Michalska-Smith Matthew, Enns Eva A, White Lauren A, Gilbertson Marie L J, Craft Meggan E
Department of Ecology, Evolution and behavior, University of Minnesota, Minneapolis, MN, USA.
Department of Plant Pathology, University of Minnesota, Minneapolis, MN, USA.
R Soc Open Sci. 2023 Mar 29;10(3):221122. doi: 10.1098/rsos.221122. eCollection 2023 Mar.
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.
个体之间的密切接触为包括新冠病毒在内的疾病传播提供了机会。虽然个体参与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产生了将人群中的个体相互连接起来的复杂社会接触网络。因此，虽然个体可能会根据感染威胁来决定自己的风险承受能力，但这些决定的后果很少如此局限，会传播到远远超出任何一个人的范围。我们评估不同的人群层面风险承受机制、年龄和家庭规模分布形式的人口结构以及不同互动类型对合理的人际接触网络中疫情传播的影响，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，我们发现处于隔离状态的易感个体的行为改变不足以降低这些个体的感染风险，而且人口结构可能对疫情结果产生不同且相互抵消的影响。每种互动类型的相对影响取决于接触网络构建所依据的假设，这突出了实证验证的重要性。综合来看，这些结果促进了对接触网络上疾病传播的细致理解，对公共卫生策略具有启示意义。
