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

• Main Authors: Nikunj Kansara, Ashok B Nandapurkar, Rahul Maniyar, Arun Kumar Yadav
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2021-01-01
• Series: Indian Journal of Public Health
• Subjects: comorbidities; coronavirus disease; mortality; secondary analysis; surveillance
• Online Access: http://www.ijph.in/article.asp?issn=0019-557X;year=2021;volume=65;issue=1;spage=64;epage=66;aulast=Kansara
• ISSN: 0019-557X

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.