Main Article Content
OBJECTIVE: To investigate the impact of age, comorbidity, and vaccination in the fatality of older COVID-19 patients in the state of Kerala, India.
METHODS: A cross sectional study, adopting a mixed method approach was used and conducted among the older population in Kerala. To study the health profile of study participants 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 the Co-WIN government website (cowin.gov.in) to study its impact. The data was analyzed using the IBM SPSS version 22.0.
RESULTS: Age is a predictor of COVID-19 fatality. Diabetes, hypertension, CAD, CKD and COPD are the significant predictors of elderly COVID-19 fatality in Kerala. The current comorbidity profile of the total older population matches with the comorbidities of the COVID-19 elderly death cases. CFR and IFR have declined even when the CMR is high in the second wave of COVID-19 with more deaths. This is attributable to vaccination even though there exists a lesser chance for breakthrough infection.
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. Vaccination is an effective tool in preventing infection compared to the unvaccinated even though the chance for breakthrough infection is there, particularly, in people with comorbidities.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.