School of Medicine, Stanford University, Stanford, California, United States of America.
Department of Biology, Stanford University, Stanford, California, United States of America.
PLoS Comput Biol. 2023 Sep 5;19(9):e1011217. doi: 10.1371/journal.pcbi.1011217. eCollection 2023 Sep.
Heterogeneity in contact patterns, mortality rates, and transmissibility among and between different age classes can have significant effects on epidemic outcomes. Adaptive behavior in response to the spread of an infectious pathogen may give rise to complex epidemiological dynamics. Here we model an infectious disease in which adaptive behavior incentives, and mortality rates, can vary between two and three age classes. The model indicates that age-dependent variability in infection aversion can produce more complex epidemic dynamics at lower levels of pathogen transmissibility and that those at less risk of infection can still drive complexity in the dynamics of those at higher risk of infection. Policymakers should consider the interdependence of such heterogeneous groups when making decisions.
不同年龄组之间和内部的接触模式、死亡率和传染性的异质性会对疫情结果产生重大影响。针对传染病原体传播而做出的适应性行为可能会引发复杂的流行病学动态。在这里,我们构建了一个传染病模型,在该模型中,适应性行为激励和死亡率在两个到三个年龄组之间存在差异。该模型表明,感染厌恶的年龄依赖性变化可以在较低的病原体传播率水平下产生更复杂的疫情动态,而那些感染风险较低的人仍然可以驱动那些感染风险较高的人的疫情动态的复杂性。决策者在做出决策时应该考虑到这种异质群体的相互依存关系。