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恐惧与疾病的耦合传染动力学:数学与计算探索

Coupled contagion dynamics of fear and disease: mathematical and computational explorations.

作者信息

Epstein Joshua M, Parker Jon, Cummings Derek, Hammond Ross A

机构信息

Center on Social and Economic Dynamics, The Brookings Institution, Washington DC, United States of America.

出版信息

PLoS One. 2008;3(12):e3955. doi: 10.1371/journal.pone.0003955. Epub 2008 Dec 16.

DOI:10.1371/journal.pone.0003955
PMID:19079607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2596968/
Abstract

BACKGROUND

In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics. They do not endogenously engage, for example, in social distancing based on fear. Yet, adaptive behavior is well-documented in true epidemics. We explore the effect of including such behavior in models of epidemic dynamics.

METHODOLOGY/PRINCIPAL FINDINGS: Using both nonlinear dynamical systems and agent-based computation, we model two interacting contagion processes: one of disease and one of fear of the disease. Individuals can "contract" fear through contact with individuals who are infected with the disease (the sick), infected with fear only (the scared), and infected with both fear and disease (the sick and scared). Scared individuals--whether sick or not--may remove themselves from circulation with some probability, which affects the contact dynamic, and thus the disease epidemic proper. If we allow individuals to recover from fear and return to circulation, the coupled dynamics become quite rich, and can include multiple waves of infection. We also study flight as a behavioral response.

CONCLUSIONS/SIGNIFICANCE: In a spatially extended setting, even relatively small levels of fear-inspired flight can have a dramatic impact on spatio-temporal epidemic dynamics. Self-isolation and spatial flight are only two of many possible actions that fear-infected individuals may take. Our main point is that behavioral adaptation of some sort must be considered.

摘要

背景

在经典的数理流行病学中,个体在疫情期间不会调整其接触行为。例如,他们不会基于恐惧而自发地采取社交 distancing 措施。然而,在实际疫情中,适应性行为有充分的记录。我们探讨了在疫情动态模型中纳入此类行为的影响。

方法/主要发现:我们使用非线性动力系统和基于主体的计算方法,对两个相互作用的传染过程进行建模:一个是疾病传染过程,另一个是对疾病的恐惧传染过程。个体可以通过与感染疾病的个体(患病者)、仅感染恐惧的个体(恐惧者)以及同时感染恐惧和疾病的个体(患病且恐惧者)接触而“感染”恐惧。恐惧的个体——无论是否患病——可能会以一定概率退出社交活动,这会影响接触动态,进而影响疾病的实际传播。如果我们允许个体从恐惧中恢复并重新参与社交活动,耦合动态会变得相当丰富,并且可能包括多波感染。我们还研究了作为行为反应的逃离行为。

结论/意义:在空间扩展的环境中,即使是相对较小程度的因恐惧引发的逃离行为也可能对时空疫情动态产生巨大影响。自我隔离和空间逃离只是受恐惧感染的个体可能采取的众多可能行动中的两种。我们的主要观点是,必须考虑某种形式的行为适应。

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