Next Article in Journal
A Comparison of the Gluco-Regulatory Responses to High-Intensity Interval Exercise and Resistance Exercise
Previous Article in Journal
Blood Pressure and Tooth Loss: A Large Cross-Sectional Study with Age Mediation Analysis
Open AccessArticle

Modeling the Dynamics of Drug Spreading in China

1
Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China
2
School of Mathematics, Taiyuan University of Technology, Taiyuan 030024, China
3
School of Public Health, Peking University, Beijing 100191, China
4
State Key Lab of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
5
Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(1), 288; https://doi.org/10.3390/ijerph18010288
Received: 3 November 2020 / Revised: 6 December 2020 / Accepted: 30 December 2020 / Published: 2 January 2021
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. View Full-Text
Keywords: drug epidemic model; basic reproduction number; stability; sensitivity; China; numerical simulation drug epidemic model; basic reproduction number; stability; sensitivity; China; numerical simulation
Show Figures

Figure 1

MDPI and ACS Style

Tang, H.; Li, M.; Yan, X.; Lu, Z.; Jia, Z. Modeling the Dynamics of Drug Spreading in China. Int. J. Environ. Res. Public Health 2021, 18, 288. https://doi.org/10.3390/ijerph18010288

AMA Style

Tang H, Li M, Yan X, Lu Z, Jia Z. Modeling the Dynamics of Drug Spreading in China. International Journal of Environmental Research and Public Health. 2021; 18(1):288. https://doi.org/10.3390/ijerph18010288

Chicago/Turabian Style

Tang, Haoxiang; Li, Mingtao; Yan, Xiangyu; Lu, Zuhong; Jia, Zhongwei. 2021. "Modeling the Dynamics of Drug Spreading in China" Int. J. Environ. Res. Public Health 18, no. 1: 288. https://doi.org/10.3390/ijerph18010288

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop