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双斑块耐药结核病动力学模型的稳定性分析
Stability Analysis of Drug-Resistant Tuberculosis Model in a Two-Patch Environment

DOI: 10.12677/aam.2024.137335, PP. 3502-3519

Keywords: 双斑块模型,耐药结核病,李雅普诺夫函数,稳定性
Two-Patch Model
, Drug-Resistant Tuberculosis, Lyapunov Function, Stability

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Abstract:

为了研究人口迁移对耐药结核病传播造成的影响,建立了一个含有迁移的耐药结核病双斑块动力学模型。首先,利用下一代矩阵的方法得到了基本再生数;其次,证明了无病平衡点的全局渐近稳定性,并通过构造李雅普诺夫函数证明了地方病平衡点的全局渐近稳定性;最后,对模型进行了基本再生数的敏感性分析和数值模拟。模拟结果表明,迁移率和耐药性转化率的增大均会导致耐药结核病人数的增多,且迁移率相对于耐药性转化率来说对耐药结核病人数的影响更明显。因此,在合理控制迁移率的基础上降低药物敏感结核病向耐药结核病的转化率,能更有效控制结核病的传播。
A two-patch drug-resistant tuberculosis model is formulated to investigate the impact of population migration on the spread of drug-resistant tuberculosis. Firstly, by using the next generation matrix method, the basic reproduction number was obtained. Secondly, the global asymptotic stability of disease-free equilibrium point is proved, by using the theory of stability of differential equations. And the global asymptotic stability of endemic equilibrium point by constructing the Lyapunov function is proved. Finally, a sensitivity analysis of the basic reproduction number and numerical simulation of the model. The numerical simulation shows that the increase in migration rate and drug-resistance conversion rate will lead to an increase in the number of patients with resistance to resistance. The increase in migration rate and drug resistance at the same time will have a negative impact on the number of patients with drug-resistant tuberculosis. Therefore, to reduce the conversion rate of Drug-Sensitive tuberculosis to Drug-Resistant tuberculosis on the basis of reasonable control of migration, which can more effectively control the spread of tuberculosis.

References

[1]  World Health Organization (2023) Global Tuberculosis Report 2023. WHO Report 2023.
https://www.who.int/publications/i/item/9789240083851
[2]  Waaler, H., Geser, A. and Andersen, S. (1962) The Use of Mathematical Models in the Study of the Epidemiology of Tuberculosis. American Journal of Public Health and the Nations Health, 52, 1002-1013.
https://doi.org/10.2105/ajph.52.6.1002
[3]  Brogger, S. (1967) Systems Analysis in Tuberculosis Control: A Model. American Review of Respiratory Disease, 95, 419-434.
[4]  Song, B., Castillo-Chavez, C. and Aparicio, J.P. (2002) Tuberculosis Models with Fast and Slow Dynamics: The Role of Close and Casual Contacts. Mathematical Biosciences, 180, 187-205.
https://doi.org/10.1016/s0025-5564(02)00112-8
[5]  Zhang, J. and Feng, G. (2014) Global Stability for a Tuberculosis Model with Isolation and Incomplete Treatment. Computational and Applied Mathematics, 34, 1237-1249.
https://doi.org/10.1007/s40314-014-0177-0
[6]  Ullah, I., Ahmad, S. and Zahri, M. (2023) Investigation of the Effect of Awareness and Treatment on Tuberculosis Infection via a Novel Epidemic Model. Alexandria Engineering Journal, 68, 127-139.
https://doi.org/10.1016/j.aej.2022.12.061
[7]  Ronoh, M., Jaroudi, R., Fotso, P., Kamdoum, V., Matendechere, N., Wairimu, J., et al. (2016) A Mathematical Model of Tuberculosis with Drug Resistance Effects. Applied Mathematics, 7, 1303-1316.
https://doi.org/10.4236/am.2016.712115
[8]  张华龙, 祝光湖, 陈思行. 耐药肺结核的传播动力学和关键因素分析[J]. 桂林电子科技大学学报, 2018, 38(1): 75-81.
[9]  Xu, A., Wen, Z., Wang, Y. and Wang, W. (2022) Prediction of Different Interventions on the Burden of Drug-Resistant Tuberculosis in China: A Dynamic Modelling Study. Journal of Global Antimicrobial Resistance, 29, 323-330.
https://doi.org/10.1016/j.jgar.2022.03.018
[10]  Hethcote, H.W. (1976) Qualitative Analyses of Communicable Disease Models. Mathematical Biosciences, 28, 335-356.
https://doi.org/10.1016/0025-5564(76)90132-2
[11]  Wang, W. and Zhao, X. (2004) An Epidemic Model in a Patchy Environment. Mathematical Biosciences, 190, 97-112.
https://doi.org/10.1016/j.mbs.2002.11.001
[12]  Phaijoo, G.R. and Gurung, D.B. (2016) Mathematical Study of Dengue Disease Transmission in Multi-Patch Environment. Applied Mathematics, 7, 1521-1533.
https://doi.org/10.4236/am.2016.714132
[13]  Zhang, J., Cosner, C. and Zhu, H. (2018) Two-Patch Model for the Spread of West Nile Virus. Bulletin of Mathematical Biology, 80, 840-863.
https://doi.org/10.1007/s11538-018-0404-8
[14]  Meng, L. and Zhu, W. (2021) Generalized SEIR Epidemic Model for COVID-19 in a Multipatch Environment. Discrete Dynamics in Nature and Society, 2021, Article ID: 5401253.
https://doi.org/10.1155/2021/5401253
[15]  Badjo Kimba, A.W., Moustapha, D. and Saley, B. (2022) Mathematical Analysis and Simulation of an Age-Structured Model with Two-Patch and an Uncontrolled Migration: Application to Tuberculosis. European Journal of Pure and Applied Mathematics, 15, 2054-2073.
https://doi.org/10.29020/nybg.ejpam.v15i4.4556
[16]  马知恩, 周义仓, 王稳地, 靳祯. 传染病动力学的数学建模与研究[M]. 北京: 科学出版社, 2004.
[17]  Tewa, J.J., Bowong, S. and Mewoli, B. (2012) Mathematical Analysis of Two-Patch Model for the Dynamical Transmission of Tuberculosis. Applied Mathematical Modelling, 36, 2466-2485.
https://doi.org/10.1016/j.apm.2011.09.004
[18]  Yu, Y., Shi, Y. and Yao, W. (2018) Dynamic Model of Tuberculosis Considering Multi-Drug Resistance and Their Applications. Infectious Disease Modelling, 3, 362-372.
https://doi.org/10.1016/j.idm.2018.11.001
[19]  Huo, H., Chen, R. and Wang, X. (2016) Modelling and Stability of HIV/AIDS Epidemic Model with Treatment. Applied Mathematical Modelling, 40, 6550-6559.
https://doi.org/10.1016/j.apm.2016.01.054
[20]  Liu, M. and Li, Y. (2023) Dynamics Analysis of an SVEIR Epidemic Model in a Patchy Environment. Mathematical Biosciences and Engineering, 20, 16962-16977.
https://doi.org/10.3934/mbe.2023756
[21]  Salmani, M. and van den Driessche, P. (2006) A Model for Disease Transmission in a Patchy Environment. Discrete & Continuous Dynamical Systems B, 6, 185-202.
https://doi.org/10.3934/dcdsb.2006.6.185
[22]  Van den Driessche, P. and Watmough, J. (2002) Reproduction Numbers and Sub-Threshold Endemic Equilibria for Compartmental Models of Disease Transmission. Mathematical Biosciences, 180, 29-48.
https://doi.org/10.1016/s0025-5564(02)00108-6
[23]  Smith, H.L. and Waltman, P. (1995). The Theory of the Chemostat: Dynamics of Microbial Competition. Cambridge University Press.
https://doi.org/10.1017/cbo9780511530043
[24]  宁鹏静, 靳祯, 王丽萍. 一类肺结核传播模型的动力学分析[J]. 中北大学学报(自然科学版), 2023, 44(4): 340-345+351.
[25]  陈兰荪. 数学生态学模型与研究方法[M]. 北京: 科学出版社, 1988.
[26]  Chitnis, N., Hyman, J.M. and Cushing, J.M. (2008) Determining Important Parameters in the Spread of Malaria through the Sensitivity Analysis of a Mathematical Model. Bulletin of Mathematical Biology, 70, 1272-1296.
https://doi.org/10.1007/s11538-008-9299-0

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