Determining Role of Air Temperature in Predicting and Controlling COVID-19 Risk Levels Anywhere Anytime Using Multiple Modelling Analyses

Abstract

Background: Novel coronavirus disease (COVID-19) is an ongoing pandemic with no cure. It is imperative to employ low-cost interventions to contain its spread. In the present study, the role of ambient temperature (AT) in predicting and controlling the risk of COVID-19 spread were evaluated. Methods: Data on monthly new deaths or new cases per million population (MDPM or MCPM) and monthly cumulated days with more cases than the previous day (DI) from March 1 to May 30, 2020 were collected. COVID-19 data of all 118 countries with population over five million were analyzed. Findings: Monthly average AT negatively correlated with the transmission parameters. A significant decrease in transmission was observed when AT reached above 20 oC . Monthly average AT of countries with MDPM 25 oC were considered as high, medium, and low risk AT. Furthermore, MDPM in countries with AT 25 oC in March, April, and May, respectively. MDPM high-risk rates in countries with AT >25 oC were 0, 8, and 4%, and the low-risk rates were 100, 82, and 88%, respectively. In countries with AT <20 oC, the trends were opposite. Interpretations : Authorities and the general population can evaluate COVID-19 risk level anywhere anytime based on local AT. According to our results, setting indoor temperature to 25 oC could replace social distancing and business shutdown to contain the spread in most situations. However, factors such as population density, humidity, and others could limit the effectiveness of controlling AT. Ventilation and sanitizing the air with ultraviolet light in nonbusiness hours may be additionally effective. Funding: The National Natural Science Foundation of China. Declaration of Interests: The authors declare no competing interests.