A data-driven framework to assess population dynamics during novel coronavirus outbreaks: A case study on Xiamen Island, China
Peng Wang,
Jinliang Huang
Abstract:The outbreak of the Coronavirus Disease 2019 (COVID-19) has profoundly influenced daily life, necessitating the understanding of the relationship between the epidemic’s progression and population dynamics. In this study, we present a data-driven framework that integrates GIS-based data mining technology and a Susceptible, Exposed, Infected and Recovered (SEIR) model. This approach helps delineate population dynamics at the grid and community scales and analyze the impacts of government policies, urban function… Show more
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