The illusion of personal health decisions for infectious disease management: disease spread in social contact networks.
The illusion of personal health decisions for infectious disease management: disease spread in social contact networks.
复制标题
DOI：
10.1098/rsos.221122
复制
发表时间：
2023-03
影响因子：
3.5
通讯作者：
Craft, Meggan E
中科院分区：
文献类型：
--
作者：
Michalska-Smith, Matthew;Enns, Eva A;White, Lauren A;Gilbertson, Marie L J;Craft, Meggan E
人与人之间的密切接触为疾病的传播提供了机会，包括新冠肺炎。虽然个人参与了许多不同类型的互动，包括与同学、同事和家庭成员的互动，但正是所有这些互动的集合，才产生了将整个人口中的个人相互连接起来的复杂的社会联系网络。因此，虽然一个人可能会决定自己对感染威胁的风险承受能力，但这种决定的后果很少如此有限，远远超出了任何一个人的范围。我们评估了不同人口水平的风险容忍机制、年龄和家庭规模分布形式的人口结构以及不同相互作用类型对合理的人类接触网络中流行病传播的影响，以深入了解接触网络结构如何影响病原体在人群中的传播。特别是，我们发现，易受感染的人在与世隔绝的情况下行为变化不足以降低这些人的感染风险，而且人口结构可能对流行病结果产生不同的抵消影响。每种互动类型的相对影响取决于联系网络建设的假设，强调了经验验证的重要性。综上所述，这些结果促进了对通过接触网络传播疾病的细微差别的理解，并对公共卫生战略产生了影响。
Close contacts between individuals provide opportunities for the transmission of diseases, including COVID-19. While individuals take part in many different types of interactions, including those with classmates, co-workers and household members, it is the conglomeration of all of these interactions that produces the complex social contact network interconnecting individuals across the population. Thus, while an individual might decide their own risk tolerance in response to a threat of infection, the consequences of such decisions are rarely so confined, propagating far beyond any one person. We assess the effect of different population-level risk-tolerance regimes, population structure in the form of age and household-size distributions, and different interaction types on epidemic spread in plausible human contact networks to gain insight into how contact network structure affects pathogen spread through a population. In particular, we find that behavioural changes by vulnerable individuals in isolation are insufficient to reduce those individuals’ infection risk and that population structure can have varied and counteracting effects on epidemic outcomes. The relative impact of each interaction type was contingent on assumptions underlying contact network construction, stressing the importance of empirical validation. Taken together, these results promote a nuanced understanding of disease spread on contact networks, with implications for public health strategies.