Weather Parameters Impact on Daily COVID-19 Transmission in Bangladesh

COVID-19 disease causes millions of human deaths and huge economic losses throughout the world. To limit the disease transmission numerous attempts have been made. Several studies observed associations of weather values on COVID-19 transmission. In the current study, the impacts of weather parameters on daily COVID-19 incidences have been examined in eight different cities in Bangladesh. For this purpose, a whole one-year data set of daily COVID-19 laboratory tests and tested positive identified counts have been collected from the daily press releases of the director general of health services, Dhaka, Bangladesh for all the cities. From these data sets a percentage of positive identified rate has been calculated. As well as daily weather parameter values for all the cities have been collected from the website of world weather online for the whole year. Spearman rank correlation and quasi-poisson generalized linear model have been applied in the daily weather and COVID-19 percentage of positive identified data sets to find associations between them. Significant stable negative impacts have been observed for maximum temperature (correlation estimate: -0.25 to -0.50; model estimate: -0.15 to -0.30) and air pressure (correlation estimate: -0.10 to -0.40; model estimate: -0.08 to -0.17) in both analyses. Mixed (positive, negative, and no) effects have been noticed for other weather factors (humidity, rain, wind speed, minimum temperature, and cloud) on COVID-19 cases. Also, weekly variations of COVID-19 and weather values have been examined here. Comparatively lower values have been observed for maximum temperature during December-February and for air pressure during May-August. Hence, January-February due to lower temperatures, and July-August due to lower air pressure might be more sensitive seasons to the COVID-19 outbreak in Bangladesh. These findings might help the decision-makers of the country to initiate necessary steps before the COVID-19 seasonal outbreak.