Evolution of COVID-19 mortality risk: A retrospective study of three epidemic waves in Faridabad, India

Purpose

The study aimed to compare the sociodemographic, comorbidity, and clinical variables associated with coronavirus disease 2019 (COVID-19) mortality across three distinct epidemic waves in Faridabad, India.

Methods

A retrospective analysis of the medical records of patients admitted with COVID-19 was conducted at a tertiary care center at Faridabad, India. COVID-19 epidemic waves were categorized into the first wave (April 2020–January 2021), second wave (March 2021–June 2021), and third wave (December 2021–February 2022). Sociodemographic, comorbidity, and clinical parameters were assessed for their association with mortality in each of the waves by the Chi-square test. The Cochran–Armitage test for trend was used to assess changes in these associations with respect to the mortality rate across the epidemic waves.

Results

A total of 5217 patient records were assessed, with 4066 in the first wave, 895 in the second wave, and 256 in the third wave. Across all waves, comorbidities (diabetes and hypertension), multimorbidity, severe disease (requiring intensive care unit admission and ventilator support) were consistently associated (p < 0.05) with higher mortality. While sociodemographic factors were significant (p < 0.05) in the first two waves, their impact diminished in the third. Clinical symptoms, particularly ‘cold and flu’ showed consistent significance (p < 0.05) across all waves. COVID-19 mortality trend peaked in the second wave, disproportionately (p < 0.05) affecting females, older patients, and those with comorbidities or severe symptoms.

Conclusions

Understanding the shifting risk factors across COVID-19 epidemic waves is crucial for targeted interventions. Prioritizing high-risk groups, particularly during peak waves, can optimize resource allocation and minimize mortality.