Evidence map›Paper›PMID 34399090›Full record

ArticleThe Lancet. Infectious diseases2021

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

Ramanan Laxminarayan, Chandra Mohan B, Vinay T G, K V Arjun Kumar, Brian Wahl, Joseph A Lewnard

Open access · hybridAbstract read
In one paragraph

Article in The Lancet. Infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.9field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 46 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Ramanan LaxminarayanCentre for Disease Dynamics, Economics, and Policy, New Delhi, India; Princeton University, Princeton, NJ, USA; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Chandra Mohan BDepartment of Backward Classes, Most Backward Classes and Minorities Welfare, Government of Tamil Nadu, Chennai, India.
Vinay T GMadurai District, Madurai, India.
K V Arjun KumarMadurai District, Madurai, India.
Brian WahlDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Joseph A LewnardDivision of Epidemiology and Division of Infectious Diseases and Vaccinology, School of Public Health and Center for Computational Biology, College of Engineering, University of California, Berkeley, CA, USA. Electronic address: jlewnard@berkeley.eduv.
Johns Hopkins University · USMadurai Medical College · INGovernment of Tamil Nadu · INUniversity of California, Berkeley · US

Funding

NIGMS NIH HHS MIDASNI2020-3
6 · The paper itself

Abstract

backgroundSARS-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.

methodsIn 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.

resultsBetween 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.

interpretationIn 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.

fundingThe Bill & Melinda Gates Foundation, the National Science Foundation, and the National Institute of General Medical Sciences. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.

Indexed as

AdolescentAdultAgedAged, 80 and overAsymptomatic InfectionsChildChild, PreschoolCOVID-19Cross-Sectional StudiesFemaleHumansIndiaInfantInfant, NewbornMaleMiddle Aged

Identifiers

PMID34399090
PMCPMC8363227
OpenAlexW3195977920

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.