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The COVID-19 epidemic poses a significant challenge to the operation of society and the resumption of work and production. How to quickly track the resident location and activity trajectory of the population, and identify the spread risk of COVID-19 in geospatial space has important theoretical and practical significance for controlling the spread of the virus on a large scale. In this study we take the geographical community as the research object, and use the mobile phone trajectory data to construct the spatiotemporal profile of the potential high-risk population. First, by using the spatiotemporal data collision method, identify and recover the trajectories of the people who were in the same area with the confirmed patients during the same time. Then, based on the range of activities of both cohorts (the confirmed cases and the potentially infected groups), we analyze the risk level of the relevant places and evaluate the scale of potential spread. Finally, we calculate the probabi

United statesMonte carloJohns hopkins universityJ university electrLancet global healthChina map publishing groupPublic healthSinomaps press co ltdHealth commission of sichuan provinceSichuan chuanda zhisheng system integration co ltdHealth commissionTsinghua universityChengdu university of technologyJiaotong universityHealth care managResearch methods