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Title: Understanding the coevolution of mask wearing and epidemics: A network perspective
Nonpharmaceutical interventions (NPIs) such as mask wearing can be effective in mitigating the spread of infectious diseases. Therefore, understanding the behavioral dynamics of NPIs is critical for characterizing the dynamics of disease spread. Nevertheless, standard infection models tend to focus only on disease states, overlooking the dynamics of “beneficial contagions,” e.g., compliance with NPIs. In this work, we investigate the concurrent spread of disease and mask-wearing behavior over multiplex networks. Our proposed framework captures both the competing and complementary relationships between the dueling contagion processes. Further, the model accounts for various behavioral mechanisms that influence mask wearing, such as peer pressure and fear of infection. Our results reveal that under the coupled disease–behavior dynamics, the attack rate of a disease—as a function of transition probability—exhibits a critical transition. Specifically, as the transmission probability exceeds a critical threshold, the attack rate decreases abruptly due to sustained mask-wearing responses. We empirically explore the causes of the critical transition and demonstrate the robustness of the observed phenomena. Our results highlight that without proper enforcement of NPIs, reductions in the disease transmission probability via other interventions may not be sufficient to reduce the final epidemic size.  more » « less
Award ID(s):
1633028 1916805 1918656 2028004 2027541 2041952 2142997
NSF-PAR ID:
10403912
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Proceedings of the National Academy of Sciences
Volume:
119
Issue:
26
ISSN:
0027-8424
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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