Agent-Based Simulation of Virus Testing in Certain-Exposure Time through Community Health Service Centers’ Evaluation—A Case Study of Wuhan

Abstract

Short-term and large-scale full-population virus testing is crucial in containing the spread of the COVID-19 pandemic in China. However, the uneven distribution of health service facilities in terms of space and size may lead to prolonged crowding during testing, thus increasing the chance of virus cross-infection. Therefore, appropriate control of crowd exposure time in large-scale virus testing should be an important goal in the layout of urban community health facilities. This paper uses the Quanta concept and Wells-Riley model to define the “certain-exposure time” under low cross-infection rate. Then, an agent-based simulation model was used to simulate the reasonable screening efficiency of community health service facilities during certain-exposure time at different stages of the COVID-19 pandemic and under different screening processes. Eventually, the screening efficiency was evaluated for all community health service centers in Wuhan. During the early period of the pandemic, 23.13% of communities failed to complete virus testing of community residents within 2 h of certain-exposure time, leaving approximately 56.07% of the population unscreened; during the later period of the COVID-19 pandemic, approximately 53% of communities and 75% of residents could not be screened. The results can pinpoint the distribution of community health service centers with inadequate screening capacity, facilitate targeted policymaking and planning, and effectively curb COVID-19 cross-infection during screening.