COUPLING INFECTIOUS DISEASE MODEL AND GIS FOR LIVING MATERIAL SUPPLY ANALYSIS DURING COVID-19 OUTBREAK – TAKING SHENZHEN AS AN EXAMPLE
- 1School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
- 2Guangdong Key Laboratory of Urban Informatics, Shenzhen Key Laboratory of Spatial Smart Sensing and Service, Shenzhen 518060, China
- 3Key Laboratory for Geo‐Environmental Monitoring of Great Bay Area, MNR, Shenzhen 518060, China
Keywords: Infectious disease simulation, GIS, spatial analysis, material guarantee, supply and demand
Abstract. The COVID-19 epidemic has posed a grave threat to human life. The stay-at-home quarantine is an effective method of minimizing physical contact and the risk of COVID-19 transmission. However, the supply of living materials (such as meat, vegetables, grain, and oil) has become a great challenge as residents' activities have been restricted. In this paper, we present a spatial analysis framework for the supply of living materials during COVID-19 outbreak by coupling an infectious disease model with geographic information system (GIS). First, a virus spreading spatial simulation model is developed by combining cellular automata (CA) and Susceptible-Exposed-Infected-Recovered-Death (SEIRD) to estimate COVID-19's spreading under various scenarios. Second, the demand and supply of living materials in the impacted residents are calculated. Finally, the imbalance of the supply and demand of the living materials is assessed. We conduct experiments in Shenzhen. The experimental results show that localities with supply-demand mismatches are primarily concentrated in the southwest of Bao'an District, the southern of Longhua District, and Longgang District. Additionally, the spatial distribution of the mismatch level between supply and demand for living materials in Shenzhen exhibits a significant agglomeration effect, manifested as "low-low" and "high-high" agglomeration. The spatial agglomeration effect of material mismatch has increased with the spread of the epidemic. These results support the prevention and control of the COVID-19 spreading.