Berry Tyrus, Ferrari Matthew, Sauer Timothy, Greybush Steven J, Ebeigbe Donald, Whalen Andrew J, Schiff Steven J
Department of Mathematical Sciences, George Mason University, Fairfax, VA, USA.
Department of Biology, Center for Infectious Disease Dynamics, Penn State University, University Park, PA USA.
medRxiv. 2023 Oct 23:2023.03.13.23287222. doi: 10.1101/2023.03.13.23287222.
Predicting the interplay between infectious disease and behavior has been an intractable problem because behavioral response is so varied. We introduce a general framework for feedback between incidence and behavior for an infectious disease. By identifying stable equilibria, we provide policy end-states that are self-managing and self-maintaining. We prove mathematically the existence of two new endemic equilibria depending on the vaccination rate: one in the presence of low vaccination but with reduced societal activity (the "new normal"), and one with return to normal activity but with vaccination rate below that required for disease elimination. This framework allows us to anticipate the long-term consequence of an emerging disease and design a vaccination response that optimizes public health and limits societal consequences.
预测传染病与行为之间的相互作用一直是一个棘手的问题，因为行为反应千差万别。我们引入了一个关于传染病发病率与行为之间反馈的通用框架。通过确定稳定均衡，我们提供了自我管理和自我维持的政策终态。我们通过数学证明了取决于疫苗接种率的两种新的地方病均衡的存在：一种是疫苗接种率低但社会活动减少（“新常态”）的情况，另一种是社会活动恢复正常但疫苗接种率低于疾病消除所需水平的情况。这个框架使我们能够预测新出现疾病的长期后果，并设计出一种疫苗接种应对措施，以优化公共卫生并限制社会影响。
