Biography: Dr. Nan Zhang is an Associate Professor in Beijing University of Technology. He works on city-scale infectious disease transmission, human behavior detection based on machine learning, human health in indoor environments, and energy conservation under COVID-19 pandemic. As the first author, he has published 30 SCI journal papers on Environment International (IF=9.6), Clinical Infectious Diseases (IF=9.1), etc, with 800 citations. He received the Best Paper Award of Building and Environment (IF=6.7) in 2020; the Distinguished Paper of Risk Analysis in 2017; the Best Paper Award of the 3rd International Conference on Multimedia Technology (ICMT 2013).

Topic: Real Human Behavior Based City-scale COVID-19 Transmission

Abstract: By the end of October 2021, COVID-19 had spread to over 230 countries, with more than 240 million confirmed cases and 5.0 million deaths. To control infection spread with the least disruption to economic and societal activities, it is crucial to implement the various interventions effectively. In this study, we developed an agent-based SEIR model, using real demographic, geographic, and human-behavior data from Hong Kong, to analyze the efficiency of various intervention strategies in preventing infection by the SARS-CoV-2 virus. Close contact route including short-range airborne is considered as the main transmission routes for COVID-19 spread. Contact tracing is not that useful if all other interventions have been fully deployed. The number of infected individuals could be halved if people reduced their close contact rate by 25%. For reducing transmission, students should be prioritized for vaccination rather than retired older people and preschool aged children. Home isolation, and taking the nucleic acid test (NAT) as soon as possible after symptom onset, are much more effective interventions than wearing masks in public places. Temperature screening in public places only disrupted the infection spread by a small amount when other interventions have been fully implemented. Our results may be useful for other highly populated cities, when choosing their intervention strategies to prevent outbreaks of COVID-19 and similar diseases.