Epidemics on networks: Reducing disease transmission using health emergency declarations and peer communication

Azizi, Asma; Montalvo, Cesar; Espinoza, Baltazar; Kang, Yun; Castillo-Chavez, Carlos

In this paper, we explore the impact of various, prevalence-dependent pre-selected thresholds (decisions made by public health officials) as triggers of possibly temporarily behavioral change. The time to a triggering event is assumed to depend on the prevalence of infectione a decision taken by health authorities (declaring some level of health emergency). We carry out simulations to explore the impact of variations on triggering prevalence-driven levels on the final epidemic size of a non-fatal infection under three distinct fixed artificial social structures modeled as, Erd} os-R enyi, Small-world, and Scale-free networks.