Geographic information system methods tell spatiotemporal transmission and its drivers of COVID-19 in Wuhan, China at street-level

Abstract

Background: No study has revealed spatial transmission characteristics of COVID-19 in Wuhan, China. We aimed to analyze the spatiotemporal spread of COVID-19 in Wuhan and its influence factors.Methods: Information of 32,682 COVID-19 cases reported through March 18 were extracted from the national infectious disease surveillance system. Geographic information system methods were applied to analysis transmission of COVID-19 and its influence factors in different periods.Results: We found decrease in effective reproduction number (Rt) and COVID-19 related indicators through taking a series of effective public health measures including restricting traffic, centralized quarantine and strict stay-at home policy. The distribution of COVID-19 cases number in Wuhan showed an obvious global aggregation and a local aggregation in central urban areas, but such aggregations was decreased in the later period of the epidemic. In addition, the analysis at streets-level suggested population density and the number of hospitals were influence factors of spatial difference.Conclusions: The epidemic situation showed obvious global and local spatial aggregations. High population density and directional flow of the Population to hospitals may account for the aggregations. Strong quarantine measures and restrictions on movement of residents in Wuhan make the epidemic under control in a short time.