现在我知道我的Alpha, Beta, gamma:流行病计划中的变体

Michael Dubé, S. Houghten
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引用次数: 3

摘要

个人联系网络用于表示群体中个体之间存在的社会联系。生成代表网络中存在的实际感染媒介的准确网络,对于模拟受网络结构显著影响的流行病轨迹和结果非常有用。采用一种进化算法对这些网络进行进化,以适应两种适应度度量:流行病持续时间和流行病在群体中的传播。每次感染都有很小的可能性产生新的变种。被一种变体感染后,对未来的变体具有部分免疫力。这使我们能够评估每个变体的影响,与其他工作相比,这是一个重要的创新。每种变异被允许改变的数量对流行病的传播有重大影响。就流行持续时间而言,新变异的概率是流行持续时间增加的主要原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Now I Know My Alpha, Beta, Gammas: Variants in an Epidemic Scheme
Personal contact networks are used to represent the social connections that exist between individuals within a population. Producing accurate networks that represent the actual vectors of infection that exist within a network can be useful for modelling epidemic trajectory and outcomes, which is significantly impacted by a network's structure. An evolutionary algorithm is used to evolve these networks subject to two fitness measures: epidemic duration and epidemic spread through a population. With each infection there is a small probability of a new variant being generated. Being infected with one variant provides partial immunity to future variants. This allows us to evaluate the impact of each variant, a significant innovation in comparison to other work. The amount by which each variant was allowed to change had a significant impact upon epidemic spread. For epidemic duration, the probability of new variants was the primary cause of increased epidemic duration.
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