New paper out on computational modelling of social and disease epidemics

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.

multilayer network — A pictorial example of the proposed dueling contagion frameworkwhere the social contagion—mask wearing—spreads on the top layer, andthe disease spreads on the bottom layer. The two layers share the samepopulation. Fig.1 from Qiu, Z., Espinoza, B., **Vasconcelos, V. V.**, Chen, C., Constantino, S. M., Crabtree, S. A., … & Marathe, M. V. (2022). Understanding the coevolution of mask wearing and epidemics: A network perspective. *Proceedings of the National Academy of Sciences*, *119*(26), e2123355119.

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

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