Optimal control of an influenza model with mixed cross-infection by age group

被引:9
作者
Chen, Ya
Zhang, Juping [1 ,2 ]
Jin, Zhen [1 ,2 ]
机构
[1] Shanxi Univ, Complex Syst Res Ctr, Taiyuan 030006, Shanxi, Peoples R China
[2] Shanxi Key Lab Math Tech & Big Data Anal Dis Contr, Taiyuan 030006, Shanxi, Peoples R China
关键词
Influenza model; Epidemic threshold; Parameter estimation; Optimal control; Gradient descent method; EPIDEMIC MODEL; VACCINATION; TRANSMISSION; DISEASE; INTERVENTION; SENSITIVITY; UNCERTAINTY; STRATEGIES; STABILITY; DYNAMICS;
D O I
10.1016/j.matcom.2022.11.019
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Influenza is one of the major public health problems, and contact between all age groups and the emergence of influenza vaccines have played a vital role in the spread of influenza. In this paper, a mixed cross-infection influenza model by age group is established to study the effects of the number of contacts, vaccination rates, and protection rates among different age groups on the control of influenza transmission. The optimal control theory is applied to the model, the existence of the optimal control is proved, and the optimal path is obtained by using the Pontryagin's maximum principle, by looking for the optimal control strategy to minimize the disease burden and intervention cost caused by influenza. Parameter estimation and numerical simulation are carried out using actual data, and the sensitivity analysis of the threshold R-0 is carried out. The results show that compared with controlling the number of contacts between different age groups, increasing the vaccination rate and protection rate can reduce the number of infections to a greater extent. Finally, the gradient descent method is applied to numerical simulation of the optimal control strategy of the influenza model, and compared various control measures. We observe that considering the vaccination rate and protection rate is the best control strategy. (c) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:410 / 436
页数:27
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