Forthcoming Articles https://www.dqxxkx.cn EN-US https://www.dqxxkx.cn/EN/current.shtml https://www.dqxxkx.cn 5 st wave of COVID-19 epidemic in 2020. It is critical to evaluate the effectiveness of these NPIs for future epidemic control. However, as a variety of NPIs were applied together in practice, it is difficult to evaluate the effectiveness of a single type of intervention by epidemiological observation. Taking Shenzhen city as an example, this study used a spatially explicit agent-based model by integrating mobile phone location data, travel survey data, building survey data and other multi- source spatiotemporal big data to evaluate the effectiveness of different types of NPIs in the suppression of the 1^st wave of COVID-19 epidemic in Shenzhen. The simulation results show that the peak of the epidemic would have appeared on the 127^th day since Jan 1^st of 2020, resulting in an average of 72.26% of the population to be infected without any interventions. In the 1^st wave of Shenzhen epidemic, except for the hospitalization of confirmed cases and intercity traffic restrictions, the stay- at- home order was the most effective one, followed by comprehensive isolation and quarantine measures (for close contacts, imported population and suspected cases), mask wearing, and orderly resumption of work. The stay- at-home order and comprehensive isolation and quarantine measures can effectively control the large-scale outbreak of the COVID-19, which are identified as the core measures; Mask wearing and orderly resumption of work can only reduce the overall infection size and delay the epidemic peak, which are identified as secondary measures. Considering the socioeconomic costs and the receding compliance to interventions in the post- epidemic period, this study suggests that the core measures and secondary measures should be combined to control the sporadic cases. Specifically, the local government can give the highest priority to isolation and quarantine measures for confirmed cases and high- risk individuals, complemented by mask wearing. In addition, our model can reveal the high- risk infection areas at a community level, which can help deploy control measures within an urban environment. In summary, this study demonstrated the advantages of integrating spatiotemporal big data and agent- based models to simulate the spread processes of infectious diseases in an urban environment: it can not only simulate the evolving processes of an epidemic at a finegrained scale, but also evaluate the effectiveness of the NPIs at an individual level and for activity- travel behaviors, which can be useful for precise intervention.]]>