We investigate phase transitions associated with three control methods for epidemics on small world networks. Motivated by the behavior of SARS-CoV-2, we construct a theoretical SIR model of a virus that exhibits presymptomatic, asymptomatic, and symptomatic stages in two possible pathways. Using agent-based simulations on small world networks, we observe phase transitions for epidemic spread related to: 1) Global social distancing with a fixed probability of adherence. 2) Individually initiated social isolation when a threshold number of contacts are infected. 3) Viral shedding rate. The primary driver of total number of infections is the viral shedding rate, with probability of social distancing being the next critical factor. Individually initiated social isolation was effective when initiated in response to a single infected contact. For each of these control measures, the total number of infections exhibits a sharp phase transition as the strength of the measure is varied.
Digital Object Identifier (DOI)
All NetLogo code and experimental data files are available from the github repository https://github.com/braunmath/social-distance-effects-covid19.
Braun, Benjamin; Taraktaş, Başak; Beckage, Brian; and Molofsky, Jane, "Simulating Phase Transitions and Control Measures for Network Epidemics Caused by Infections with Presymptomatic, Asymptomatic, and Symptomatic Stages" (2020). Mathematics Faculty Publications. 42.