Intracity Pandemic Risk Evaluation Using Mobile Phone Data: The Case of Shanghai during COVID-19

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has provided an opportunity to rethink the development of a sustainable and resilient city. A framework for comprehensive intracity pandemic risk evaluation using mobile phone data is proposed in this study. Four steps were included in the framework: identification of high-risk groups, calculation of dynamic population flow and construction of a human mobility network, exposure and transmission risk assessment, and pandemic prevention guidelines. First, high-risk groups were extracted from mobile phone data based on multi-day activity chains. Second, daily human mobility networks were created by aggregating population and origin-destination (OD) flows. Third, clustering analysis, time series analysis, and network analysis were employed to evaluate pandemic risk. Finally, several solutions are proposed to control the pandemic. The outbreak period of COVID-19 in Shanghai was used to verify the proposed framework and methodology. The results show that the evaluation method is able to reflect the different spatiotemporal patterns of pandemic risk. The proposed framework and methodology may help prevent future public health emergencies and localized epidemics from evolving into global pandemics.

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