The present study explores the association between weather and COVID-19 pandemic in Delhi, India. The study used the data from daily newspaper releases from the Ministry of Health and Family Welfare, Government of India. Linear regression was run to understand the effect of the number of tests, temperature, and relative humidity on the number of COVID-19 cases in Delhi. The model was significantly able to predict number of COVID-19 cases, F (4,56) = 1213.61, < 0.05, accounting for 99.4% of the variation in COVID-19 cases with adjusted R = 98.8%. Maximum Temperature, average temperature and average relative humidity did not show statistical significance. The only number of tests was significantly associated with COVID-19 cases.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436072 | PMC |
http://dx.doi.org/10.1007/s12291-020-00921-6 | DOI Listing |
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