The spread of COVID-19 has seriously affected the normal life of people. Early detection and isolation of potentially susceptible population can effectively control the spread of the virus.

Recently, a team led by Professor Li Tianrui from the School of Information Science and Technology of the University and JD iCity have jointly proposed a novel solution for the measurement of spatio-temporal infection rate based on human motion trajectory, which can fully describe the infection risk of the population affected by the motion trajectory of the infected. Furthermore, with the formulation of a highly efficient spatio-temporal index, the susceptible population can be quickly located in line with a large number of motion trajectories. Experimental results based on real and synthetic trajectory data sets have proved the effectiveness of the solution.

Location of Susceptible Population