In this study, we proposed two, symptom-dependent, HIV/AIDS models to investigate the dynamical properties of HIV/AIDS in the Fujian Province. The basic reproduction number was obtained, and the local and global stabilities of the disease-free and endemic equilibrium points were verified to the deterministic HIV/AIDS model. Moreover, the indicators $ R_0^s $ and $ R_0^e $ were derived for the stochastic HIV/AIDS model, and the conditions for stationary distribution and stochastic extinction were investigated. By using the surveillance data from the Fujian Provincial Center for Disease Control and Prevention, some numerical simulations and future predictions on the scale of HIV/AIDS infections in the Fujian Province were conducted.
Citation: Wenshuang Li, Shaojian Cai, Xuanpei Zhai, Jianming Ou, Kuicheng Zheng, Fengying Wei, Xuerong Mao. Transmission dynamics of symptom-dependent HIV/AIDS models[J]. Mathematical Biosciences and Engineering, 2024, 21(2): 1819-1843. doi: 10.3934/mbe.2024079
In this study, we proposed two, symptom-dependent, HIV/AIDS models to investigate the dynamical properties of HIV/AIDS in the Fujian Province. The basic reproduction number was obtained, and the local and global stabilities of the disease-free and endemic equilibrium points were verified to the deterministic HIV/AIDS model. Moreover, the indicators $ R_0^s $ and $ R_0^e $ were derived for the stochastic HIV/AIDS model, and the conditions for stationary distribution and stochastic extinction were investigated. By using the surveillance data from the Fujian Provincial Center for Disease Control and Prevention, some numerical simulations and future predictions on the scale of HIV/AIDS infections in the Fujian Province were conducted.
[1] | World Health Organization, 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/hiv-aids. |
[2] | Chinese Center for Disease Control and Prevention, 2023. Available from: https://www.chinacdc.cn/index.html. |
[3] | S. Tang, Y. Xiao, Y. Wang, H. Wu, Piecewise HIV virus dynamic model with CD4$^+$ T cell count-guided therapy: Ⅰ, J. Theor. Biol., 308 (2012), 123–134. http://doi.org/10.1016/j.jtbi.2012.05.022 doi: 10.1016/j.jtbi.2012.05.022 |
[4] | X. Wang, S. Liu, X. Song, A within-host virus model with multiple infected stages under time-varying environments, Appl. Math. Comput., 266 (2015), 119–134. http://doi.org/10.1016/j.amc.2015.05.033 doi: 10.1016/j.amc.2015.05.033 |
[5] | P. Naik, K. Owolabi, M. Yavuz, J. Zu, Chaotic dynamics of a fractional order HIV-1 model involving AIDS-related cancer cells, Chaos Solitons Fractals, 140 (2020), 110272. https://doi.org/10.1016/j.chaos.2020.110272 doi: 10.1016/j.chaos.2020.110272 |
[6] | B. Hirschel, T. Flanigan, Is it smart to continue to study treatment interruptions?, AIDS, 23 (2009), 757–759. |
[7] | M. Martcheva, Introduction to Mathematical Epidemiology, Springer Science and Business Media, New York, 2015. |
[8] | J. Ren, Q. Zhang, M. Li, F. Cao, M. Ye, A stochastic age-structured HIV/AIDS model based on parameters estimation and its numerical calculation, Math. Comput. Simul., 190 (2021), 159–180. https://doi.org/10.1016/j.matcom.2021.04.024 doi: 10.1016/j.matcom.2021.04.024 |
[9] | H. Song, S. Liu, W. Jiang, J. Wang, Global stability and periodic oscillations for an SIV infection model with immune response and intracellular delays, Appl. Math. Model., 38 (2014), 6108–6121. http://doi.org/10.1016/j.apm.2014.05.017 doi: 10.1016/j.apm.2014.05.017 |
[10] | L. Cai, S. Guo, S. Wang, Analysis of an extended HIV/AIDS epidemic model with treatment, Appl. Math. Comput., 236 (2014), 621–627. http://doi.org/10.1016/j.amc.2014.02.078 doi: 10.1016/j.amc.2014.02.078 |
[11] | L. Cai, B. Fang, X. Li, A note of a staged progression HIV model with imperfect vaccine, Appl. Math. Comput., 234 (2014), 412–416. http://doi.org/10.1016/j.amc.2014.01.179 doi: 10.1016/j.amc.2014.01.179 |
[12] | L. Zou, S. Ruan, W. Zhang, On the sexual transmission dynamics of hepatitis B virus in China, J. Theor. Biol., 369 (2015), 1–12. http://doi.org/10.1016/j.jtbi.2015.01.005 doi: 10.1016/j.jtbi.2015.01.005 |
[13] | Y. Xiao, S. Tang, Y. Zhou, R. Smith, J. Wu, N. Wang, Predicting the HIV/AIDS epidemic and measuring the effect of mobility in mainland China, J. Theor. Biol., 317 (2013), 271–285. http://doi.org/10.1016/j.jtbi.2012.09.037 doi: 10.1016/j.jtbi.2012.09.037 |
[14] | P. Wu, X. Wang, H. Wang, Threshold dynamics of a nonlocal dispersal HIV/AIDS epidemic model with spatial heterogeneity and antiretroviral therapy, Commun. Nonlinear Sci. Numer. Simul., 115 (2022), 106728. https://doi.org/10.1016/j.cnsns.2022.106728 doi: 10.1016/j.cnsns.2022.106728 |
[15] | X. Wang, G. Mink, D. Lin, X. Song, L. Rong, Influence of raltegravir intensification on viral load and 2-LTR dynamics in HIV patients on suppressive antiretroviral therapy, J. Theor. Biol., 416 (2017), 16–27. http://doi.org/10.1016/j.jtbi.2016.12.015 doi: 10.1016/j.jtbi.2016.12.015 |
[16] | D. Yan, B. Tang, Z. Peng, L. Rong, S. Tang, Stochastic HIV model coupled with pharmacokinetics and drug adherence may explain intermittent viral blips, Appl. Math. Lett., 133 (2022), 108242. https://doi.org/10.1016/j.aml.2022.108242 doi: 10.1016/j.aml.2022.108242 |
[17] | P. Naik, J. Zu, K. Owolabi, Modeling the mechanics of viral kinetics under immune control during primary infection of HIV-1 with treatment in fractional order, Physica A, 545 (2020), 123816. https://doi.org/10.1016/j.physa.2019.123816 doi: 10.1016/j.physa.2019.123816 |
[18] | M. Gao, D. Jiang, T. Hayat, Qualitative analysis of an HIV/AIDS model with treatment and nonlinear perturbation, Qual. Theor. Dyn. Syst., 21 (2022). https://doi.org/10.1007/s12346-022-00615-9 doi: 10.1007/s12346-022-00615-9 |
[19] | C. Silva, D. Torres, A TB-HIV/AIDS coinfection model and optimal control treatment, Discrete Contin. Dyn. Syst., 35 (2015), 4639–4663. |
[20] | C. Silva, D. Torres, A SICA compartmental model in epidemiology with application to HIV/AIDS in cape verde, Ecol. Complex, 30 (2017), 70–75. http://doi.org/10.1016/j.ecocom.2016.12.001 doi: 10.1016/j.ecocom.2016.12.001 |
[21] | D. Jasmina, C. Silva, D. Torres, A stochastic SICA epidemic model for HIV transmission, Appl. Math. Lett., 84 (2018), 168–175. https://doi.org/10.1016/j.aml.2018.05.005 doi: 10.1016/j.aml.2018.05.005 |
[22] | Y. Tan, Y. Cai, X. Sun, K. Wang, R. Yao, W. Wang, Z. Peng, A stochastic SICA model for HIV/AIDS transmission, Chaos Solitons Fractals, 165 (2022), 112768. https://doi.org/10.1016/j.chaos.2022.112768 doi: 10.1016/j.chaos.2022.112768 |
[23] | C. Silva, D. Torres, Stability of a fractional HIV/AIDS model, Math. Comput. Simul., 164 (2019), 180–190. https://doi.org/10.1016/j.matcom.2019.03.016 doi: 10.1016/j.matcom.2019.03.016 |
[24] | K. Fatmawati, H. Odinsyah, Fractional model of HIV transmission with awareness effect, Chaos Solitons Fractals, 138 (2020), 109967. https://doi.org/10.1016/j.chaos.2020.109967 doi: 10.1016/j.chaos.2020.109967 |
[25] | X. Zhai, W. Li, F. Wei, X. Mao, Dynamics of an HIV/AIDS transmission model with protection awareness and fluctuations, Chaos Solitons Fractals, 169 (2023), 113224. https://doi.org/10.1016/j.chaos.2023.113224 doi: 10.1016/j.chaos.2023.113224 |
[26] | Q. Liu, D. Jiang, Dynamical behavior of a higher order stochastically perturbed HIV/AIDS model with differential infectivity and amelioration, Chaos Solitons Fractals, 141 (2020), 110333. https://doi.org/10.1016/j.chaos.2020.110333 doi: 10.1016/j.chaos.2020.110333 |
[27] | A. Elaiw, N. Almuallem, Global properties of delayed-HIV dynamics models with differential drug efficacy in cocirculating target cells, Appl. Math. Comput., 265 (2015), 1067–1089. http://dx.doi.org/10.1016/j.amc.2015.06.011 doi: 10.1016/j.amc.2015.06.011 |
[28] | B. Han, D. Jiang, T. Hayat, A. Alsaedi, B. Ahmad, Stationary distribution and extinction of a stochastic staged progression AIDS model with staged treatment and second-order perturbation, Chaos Solitons Fractals, 140 (2020), 110238. https://doi.org/10.1016/j.chaos.2020.110238 doi: 10.1016/j.chaos.2020.110238 |
[29] | K. Qi, D. Jiang, The impact of virus carrier screening and actively seeking treatment on dynamical behavior of a stochastic HIV/AIDS infection model, Appl. Math. Model., 85 (2020), 378–404. https://doi.org/10.1016/j.apm.2020.03.027 doi: 10.1016/j.apm.2020.03.027 |
[30] | P. Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29–48. |
[31] | Y. Zhao, D. Jiang, The threshold of a stochastic SIRS epidemic model with saturated incidence, Appl. Math. Lett., 34 (2014), 90–93. http://dx.doi.org/10.1016/j.aml.2013.11.002 doi: 10.1016/j.aml.2013.11.002 |
[32] | D. Li, F. Wei, X. Mao, Stationary distribution and density function of a stochastic SVIR epidemic model, J. Franklin Inst., 359 (2022), 9422–9449. https://doi.org/10.1016/j.jfranklin.2022.09.026 doi: 10.1016/j.jfranklin.2022.09.026 |
[33] | F. Liu, F. Wei, An epidemic model with Beddington-DeAngelis functional response and environmental fluctuations, Physica A, 597 (2022), 127321. https://doi.org/10.1016/j.physa.2022.127321 doi: 10.1016/j.physa.2022.127321 |
[34] | X. Wu, F. Wei, Single-species population models with stage structure and partial tolerance in polluted environments, Math. Biosci. Eng., 19 (2022), 9590–9611. http://dx.doi.org/10.3934/mbe.2022446 doi: 10.3934/mbe.2022446 |
[35] | X. Mao, Stochastic differential equations and applications, Elsevier, Amsterdam, 2015. |
[36] | J. Zhang, F. Wei, Effects of media coverage and temporary immunity to a stochastic SEIR epidemic model, Ann. Appl. Math., 36 (2020), 442–458. |
[37] | F. Wei, R.Xue, Stability and extinction of SEIR epidemic models with generalized nonlinear incidence, Math. Comput. Simul., 170 (2020), 1–15. https://doi.org/10.1016/j.matcom.2018.09.029 doi: 10.1016/j.matcom.2018.09.029 |
[38] | X. Mao, G. Marion, E. Renshaw, Environmental Brownian noise suppresses explosions in population dynamics, Stoch. Process. Their Appl., 97 (2002), 95–110. |
[39] | Y. Zhao, D. Jiang, The threshold of a stochastic SIS epidemic model with vaccination, Appl. Math. Comput., 243 (2014), 718–27. http://dx.doi.org/10.1016/j.amc.2014.05.124 doi: 10.1016/j.amc.2014.05.124 |
[40] | Fujian Statistical Yearbook, 2022. Available from: https://tjj.fujian.gov.cn/tongjinianjian/dz2022/index.htm. |
[41] | S. Huang, A new SEIR epidemic model with applications to the theory of eradication and control of diseases, and to the calculation of R0, Math. Biosci., 215 (2008), 84–104. |
[42] | The State Council of the People's Republic of China. Available from: http://english.www.gov.cn/. |
[43] | S. Mangal, O. Misra, J. Dhar, Fractional-order deterministic epidemic model for the spread and control of HIV/AIDS with special reference to Mexico and India. Math, Comput. Simul., 210 (2023), 82–102. https://doi.org/10.1016/j.matcom.2023.03.008 doi: 10.1016/j.matcom.2023.03.008 |
[44] | X. Mao, F. Wei, T. Wiriyakraikul Positivity preserving truncated Euler-Maruyama Method for stochastic Lotka-Volterra competition model, J. Comput. Appl. Math., 394 (2021), 113566. https://doi.org/10.1016/j.cam.2021.113566 doi: 10.1016/j.cam.2021.113566 |
[45] | Y. Cai, X. Mao, F. Wei, An advanced numerical scheme for multi-dimensional stochastic Kolmogorov equations with superlinear coefficients, J. Comput. Appl. Math., 437 (2024), 115472. https://doi.org/10.1016/j.cam.2023.115472 doi: 10.1016/j.cam.2023.115472 |
[46] | D. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev., 43 (2001), 525–546. https://doi.org/10.1137/S0036144500378302 doi: 10.1137/S0036144500378302 |
[47] | G. Assembly, Resolution Adopted By the General Assembly, New York, 2016. |
[48] | Y. Gao, T. Yuan, Y. Zhan, H. Qian, Y. Sun, W. Zheng, et al, Association between medical male circumcision and HIV risk compensation among heterosexual men: a systematic review and meta-analysis, Lancet Glob Health, 9 (2021), e932–e941. https://doi.org/10.1016/S2214-109X(21)00102-9 doi: 10.1016/S2214-109X(21)00102-9 |