Effect of temperature on the infectivity of COVID-19
Mugen Ujiie, Shinya Tsuzuki, Norio Ohmagari
Abstract
OBJECTIVES: To evaluate the influence of temperature on the infectivity of COVID-19 in Japan. METHODS: We evaluated the relationship between the accumulated number of patients per 1,000,000 population and the average temperature in February 2020 in each prefecture by Poisson regression analysis. We introduced the monthly number of inbound visitors from China in January 2020 in each prefecture and old-age dependency ratio as additional explanatory variables in the model. RESULTS: Monthly inbound visitors from China in January 2020, old-age dependency ratio, and mean temperature in February 2020 are associated with the cumulative number of COVID-19 case on March 16, 2020. CONCLUSIONS: Our analysis showed a possible association between low temperature and increased risk of COVID-19 infection. Further evaluation would be desirable at a global level.