On the analysis of a multi-regions discrete SIR epidemic model: an optimal control approach

被引:47
作者
Zakary O. [1 ]
Rachik M. [1 ]
Elmouki I. [1 ]
机构
[1] Laboratory of Analysis, Modeling and Simulation (LAMS), Department of Mathematics and Computer Sciences, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Avenue Commandant Driss ELHARTI, Ben M’Sik, B.P. 7955, Casablanca
关键词
Discrete SIR model; Multi-points boundary value problems; Multi-regions; Optimal control;
D O I
10.1007/s40435-016-0233-2
中图分类号
学科分类号
摘要
In this paper, we devise a discrete time SIR model depicting the spread of infectious diseases in various geographical regions that are connected by any kind of anthropological movement, which suggests disease-affected people can propagate the disease from one region to another via travel. In fact, health policy-makers could manage the problem of the regional spread of an epidemic, by organizing many vaccination campaigns, or by suggesting other defensive strategies such as blocking movement of people coming from borders of regions at high-risk of infection and entering very controlled regions or with insignificant infection rate. Further, we introduce in the discrete SIR systems, two control variables which represent the effectiveness rates of vaccination and travel-blocking operation. We focus in our study to control the outbreaks of an epidemic that affects a hypothetical population belonging to a specific region. Firstly, we analyze the epidemic model when the control strategy is based on the vaccination control only, and secondly, when the travel-blocking control is added. The multi-points boundary value problems, associated to the optimal control problems studied here, are obtained based on a discrete version of Pontryagin’s maximum principle, and resolved numerically using a progressive-regressive discrete scheme that converges following an appropriate test related to the Forward-Backward Sweep Method on optimal control. © 2016, Springer-Verlag Berlin Heidelberg.
引用
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页码:917 / 930
页数:13
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