文献类型：期刊文献

英文题名：Hamiltonian optimal control of quarantine against epidemic spreading on complex networks

作者：Fan, Yufei[1,2];Meng, Xueyu[1,2,3];Liu, Jun[1];Ma, Jun-Chao[3,4,5];Cai, Zhiqiang[1,2];Si, Shubin[1,2]

机构：[1]Northwestern Polytech Univ, Sch Mech Engn, Dept Ind Engn, Xian 710072, Peoples R China;[2]Northwestern Polytech Univ, Key Lab Ind Engn & Intelligent Mfg, Minist Ind & Informat Technol, Xian 710072, Peoples R China;[3]Univ Fribourg, Dept Phys, CH-1700 Fribourg, Switzerland;[4]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[5]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China

年份：2025

卷号：194

外文期刊名：CHAOS SOLITONS & FRACTALS

收录：;EI(收录号：20251017983708);WOS:【SCI-EXPANDED(收录号:WOS:001440677100001)】；

基金：The authors gratefully acknowledge the financial supports for this research from the National Natural Science Foundation of China (No. 72271200) , the Distinguished Young Scholar Program of Shaanxi Province (No. 2023-JQ-JC-10) and the Science and Technology Innovation Group Program of Shaanxi Province (2024RS-CXTD-28) .

语种：英文

外文关键词：Complex networks; SIQRSV compartmental model; Epidemic control; Hamiltonian optimal control; Decision making

摘要：Effective optimization of prevention and control measures can significantly organize the spread of infectious diseases. In this paper, we construct an SIQRSV (Susceptible-Infected-Quarantined-Recovered-Susceptible- Vaccinated) compartmental model for infectious diseases on complex networks to study the infection mechanism. Specifically, we analyze the impact mechanism of infection rates, consider network heterogeneity, and examine the influence of network topology on disease spread. Using a system of differential equations, we can elucidate the disease transmission process. Furthermore, we obtain the disease-free equilibrium point of the system in its steady state. By constructing an autonomous equation, we derive the basic reproduction number of the system, and further validate it using the next-generation matrix method. Additionally, through the Jacobian matrix, we demonstrate the stability of the disease-free equilibrium points. Subsequently, based on the compartmental model, we consider the costs of treatment, control measures, and vaccination to construct a Hamiltonian system to optimize the quarantine rate. Finally, we conduct simulation experiments based on our proposed model on various networks, including BA scale-free networks and four empirical networks. The results indicate that compared to random quarantine measures, our optimized measures can effectively suppress the spread of infectious diseases, thereby providing theoretical support for policymakers in formulating control measures.