Effect of Temperatures, Humidity and Population Density on the Spreading of Covid-19 at 70 Cities/Provinces

Jishan Ahmed; Md. Hasnat Jaman; Goutam Saha; Pratyya Ghosh

Working Paper Article Version 1 This version is not peer-reviewed

Version 1 : Received: 22 June 2020 / Approved: 24 June 2020 / Online: 24 June 2020 (09:44:59 CEST)

The main goal of this article is to demonstrate the impact of environmental data on the spreading of Covid-19. In this research, data has been collected from 70 cities/provinces that are affected by Covid-19. Here, environmental data refers to temperatures, humidity and population density in each of these cities/provinces. This data has been analyzed using statistical models such as Poisson, Quasi-Poisson and negative Binomial. It is found that a negative Binomial regression model is the best fit for our data. Our results reveal that average high temperature is the vital factor to slow down the spread of Covid-19. In addition, higher population density found to be an important factor for the quick spreading of Covid-19 where it is quite impossible to maintain the social distance and the virus can spread easily.

temperatures; humidity; population density; environment; Covid-19; generalized linear model

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Effect of Temperatures, Humidity and Population Density on the Spreading of Covid-19 at 70 Cities/Provinces

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