Exploring the optimal network topology for spreading dynamics

Multilayer networks with higher-order interaction reveal the impact of collective behavior on epidemic dynamics

“…In the absence of pharmaceutical interventions, situational awareness and collective adoption of protective behaviors are pivotal to combat spreadout of infectious diseases, as demonstrated by the ongoing COVID-19 pandemic and the flare-up or resurgent outbreaks around the world. The integration of awareness into mathematical models, mainly through variants of susceptible-infectious-recovered (SIR) models, has been widely investigated since the onset of COVID-19 [1] . Most of these models merely capture oversimplified behaviors (e.g., social distancing or not) and fail to capture the sophisticated mechanisms underlying behavioral responses, including the individual perception of infection risk and bounded rationality, government mandate, socioeconomic cost and fatigue on adherence to containment policies, as well as social influence [2] , [3] , [4] , [5] .…”