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Modeling the Dynamics of Drug Spreading in China

Author

Listed:
  • Haoxiang Tang

    (Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China)

  • Mingtao Li

    (School of Mathematics, Taiyuan University of Technology, Taiyuan 030024, China)

  • Xiangyu Yan

    (School of Public Health, Peking University, Beijing 100191, China)

  • Zuhong Lu

    (State Key Lab of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China)

  • Zhongwei Jia

    (School of Public Health, Peking University, Beijing 100191, China
    Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100191, China)

Abstract

Drug abuse remains one of the major public health issues at the global level. In this article, we propose a drug epidemic model with a complete addiction–rehabilitation–recovery process, which allows the initiation of new users under the influence of drug addicts undergoing treatment and hidden drug addicts. We first conduct qualitative analyses of the dynamical behaviors of the model, including the existence and positivity of the solutions, the basic reproduction number, global asymptotic stabilities of both the drug-free and the drug-persistent equilibria, as well as sensitivity analysis. Then we use the model to predict the drug epidemic in China during 2020–2030. Finally, we numerically simulate the potential impact of intervention strategies on different drug users. The results show that the drug epidemic will decrease significantly during 2020−2030, and the most effective intervention strategy to eliminate drug epidemics is to strengthen the investigation and rehabilitation admission of hidden drug users.

Suggested Citation

  • Haoxiang Tang & Mingtao Li & Xiangyu Yan & Zuhong Lu & Zhongwei Jia, 2021. "Modeling the Dynamics of Drug Spreading in China," IJERPH, MDPI, vol. 18(1), pages 1-25, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:1:p:288-:d:473834
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    References listed on IDEAS

    as
    1. Wang, Jinliang & Wang, Jing & Kuniya, Toshikazu, 2019. "Analysis of an age-structured multi-group heroin epidemic model," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 78-100.
    2. Wei, Yongchang & Yang, Qigui & Li, Guangjie, 2019. "Dynamics of the stochastically perturbed Heroin epidemic model under non-degenerate noises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
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    5. Fang, Bin & Li, Xue-Zhi & Martcheva, Maia & Cai, Li-Ming, 2015. "Global asymptotic properties of a heroin epidemic model with treat-age," Applied Mathematics and Computation, Elsevier, vol. 263(C), pages 315-331.
    6. Lihong Wang & Fanghong Zhang & Cuncheng Jin, 2017. "Analysis of an Eco-Epidemiological Model with Disease in the Prey and Predator," International Journal of Mathematical Research, Conscientia Beam, vol. 6(1), pages 22-28.
    7. repec:pkp:ijomre:2017:p:22-28 is not listed on IDEAS
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    1. Savadkoohi, Marjan & Macarulla, Marcel & Casals, Miquel, 2023. "Facilitating the implementation of neural network-based predictive control to optimize building heating operation," Energy, Elsevier, vol. 263(PB).

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