Relationship between COVID-19 infection rates and air pollution, geo-meteorological, and social parameters

04, January 2021 | Bangladesh

Authors:

Abstract

Like all infectious diseases, the infection rate of COVID-19 is dependent on many variables. In order to effectively prepare a localized plan for infectious disease management, it is important to find the relation- ship between COVID-19 infection rate and other key variables. This study aims to understand the spatial relationships between COVID-19 infection rate and key variables of air pollution, geo-meteorological, and social parameters in Dhaka, Bangladesh. The relation- ship was analyzed using Geographically Weighted Re- gression (GWR) model and Geographic Information System (GIS) by means of COVID-19 infection rate as a dependent variable and 17 independent variables. This study revealed that air pollution parameters like PM2.5 (p < 0.02), AOT (p < 0.01), CO (p < 0.05), water vapor (p < 0.01), and O3 (p < 0.01) were highly correlated with COVID-19 infection rate while geo-meteorological pa- rameters like DEM (p < 0.01), wind pressure (p < 0.01), LST (p < 0.04), rainfall (p < 0.01), and wind speed (p < 0.03) were also similarly associated. Social param- eters like population density (p < 0.01), brickfield den- sity (p < 0.02), and poverty level (p < 0.01) showed high coefficients as the key independent variables to COVID- 19 infection rate. Significant robust relationships be- tween these factors were found in the middle and south- ern parts of the city where the reported COVID-19 infection case was also higher. Relevant agencies can utilize these findings to formulate new and smart strat- egies for reducing infectious diseases like COVID-19 in Dhaka and in similar urban cities around the world. Future studies will have more variables including eco- logical, meteorological, and economical to model and understand the spread of COVID-19.