Measures of concurrency in networks and the spread of infectious disease
Measures of concurrency in networks and the spread of infectious disease
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DOI：
10.1016/0025-5564(95)00093-3
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发表时间：
1996-04-15
影响因子：
4.3
通讯作者：
Morris, M
中科院分区：
文献类型：
--
作者：
Kretzschmar, M;Morris, M
研究了并行伙伴关系对流行病传播的影响。从个体层面的并发定义开始，作者定义了在总体层面上量化并发的方法。介绍了一种基于图论考虑的并发性指标，并论证了并发性指标与接触图度分布的关系。然后研究了一种传染病在动态伙伴网络中的传播。该模型基于成对形成和分离的随机过程以及易感和受感染个体之间的伙伴关系中的疾病传播过程。利用蒙特卡罗模拟，比较了从连续一夫一妻制到个人可以同时拥有许多伴侣的接触模式的流行病传播情况。研究发现，在每个人的平均伴侣数量固定的情况下，这些伴侣在人口中的分布对流行病初期的传播速度产生重大影响，从而对一段时间后受感染的人数产生重大影响。
An investigation is made into the impact of concurrent partnerships on epidemic spread. Starting from a definition of concurrency on the level of individuals, the authors define ways to quantify concurrency on the population level. An index of concurrency based on graph theoretical considerations is introduced, and the way in which it is related to the degree distribution of the contact graph is demonstrated. Then the spread of an infectious disease on a dynamic partnership network is investigated. The model is based on a stochastic process of pair formation and separation and a process of disease transmission within partnerships of susceptible and infected individuals. Using Monte Carlo simulation, the spread of the epidemic is compared for contact patterns ranging from serial monogamy to situations where individuals can have many partners simultaneously. It is found that for a fixed mean number of partners per individual the distribution of these partnerships over the population has a major influence on the speed of the epidemic in its initial phase and consequently in the number of individuals who are infected after a certain time period.