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Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities.
Singh, Balbir B; Ward, Michael P; Lowerison, Mark; Lewinson, Ryan T; Vallerand, Isabelle A; Deardon, Rob; Gill, Jatinder P S; Singh, Baljit; Barkema, Herman W.
  • Singh BB; Centre for One Health, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab 141004, India.
  • Ward MP; Sydney School of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden 2570, NSW, Australia.
  • Lowerison M; Dept. of Veterinary Microbiology, University of Saskatchewan, Saskatoon, Canada.
  • Lewinson RT; Sydney School of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden 2570, NSW, Australia.
  • Vallerand IA; Dept. of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary T2N 4N1, AB, Canada.
  • Deardon R; One Health at UCalgary, University of Calgary, 3330 Hospital Drive NW, Calgary T2N 4N1, Canada.
  • Gill JPS; Dept. of Medicine, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary T2N 4N1, Canada.
  • Singh B; Dept. of Medicine, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary T2N 4N1, Canada.
  • Barkema HW; Dept. of Production Animal Health, Faculty of Veterinary Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary T2N 4N1, Canada.
One Health ; 13: 100283, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1284430
Preprint
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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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Randomized controlled trials / Reviews Language: English Journal: One Health Year: 2021 Document Type: Article Affiliation country: J.onehlt.2021.100283

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Randomized controlled trials / Reviews Language: English Journal: One Health Year: 2021 Document Type: Article Affiliation country: J.onehlt.2021.100283