Before revision:  Thus, in this study, based on big human mobility data and city POI data, we design an interactive visual analytics system called EpiMob (Epidemic Mobility) to intuitively demonstrate and simulate how the human mobility, as well as the number of infected people , will change according to a certain restriction policy or a combination of policies . EpiMob is made up of a set of coupled modules: a data processing module for data cleansing, interpolation, and indexing; a simulation module based on a modified trajectory-based SEIR model; an interaction visualization module to interactively visualize the analytical results in light of user's settings. Through multiple case studies for the biggest city of Japan (i.e., Tokyo) and domain expert interviews , we demonstrate that our system can be beneficial to give an illustrative insight in measuring and comparing the effects of different human mobility restriction policies for epidemic control.
After revision:  Thus, in this study, based on big human mobility data and city POI data, we design an interactive visual analytics system called EpiMob (Epidemic Mobility) to intuitively demonstrate and simulate how the human mobility, as well as the number of infected people , will change according to a certain restriction policy or a combination of policies (e.g., regional lockdown, telecommuting, screening). Users can conveniently designate the spatial and temporal ranges for different mobility restriction policies, and the result reflecting the infection situation under different policies is dynamically displayed and can be flexibly compared. We completed multiple case studies for the biggest city of Japan (i.e., Tokyo) and domain expert interviews , we demonstrate that our system can be beneficial to give an illustrative insight in measuring and comparing the effects of different human mobility restriction policies for epidemic control.