Prediction of mortality by age and multi-morbidities among confirmed COVID-19 patients: Secondary analysis of surveillance data in Pune, Maharashtra, India

Indian J Public Health. 2021 Jan-Mar;65(1):64-66. doi: 10.4103/ijph.IJPH_1096_20.

Abstract

Maharashtra has reported the maximum number of COVID-19 cases in India. This study was conducted to describe the predictors of death among the confirmed cases of COVID-19 by carrying out a secondary analysis of surveillance data of 11,278 lab-confirmed COVID-19 cases and admitted in dedicated COVID hospitals and dedicated COVID health-care centers between April 4, 2020, and July 17, 2020, in Pune district of Maharashtra. A total of 1270 (11.2%, 95% confidence interval [CI]: 10.7-11.9) deaths out of 11,278 patients were reported. Out of the 1270 deaths, 825 (65%) were male and 788 (62%) had one or more comorbidities. Logistic regression was done for predictors of death, and males (adjusted odds ratio: 1.6, 95% CI: 1.4-1.8), those with symptoms at the time of admission (adjusted odds ratio: 2.9, 95% CI: 2.5-3.4), and those with the presence of two or more comorbidities (adjusted odds ratio: 2.7, 95% CI: 2.2-3.4) were having a higher risk of death.

Keywords: Comorbidities; coronavirus disease; mortality; secondary analysis; surveillance.

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • COVID-19 / epidemiology*
  • COVID-19 / mortality
  • COVID-19 / physiopathology*
  • Comorbidity
  • Female
  • Humans
  • India / epidemiology
  • Logistic Models
  • Male
  • Middle Aged
  • Risk Factors
  • SARS-CoV-2
  • Sex Distribution