Inter-State Heterogeneity of The Burden of Novel Coronavirus Disease In India: An Analysis of the Correlating Factors - Thakur, Sanjay Kumar; Sinha, Anil Kumar; Kalra, Rupinder; Singh, Garima; Jahan, Aarzoo; Sarin, Namrata; Singh, Sompal (International Journal of Scientific Research in Biological Sciences, 2021)
The number of cases of novel coronavirus 2019 (COVID-19) in India has been increasing since March 2020. However, a significant inter-state heterogeneity is evident. The present study was aimed at analysing the various factors that could correlate with this heterogeneity. This analytical cross-sectional study included the COVID-19 related data of various Indian states as on 14th Oct 2020. Data of the demographic factors and other infectious diseases were extracted from various websites. Correlation between these factors and COVID-19 confirmed cases and deaths was assessed (Pearson’s correlation coefficient). After a check for multi-collinearity, a stepwise linear regression analysis using R software was done for the final model of confirmed cases as well as deaths due to COVID-19. Pearson’s correlation coefficient showed a significant correlation between COVID-19 cases and deaths due to dengue while COVID-19 deaths demonstrated correlation with number of chikungunya cases and deaths due to dengue. The linear regression analysis gave the final model explaining COVID-19 deaths with total population, population density, other infectious diseases, average minimum temperature, and population above 60 years. The present study highlights a possible association between COVID-19 epidemiology and population density as well as with other infections like chikungunya, dengue, and malaria in India. Number of COVID-19 deaths are also related to population above 60 years. Knowledge of these related factors will help in prediction of health care need of states and better management of pandemic.