Classification and Estimation of Densely Population Areas for Prevention of COVID-19 Infection in Narashino, Chiba

Abstract

Since Dec. 2019, people’s behavior has been drastically changed caused by the epidemic of the coronavirus disease (COVID-19) pandemic. In Japan, since infections are commonly reported on facilities where many people gather, the government recommends that to take thorough infection prevention measures in such facilities. To reveal densely populated areas is important for planning infection prevention measures in each region. Therefore, in this study, we estimate a relative population density of facilities in Narashino, Chiba. Specifically, densely populated areas are calculated by the kernel density estimation based on the point-type floating population data. Moreover, we specify and classify facility types that infection prevention measures should be reinforced by the relative population density. Experimental results imply that the heavy restriction of people’s behavior is important in terms of infection prevention.