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Modeling the Spatiotemporal Association Between COVID-19 Transmission and Population Mobility Using Geographically and Temporally Weighted Regression.
Chen, Yixiang; Chen, Min; Huang, Bo; Wu, Chao; Shi, Wenjia.
  • Chen Y; School of Geographic and Biologic Information Nanjing University of Posts and Telecommunications Nanjing China.
  • Chen M; Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing China.
  • Huang B; School of Geographic and Biologic Information Nanjing University of Posts and Telecommunications Nanjing China.
  • Wu C; Department of Geography and Resource Management The Chinese University of Hong Kong HongKong China.
  • Shi W; School of Geographic and Biologic Information Nanjing University of Posts and Telecommunications Nanjing China.
Geohealth ; 5(5): e2021GH000402, 2021 May.
Article in English | MEDLINE | ID: covidwho-1240768
ABSTRACT
The ongoing Coronavirus Disease 2019 (COVID-19) has posed a serious threat to human public health and global economy. Population mobility is an important factor that drives the spread of COVID-19. This study aimed to quantitatively evaluate the impact of population flow on the spread of COVID-19 from a spatiotemporal perspective. To this end, a case study was carried out in Hubei Province, which was once the most affected area of COVID-19 outbreak in Mainland China. The geographically and temporally weighted regression (GTWR) model was applied to model the spatiotemporal association between COVID-19 epidemic and population mobility. Two patterns of population flows, including the population inflow from Wuhan and intra-city population movement, were considered to construct explanatory variables. Results indicate that the GTWR model can reveal the spatial-temporal-varying relationships between COVID-19 and population mobility. Moreover, the association between COVID-19 case counts and population movements presented three stages of temporal variation characteristics due to the virus incubation period and implementation of strict lockdown measures. In the spatial dimension, evident geographical disparities were observed across Hubei Province. These findings can provide policymakers useful knowledge about the impact of population movement on the spatio-temporal transmission of COVID-19. Thus, targeted interventions, if necessary in certain time periods, can be implemented to restrict population flow in cities with high transmission risk.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Geohealth Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Geohealth Year: 2021 Document Type: Article