抽象的

A Cross Sectional Study on the Correlation between Climate Indicators and Covid-19 Pandemic in 22 Major States of India

Manikanta Bhoi

This study aims to analyse the correlation between climate and covid-19 pandemic in 16 major states of India. This study employed a secondary data analysis of surveillance data of covid-19 from NDTV Corona Virus website (https://www.ndtv.com/coronavirus/fullcoverage) and weather from the National Centers for Environmental Information (NCEI)( https://www.ncei.noaa.gov/access/search). The components of weather include minimum temperature (0C), maximum temperature (0C), temperature average (0C), and amount of rainfall (mm). The statistics such as Spearman-rank correlation test, person correlation, Kendall correlation was used for data analysis. Among the components of the weather, only temperature average (0C), was significantly correlated with covid-19 pandemic (r=0.392; p<.01) from the month of January to May but from May to October when the rainfall comes in to picture only rainfall was significantly correlated with covid-19 pandemic (r =0.392; p<.01) . The finding serves as an input to reduce the incidence rate of covid-19 in 16 major states of India in prospective of climate factor. The findings of this study will help World Health Organization and health regulators such as Center for Disease Control (CDC) to combat COVID-19 in India and the rest of the world.