A novel approach to model the role of mobility suppression and vaccinations in containing epidemics in a network of cities

IF 8.8 3区 医学 Q1 Medicine
Leen Alrawas , Abdessamad Tridane , Ghassane Benrhmach
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引用次数: 0

Abstract

This paper presents a comprehensive agent-based model for the spread of an infection in a network of cities. Directional mobility is defined between each two cities and can take different values. The work examines the role that such mobility levels play in containing the infection with various vaccination coverage and age distributions. The results indicate that mobility reduction is sufficient to control the disease under all circumstances and full lockdowns are not a necessity. It has to be reduced to different ratios depending on the vaccination level and age distribution. A key finding is that increasing vaccination coverage above a certain level does not affect the mobility suppression level required to control the infection anymore for the cases of young population and heterogeneous age distributions. By investigating several migration and commuting patterns, it is found that shutting mobility in a few local places is favored against reducing mobility over the entire country network. In addition, commuting -and not migration-influences the spread level of the infection. The work offers an exclusive combined network-based and agent-based model that makes use of randomly generated mobility matrices.

在城市网络中模拟流动性抑制和疫苗接种对遏制流行病的作用的新方法
本文提出了一个基于代理的综合模型,用于分析感染在城市网络中的传播情况。每两个城市之间的定向流动性是确定的,可以取不同的值。本文研究了在不同疫苗接种率和年龄分布的情况下,这种流动性水平在控制感染方面所起的作用。结果表明,在任何情况下,减少流动性都足以控制疾病,完全封锁并非必要。根据疫苗接种水平和年龄分布,流动性必须降低到不同的比例。一个重要发现是,在年轻人口和年龄分布不均的情况下,将疫苗接种率提高到一定水平以上并不会影响控制感染所需的流动性抑制水平。通过对几种迁徙和通勤模式的调查,我们发现,在少数几个地方关闭流动性比减少整个国家网络的流动性更有利。此外,通勤(而非移民)也会影响感染的传播水平。这项研究提供了一个基于网络和基于代理的独特组合模型,利用随机生成的流动矩阵。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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