Transmission pattern and city-based network of COVID-19 during sporadic outbreaks

Detecting the pattern and impact factors of the persistent COVID-19 spread is essential to the national response to emerging infectious diseases in the future. Using the inter-city trajectories of the first confirmed case for each sporadic outbreak, this study constructed a city-level COVID-19 transmission network in China. The exponential random graph model (ERGM) was used to detect the COVID-19 spread pattern and examined the impact of socio-economy, city connectivity, and their interaction on COVID-19 transmission. Results demonstrated that COVID-19 transmission was strongly associated with intensive inter-city population flow, geographical proximity, and quality hospitals. During sporadic outbreaks, road or air port cities became epicentres with strong centrality. The homophily of COVID-19 transmission between natural scenery cities suggested that people wanted to travel once the restrictions were loosened but would avoid densely populated, well-developed cities. According to transmission probability estimation, well-developed cities had a higher import risk than spread risk, while border cities had a higher spread risk. Overall, the COVID-19 transmission network did not form clusters, indicating effective management of the epidemic in China during this period. This study provides valuable insights into the epidemic transmission process and proposes adaptive strategies for combating epidemics in different types of cities.