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

Abstract

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. Results 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-confirm...

All-cause mortality during the COVID-19 pandemic in Chennai, India: an observational study

“…However, the true burden of disease is uncertain because of limitations in surveillance. Analyses informed by population-based serosurveys suggest that reported COVID-19 deaths might underestimate true mortality by a factor of seven to ten, 1 , 2 in agreement with findings from other data sources such as household-based demographic surveys. 3 In high-income countries, all-cause mortality data from comprehensive vital registration systems have provided insight into the extent of underreporting of deaths attributable to COVID-19, as well as disparities in pandemic-associated mortality across socioeconomic and demographic groups.…”

“…During the early lockdown, reductions in mortality were more pronounced among men than among women, whereas Indian vital surveillance systems are generally more susceptible to under-ascertainment of female mortality. 34 Lastly, previous analyses have suggested greater degrees of underreporting of COVID-19 deaths among older age groups in India, 1 , 2 by contrast with the observed concentration of excess all-cause mortality among older age groups at the start of lockdowns and throughout the pandemic period. Deaths among older adults might owe, partly, to delayed presentation to medical facilities, including among individuals with silent hypoxemia.…”

“… 19 Although the study also reported higher estimates of the infection-fatality ratio in non-slum communities, findings should be interpreted cautiously due to differences in the age distribution of slum and non-slum settings and the potential for weaker case-based surveillance in slums. 1 , 2 Prevalent naturally-acquired immunity in communities hit hard by early waves of SARS-CoV-2 transmission might have affected which settings were most vulnerable to having cases and deaths after the emergence of the delta variant, which is associated with enhanced transmissibility and clinical severity. 10 It is important to note that our aggregation of deaths by PIN code area might obscure socioeconomic distinctions across communities in Chennai, where formal and makeshift housing are often closely interspersed.…”

“…6 Studies of all-cause mortality provide a valuable opportunity to overcome limitations affecting COVID-19 burden estimates from other data sources, and they provide additional context for estimation of pandemic-associated mortality by incorporating deaths potentially missed by COVID-19 surveillance, deaths attributable to delayed health-care seeking for other conditions, and deaths associated with other conditions occurring secondary to COVID-19. 2 Similar assessments should be undertaken in other low-income and middle-income settings, as well as in other parts of India, to understand demographic effects of the pandemic and to inform efforts aimed at enhancing mitigation, including expanded vaccine distribution to populations where access remains inadequate.…”

Compromised periodontal status could increase mortality for patients with COVID-19

“…In their active surveillance study of patients with COVID-19 in south India, Ramanan Laxminarayan and colleagues 1 reported an increased risk of death in patients who had a history of diabetes (adjusted hazard ratio 2·28, 95% CI 1·79–2·91), hypertension (2·08, 1·62–2·66), other circulatory disorders (3·89, 2·66–5·71), cancer (8·04, 3·47–18·65), or respiratory disorders (4·57, 2·43–8·61). Male sex, older age, and chronic kidney disease were also associated with higher mortality in individuals with COVID-19.…”