Analysis of Spatial-temporal Behavior Pattern of the Share Bike Usage during COVID-19 Pandemic in Beijing

During the epidemics of COVID-19, the whole world is experiencing a serious crisis on public health and economy. Understanding human mobility during the pandemic helps one to design intervention strategies and resilience measures. The widely used Bike Sharing System (BSS) can characterize the activities of urban dwellers over time & space in big cities but is rarely reported in epidemiological research. In this paper, we present a human mobility analyzing framework} based on BSS data, which examines the spatiotemporal characteristics of share bike users, detects the key time nodes of different pandemic stages, and demonstrats the evolution of human mobility due to the onset of the COVID-19 threat and administrative restrictions. We assessed the net impact of the pandemic by using the result of co-location analysis between share bike usage and POIs (Point Of Interest). Our results show the pandemic reduced the overall bike usage by 64.8%, then an average increase (15.9%) in share bike usage appeared afterwards, suggesting that productive and residential activities have partially recovered but far from the ordinary days. These findings could be a reference for epidemiological researches and inform policymaking in the context of the current COVID-19 outbreak and other epidemic events at city-scale.