With nearly 31 million reported COVID-19 cases and 410 000 deaths, India is one of the countries with the heaviest burden of COVID-19 cases and deaths. There is near-universal consensus that the country's reported morbidity and mortality data are substantial underestimates. The majority of the morbidity and mortality in India are a consequence of the second wave, which started in March, 2021, land which is attributable largely to the delta SARS-CoV-2 variant. There is some suggestion that India was largely spared from the COVID-19 disease burden in the first wave of the pandemic that began in June, 2020. In the absence of good vital registration data and electronic health records that are available in more well resourced countries, good-quality surveillance data are relied upon to estimate disease burden. In this context, the study by Ramanan Laxminarayan and colleagues in The Lancet Infectious Diseases makes a valuable contribution by reporting results from a large-scale active SARS-CoV-2 surveillance programme in Madurai, Tamil Nadu, during the first wave of the pandemic. In this study, prospective testing through RT-PCR was done from May 20, 2020, to Oct 31, 2020, for individuals with fever or acute respiratory symptoms as well as selected groups of individuals at high risk of COVID-19, including returning travellers, frontline workers, contacts of laboratory-confirmed COVID-19 cases, residents of containment zones, and patients having medical procedures. The authors also report data from a cross-sectional serosurvey done from Oct 19, 2020, to Nov 5, 2020.


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Li, Y. & Nair, H. 2021, 'How reliable are COVID-19 burden estimates for India?', The Lancet Infectious Diseases. https://doi.org/10.1016/S1473-3099(21)00422-9

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Last updated: 19 May 2023
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