Abstract

It is believed that weather conditions such as temperature and humidity have effects on COVID-19 transmission. However, these effects are not clear due to the limited observations and difficulties in separating impact of social distancing. COVID-19 data and social-economic features of 1236 regions in the world (1112 regions at the provincial level and 124 countries with the small land area) were collected. Large-scale satellite data was combined with these data with a regression analysis model to explore the effects of temperature and relative humidity on COVID-19 spreading, as well as the possible transmission risk by seasonal cycles. The result shows that temperature and relative humidity are negatively correlated with COVID-19 transmission throughout the world. Government intervention (e.g. lockdown policies) and lower population movement contributed to decrease the new daily case ratio. Weather conditions are not the decisive factor in COVID-19 transmission, in that government intervention as well as public awareness, could contribute to the mitigation of the spreading of the virus. So, it deserves a dynamic government policy to mitigate COVID-19 transmission in winter.

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