ArticleOne health (Amsterdam, Netherlands)2021
Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities.
Article in One health (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 16 citations in OpenAlex.
- Risk and predictors of severity and mortality in patients with type 2 diabetes and COVID-19 in Dubai.World journal of diabetes · 2023Article
- Association of COVID-19 with Comorbidities: An Update.ACS pharmacology & translational science · 2023Review
- A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity.Frontiers in big data · 2023Article
- Modelling the first wave of COVID-19 in India.PLoS computational biology · 2022Article
- Community seroprevalence and risk factors for SARS-CoV-2 infection in different subpopulations in Vellore, India, and their implications for future prevention.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Article
- Disability-adjusted life years (DALYs) due to the direct health impact of COVID-19 in India, 2020.Scientific reports · 2022Article
- Does money buy health? evaluation of stock market performance and economic growth in the wake of the COVID-19 pandemic.PloS one · 2022Article
- COVID-19 severity determinants inferred through ecological and epidemiological modeling.One health (Amsterdam, Netherlands) · 2021Article
- Mega festivals like MahaKumbh, a largest mass congregation, facilitated the transmission of SARS-CoV-2 to humans and endangered animals via contaminated water.International journal of hygiene and environmental health · 2021Review
- An operationally implementable model for predicting the effects of an infectious disease on a comprehensive regional healthcare system.PloS one · 2021Article
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Authors and funding
9 authors at 2 institutions in 3 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Management of coronavirus disease 2019 (COVID-19) in India is a top government priority. However, there is a lack of COVID-19 adjusted case fatality risk (aCFR) estimates and information on states with high aCFR. Data on COVID-19 cases and deaths in the first pandemic wave and 17 state-specific geodemographic, socio-economic, health and comorbidity-related factors were collected. State-specific aCFRs were estimated, using a 13-day lag for fatality. To estimate country-level aCFR in the first wave, state estimates were meta-analysed based on inverse-variance weighting and aCFR as either a fixed- or random-effect. Multiple correspondence analyses, followed by univariable logistic regression, were conducted to understand the association between aCFR and geodemographic, health and social indicators. Based on health indicators, states likely to report a higher aCFR were identified. Using random- and fixed-effects models, cumulative aCFRs in the first pandemic wave on 27 July 2020 in India were 1.42% (95% CI 1.19%-1.70%) and 2.97% (95% CI 2.94%-3.00%), respectively. At the end of the first wave, as of 15 February 2021, a cumulative aCFR of 1.18% (95% CI 0.99%-1.41%) using random and 1.64% (95% CI 1.64%-1.65%) using fixed-effects models was estimated. Based on high heterogeneity among states, we inferred that the random-effects model likely provided more accurate estimates of the aCFR for India. The aCFR was grouped with the incidence of diabetes, hypertension, cardiovascular diseases and acute respiratory infections in the first and second dimensions of multiple correspondence analyses. Univariable logistic regression confirmed associations between the aCFR and the proportion of urban population, and between aCFR and the number of persons diagnosed with diabetes, hypertension, cardiovascular diseases and stroke per 10,000 population that had visited NCD (Non-communicable disease) clinics. Incidence of pneumonia was also associated with COVID-19 aCFR. Based on predictor variables, we categorised 10, 17 and one Indian state(s) expected to have a high, medium and low aCFR risk, respectively. The current study demonstrated the value of using meta-analysis to estimate aCFR. To decrease COVID-19 associated fatalities, states estimated to have a high aCFR must take steps to reduce co-morbidities.
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