标题： 接触网络中流行病模型的最优和次优疫苗接种的群体中心性 显示英文标题

标题： Group centrality in optimal and suboptimal vaccination for epidemic models in contact networks

摘要： 追求最小化需要接种疫苗的个体数量以控制疫情的策略是数学流行病学中一个已确立的研究领域。 然而，对于某些疾病，公共政策往往优先考虑接种易感个体而非疫情控制。 因此，最优接种策略可能并不总能有效支持现实世界的公共政策。 当一种新疫苗被引入且供应不足时，也会出现类似情况，因为必须确定接种的目标优先群体。 在本研究中，我们关注一种导致长期免疫力并通过异质人群传播的疾病，该人群由接触网络表示。 我们研究了四种著名的群体中心性度量，并表明GED-Walk即使在次优情况下也能可靠地估计接种特定群体的影响。 此外，我们偏离了寻找应接种个体的思路，提供了用于识别最佳接种群体的替代方法。 虽然GED-Walk在次优情况下是最有用的中心性度量，但在寻找最佳群体时，介数（一种相关但不同的中心性度量）表现突出。 这表明最优接种并非关注于切断最多的传播路径，而是中断最短路径。 显示英文摘要

摘要： The pursuit of strategies that minimize the number of individuals needing vaccination to control an outbreak is a well-established area of study in mathematical epidemiology. However, for certain diseases, public policy tends to prioritize immunizing vulnerable individuals over epidemic control. As a result, optimal vaccination strategies may not always be effective in supporting real-world public policies. A similar situation happens when a new vaccine is introduced and is in short supply, as target priority groups for vaccination have to be defined. In this work, we focus on a disease that results in long-term immunity and spreads through a heterogeneous population, represented by a contact network. We study four well-known group centrality measures and show that the GED-Walk offers a reliable means of estimating the impact of vaccinating specific groups of individuals, even in suboptimal cases. Additionally, we depart from the search for target individuals to be vaccinated and provide proxies for identifying optimal groups for vaccination. While the GED-Walk is the most useful centrality measure for suboptimal cases, the betweenness (a related, but different centrality measure) stands out when looking for optimal groups. This indicates that optimal vaccination is not concerned with breaking the largest number of transmission routes, but interrupting geodesic ones.