A Multilayer Epidemiological Model Integrating Daily Commuting Network

Abstract

To assess the impacts of various interventions on epidemic dynamics, the authors propose an integrated epidemiological simulation framework called Multilayer Epidemic Dynamics Simulator (MEDSim), which combines four contact structures: within age group, between age groups, daily commute, and nationwide interaction. We use the daily commuting network to simulate outbreak locations and intervention scenarios for the 2009 A/H1N1 influenza epidemic in Taiwan. Our three main findings are: (a) lower transmission rates and earlier intervention activation times did not reduce total numbers of infected cases, but did delay peak times; (b) when transmission rate was decreased by a minimum of 70%, significant slowing-down effects were observed when interventions were activated before the 50th new case (c) peaks times were achieved more quickly when initial outbreaks occurred in urban rather than rural areas. The innovative simulation framework reflects the dynamic processes of epidemics under different intervention scenarios, thus clarifying the effects of complex contact structures on disease transmission dynamics.