Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China.
School of Mathematics, Taiyuan University of Technology, Taiyuan 030024, China.
Int J Environ Res Public Health. 2021 Jan 2;18(1):288. doi: 10.3390/ijerph18010288.
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.
药物滥用仍然是全球主要的公共卫生问题之一。在本文中,我们提出了一个具有完整成瘾-康复-恢复过程的药物流行模型,该模型允许在接受治疗的吸毒者和隐藏的吸毒者的影响下启动新的使用者。我们首先对模型的动态行为进行定性分析,包括解的存在性和正定性、基本再生数、无药物和药物持续平衡点的全局渐近稳定性以及敏感性分析。然后,我们使用该模型预测 2020-2030 年中国的药物流行情况。最后,我们数值模拟了不同药物使用者的干预策略的潜在影响。结果表明,2020-2030 年期间,药物流行将显著下降,消除药物流行的最有效干预策略是加强对隐藏吸毒者的调查和康复入院。