Vítor and collaborators published a multilayered network perspective on the coevolution of social behavior and disease outbreak on PNAS.
Nonpharmaceutical interventions such as mask wearing play a critical role in reducing disease prevalence. Under the dueling dynamics of mask wearing and disease, we observe a robust nonmonotonic relationship between the attack rate (i.e., the fraction of the ever-infected population) and the transmission probability of the disease. Specifically, the attack rate exhibits an abrupt reduction as the transmission probability increases to a critical threshold. Furthermore, we characterize regimes of the transmission probability where multiple waves of infection and mask adoption are expected. Our results highlight the necessity of continued public mask-wearing mandates to suppress the epidemic and effectively prevent its revival.
This project was particularly fun, being a relatively large international collaboration. We used a great dataset for the social networks Synthetic population for USA_VIRGINIA | Zenodo and I am particularly proud of the mean-field model that captures the dominant dynamic effects, while highlighting the effects of the network.Vítor V. Vasconcelos
Read more: Understanding the coevolution of mask wearing and epidemics: A network perspective