 19, 2020, to Nov 5, 2020. We estimated adjusted odds ratios (aORs) for positive RT-PCR results comparing individuals by age, sex, comorbid conditions, and aspects of clinical presentation. We estimated case-fatality ratios (CFRs) over the 30-day period following RT-PCR testing stratified by the same variables, and adjusted hazard ratios (aHRs) for death associated with age, sex, and comorbidity. We estimated infection-fatality ratios (IFRs) on the basis of age-specific seroprevalence. Findings Between May 20, 2020, and Oct 31, 2020, 13.5 diagnostic tests were done per 100 inhabitants within Madurai, as compared to 7.9 tests per 100 inhabitants throughout India. From a total of 440 253 RT-PCR tests, 15 781 (3.6%) SARS-CoV-2 infections were identified, with 8720 (5.4%) of 160 273 being positive among individuals with symptoms, and 7061 (2.5%) of 279 980 being positive among individuals without symptoms, at the time of presentation. Estimated aORs for symptomatic RT-PCR-confirmed infection increased continuously by a factor of 4.3 from ages 0-4 years to 80 years or older. By contrast, risk of asymptomatic RT-PCR-confirmed infection did not differ across ages 0-44 years, and thereafter increased by a factor of 1.6 between ages 45-49 years and 80 years or older. Seroprevalence was 40.1% (95% CI 35.8-44.6) at age 15 years or older by the end of the study period, indicating that RT-PCR clinical testing and surveillance testing identified only 1.4% (1.3-1.6%) of all infections in this age group. Among RT-PCR-confirmed cases, older age, male sex, and history of cancer, diabetes, other endocrine disorders, hypertension, other chronic circulatory disorders, respiratory disorders, and chronic kidney disease were each associated with elevated risk of mortality. The CFR among RT-PCR-confirmed cases was 2.4% (2.2-2.6); after age standardisation. At age 15 years or older, the IFR based on reported deaths was 0.043% (0.039-0.049), with reported deaths being only 11.0% (8.2-14.5) of the expected count. Interpretation In a large-scale SARS-CoV-2 surveillance programme in Madurai, India, we identified equal risk of asymptomatic infection among children, teenagers, and working-age adults, and increasing risk of infection and death associated with older age and comorbidities. Establishing whether surveillance practices or differences in infection severity account for gaps between observed and expected mortality is of crucial importance to establishing the burden of COVID-19 in India. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.

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