COVID-19 확진자 수에 미치는 서울시 행정동별 도시특성요인의 영향요인 선별 및 영향력 분석

다국어 초록 (Multilingual Abstract)

The purpose of this study is to analyze urban characteristics that affect the number of confirmed COVID-19 cases, and to identify and analyze the spatial distribution and impact by region. The results of the multi-scale geographically weighted regression model (MGWR) model analysis that can precisely reflect spatial heterogeneity by variable showed that the significant impact of each variable on the number of confirmed COVID-19 cases varied depending on regional characteristics. Population density and the proportion of commercial and business increased the risk of infection in commercial centers, but showed a low risk in residential areas such as Nowon-gu. The proportion of old houses acted as a factor that reduced the risk of infection due to low mobility and a tendency to stay at home. The proportion of single-family houses increased the risk of infection in transportation hubs, and the density of bus stops and subway stations reduced the risk of infection by dispersing the floating population in residential centers. These results suggest that customized quarantine policies that reflect regional characteristics, expansion of public infrastructure, and expansion of open spaces are necessary. It is significant in that it can provide basic data for establishing response strategies suited to regional characteristics, and can be used as a reference for responding to similar public health crises in the future.