Mixing in age-structured population models of infectious diseases
Mixing in age-structured population models of infectious diseases
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DOI：
10.1016/j.mbs.2011.10.001
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发表时间：
2012-01-01
影响因子：
4.3
通讯作者：
Castillo-Chavez, Carlos
中科院分区：
文献类型：
--
作者：
Glasser, John;Feng, Zhilan;Castillo-Chavez, Carlos
通过减少病原体在宿主内的复制或宿主之间的传播来控制传染病。模型可以可靠地评估减少传播的替代策略，但前提是人际混合是现实的。房室建模者通常使用类似年龄个体的组内和组间的接触的凸组合，分别称为优先混合和比例混合。最近发表的面对面交谈和时间使用研究表明，父母和孩子和同事也优先混合。由于混合矩阵的非对角元素会产生间接效应，因此这些观测结果非常重要。因此，我们改进了Jacquez等人发表的公式。[19]以解释这些新观察到的模式，并估计与每个首选群体接触的年龄特异性分数。由于同时代人的年龄不需要完全相同，父母和孩子的年龄也不需要完全不同的世代时间，我们还估计了高斯分布的方差，我们用它取代了理论研究中常用的克罗内克δ。我们的公式重现观察到的模式，并可用于，给定的接触，接触，以估计感染的概率，感染率和繁殖数量。作为例子，我们说明了这些计算流感的基础上的“攻击率”从一个前瞻性的家庭研究在1957年大流行和水痘的基础上累积发病率估计从1988年至1994年进行的横断面血清学调查，以及接触率从几个面对面的交谈和时间使用的研究。接触感染的易感性一般随年龄增长而下降，但在青少年和有幼儿的成年人中可能会升高。爱思唯尔公司出版
Infectious diseases are controlled by reducing pathogen replication within or transmission between hosts. Models can reliably evaluate alternative strategies for curtailing transmission, but only if interpersonal mixing is represented realistically. Compartmental modelers commonly use convex combinations of contacts within and among groups of similarly aged individuals, respectively termed preferential and proportionate mixing. Recently published face-to-face conversation and time-use studies suggest that parents and children and co-workers also mix preferentially. As indirect effects arise from the off-diagonal elements of mixing matrices, these observations are exceedingly important. Accordingly, we refined the formula published by Jacquez et al. [19] to account for these newly-observed patterns and estimated age-specific fractions of contacts with each preferred group. As the ages of contemporaries need not be identical nor those of parents and children to differ by exactly the generation time, we also estimated the variances of the Gaussian distributions with which we replaced the Kronecker delta commonly used in theoretical studies. Our formulae reproduce observed patterns and can be used, given contacts, to estimate probabilities of infection on contact, infection rates, and reproduction numbers. As examples, we illustrate these calculations for influenza based on "attack rates" from a prospective household study during the 1957 pandemic and for varicella based on cumulative incidence estimated from a cross-sectional serological survey conducted from 1988-94, together with contact rates from the several face-to-face conversation and time-use studies. Susceptibility to infection on contact generally declines with age, but may be elevated among adolescents and adults with young children. Published by Elsevier Inc.