Assessing the spread risk of COVID-19 associated with multi-mode transportation networks in China

The spatial spread of COVID-19 during early 2020 in China was primarily driven by outbound travelers leaving the epicenter,Wuhan,Hubei province.Existing studies focus on the influence of aggregated out-bound population flows originating from Wuhan;however,the impacts of different modes of transportation and the network structure of transportation systems on the early spread of COVID-19 in China are not well understood.Here,we assess the roles of the road,railway,and air transportation networks in driving the spatial spread of COVID-19 in China.We find that the short-range spread within Hubei province was dominated by ground traffic,notably,the railway transportation.In contrast,long-range spread to cities in other provinces was mediated by multiple factors,including a higher risk of case importation associated with air transportation and a larger outbreak size in hub cities located at the center of transportation networks.We further show that,although the dissemination of SARS-CoV-2 across countries and continents is determined by the worldwide air transportation network,the early geographic dispersal of COVID-19 within China is better predicted by the railway traffic.Given the recent emergence of multiple more transmissible variants of SARS-CoV-2,our findings can support a better assessment of the spread risk of those variants and improve future pandemic preparedness and responses.

Heterogeneous influence of individuals’ behavior on mask efficacy in gathering environments

Wearing masks is an easy way to operate and popular measure for preventing epidemics.Although masks can slow down the spread of viruses,their efficacy in gathering environments involving heterogeneous person-to-person contacts remains unknown.Therefore,we aim to investigate the epidemic prevention effect of masks in different real-life gathering environments.This study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering environments.The transmission of COVID-19 is simulated using the Monte Carlo simulation method.The heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general society.Furthermore,the heterogeneity of gathering environments causes the epidemic prevention effect of masks to differ.Wearing masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools,high schools,and hospitals.However,the use of masks alone in primary schools and hospitals cannot control outbreaks.In high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse,masks can meet the need for prevention.Given the heterogeneity of individual behavior,if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing,the epidemic prevention effect of masks can be improved.Finally,asymptomatic infection has varying effects on the prevention effect of masks in different environments.The effect can be weakened or eliminated by increasing the usage rate of masks in high schools and workplaces.However,the effect on primary schools and hospitals cannot be weakened.This study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention.