Convergence of Comorbidity and COVID-19 Infection to Fatality: An Investigation Based on Health Assessment and Vaccination among Older Adults in Kerala
Abstract
Objective
To investigate the impact of age, comorbidity, and vaccination in the fatality of older COVID-19 patients in the state of Kerala, India, based on their comorbidity and vaccination status.
Methods
It is a cross sectional study adopting a mixed method approach conducted among the older population in Kerala. To study the health profile, 405 older people were surveyed, and 102 people were interviewed in-depth at their households, between June to November 2020. The results of the study were triangulated with elderly COVID-19 fatality data, available from the citizen-science dashboards of the research team and Department of Health, Kerala. Vaccination data was retrieved from <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://cowin.gov.in">cowin.gov.in</ext-link> to study its impact. The data was analysed using the IBM SPSS version 22.0.
Results
Age is a predictor of COVID-19 fatality. Diabetes, hypertension, heart diseases, CKD and COPD are the significant predictors of elderly COVID-19 fatality. The current comorbidity profile of the total older population matches with the comorbidities of the COVID-19 elderly death cases. Vaccination has impacted COVID-19 mortality after vaccinating 65 percent (first dose) of the elderly.
Conclusions
Age and comorbidities can predict potential fatality among older COVID-19 patients. Timely and accurate health data and better knowledge of high-risk factors such as comorbidity can easily guide the healthcare system and authorities to efficient prevention and treatment methodologies. Knowledge on prevailing NCDs can drive early preparedness before it converges with an epidemic like the present zoonotic disease. Priority must be given for elderly vaccination to bring down the mortality rates.
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