网络和大都市地区的最佳疫苗接种策略

IF 8.8 3区 医学 Q1 Medicine Infectious Disease Modelling Pub Date : 2024-07-04 DOI:10.1016/j.idm.2024.06.007
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引用次数: 0

摘要

本研究提出了一个考虑到通勤模式的数学模型,用于在相互连接的大都市地区制定最佳疫苗接种策略。这是一个分区模型,每个城市都有一个疫苗接种率作为控制函数。通勤模式通过加权邻接矩阵和一个选择昼夜时段的参数纳入模型。优化控制问题的目的是最大限度地降低平衡住院人数和疫苗接种人数的功能成本,其中包括每周可用性上限和单位时间内疫苗接种量的限制。这项工作的主要发现是基本繁殖数量的界限,特别是在大都市地区的情况下,以及对最优控制问题的研究。理论分析和数值模拟为疾病动力学和控制措施的有效性提供了见解。正如我们在数值模拟中描述的那样,研究强调了在首都优先接种疫苗以更好地控制疾病传播的重要性。该模型可作为改善大都市地区流行病控制资源分配的工具。
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Optimal vaccination strategies on networks and in metropolitan areas

This study presents a mathematical model for optimal vaccination strategies in interconnected metropolitan areas, considering commuting patterns. It is a compartmental model with a vaccination rate for each city, acting as a control function. The commuting patterns are incorporated through a weighted adjacency matrix and a parameter that selects day and night periods. The optimal control problem is formulated to minimize a functional cost that balances the number of hospitalizations and vaccines, including restrictions of a weekly availability cap and an application capacity of vaccines per unit of time. The key findings of this work are bounds for the basic reproduction number, particularly in the case of a metropolitan area, and the study of the optimal control problem. Theoretical analysis and numerical simulations provide insights into disease dynamics and the effectiveness of control measures. The research highlights the importance of prioritizing vaccination in the capital to better control the disease spread, as we depicted in our numerical simulations. This model serves as a tool to improve resource allocation in epidemic control across metropolitan regions.

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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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