×

Global stability of an infection-age structured HIV-1 model linking within-host and between-host dynamics. (English) Zbl 1371.92130

Summary: Although much evidence shows the inseparable interaction between the within-host progression of HIV-1 infection and the transmission of the disease at the population level, few models coupling the within-host and between-host dynamics have been developed. In this paper, we adopt the nested approach, viewing the transmission rate at each stage (primary, chronic, and AIDS stage) of HIV-1 infection as a saturated function of the viral load, to formulate an infection-age structured epidemic model. We explicitly link the individual and the host population scale, and derive the basic reproduction number \(R_0\) for the coupled system. To analyze the model and perform a detailed global dynamics analysis, two Lyapunov functionals are constructed to prove the global asymptotical stability of the disease-free and endemic equilibria. Theoretical results indicate that \(R_0\) provides a threshold value determining whether or not the disease dies out. Numerical simulations are presented to quantitatively investigate the influence of the within-host viral dynamics on between-host transmission dynamics. The results suggest that increasing the effectiveness of inhibitors can decrease the basic reproduction number, but can also increase the overall infected population because of a lower disease-induced mortality rate and a longer lifespan of HIV infected individuals.

MSC:

92D30 Epidemiology
34D23 Global stability of solutions to ordinary differential equations
Full Text: DOI

References:

[1] Thieme, H. R.; Castillo-Chavez, C., How may infection-age-dependent infectivity affect the dynamics of hiv/aids?, SIAM J. Appl. Math., 53, 1447 (1993) · Zbl 0811.92021
[2] McLean, A. R.; Blower, S. M., Imperfect vaccines and herd immunity to HIV, Proc. R. Soc. London, Ser. B, 253, 9 (1993)
[3] Hyman, J. M.; Li, J.; Stanley, E. A., The differential infectivity and staged progression models for the transmission of HIV, Math. Biosci., 208, 227 (1999)
[4] Gumel, A. B.; McCluskey, C. C.; van den Driessche, P., Mathematical study of a staged progression HIV model with imperfect vaccine, Bull. Math. Biol., 68, 2105 (2006) · Zbl 1296.92124
[5] Zhou, Y. C.; Shao, Y. M.; Ruan, Y. H.; Xu, J. Q.; Ma, Z.; Mei, C. L.; Wu, J. H., Modeling and prediction of HIV in china: transmission rates structured by infection ages, Math. Biosci. Eng., 5, 403 (2008) · Zbl 1158.92327
[6] Xu, X. X.; Xiao, Y. N.; Wang, N., Modeling sexual transmission of HIV/AIDS in Jiangsu province, China, Math. Methods Appl. Sci., 36, 234 (2013) · Zbl 1263.92032
[7] Xiao, Y. N.; Tang, S. Y.; Zhou, Y. C.; Robert, J. S.; Wu, J. H.; Wang, N., Predicting an HIV/AIDS epidemic and measuring the effect on it of population mobility in mainland China, J. Theor. Biol., 317, 271 (2013) · Zbl 1368.92195
[8] Perelson, A. S.; Nelson, P. W., Mathematical analysis of HIV-1 dynamics in vivo, SIAM Rev., 41, 3 (1999) · Zbl 1078.92502
[9] Rong, L. B.; Feng, Z. L.; Perelson, A. S., Mathematical analysis of age-structured HIV-1 dynamics with combination antiretroviral therapy, SIAM J. Appl. Math., 67, 731 (2007) · Zbl 1121.92043
[10] Tang, S. Y.; Xiao, Y. N.; Wang, N.; Wu, H. L., Piecewise HIV virus dynamic model with CD \(4^+\) T cell count-guided therapy: I, J. Theor. Biol., 308, 123 (2012) · Zbl 1411.92180
[11] Huang, G.; Liu, X. N.; Takeuchi, Y., Lyapunov functions and global stability for age-structured HIV infection model, SIAM J. Appl. Math., 72, 25 (2012) · Zbl 1238.92032
[12] Xiao, Y.; Miao, H.; Tang, S.; Wu, H., Modeling antiretroviral drug responses for HIV-1 infected patients using differential equation models, Adv. Drug Delivery Rev., 65, 940 (2013)
[13] Quinn, T. C.; Wawer, M. J.; Sewankambo, N., Viral load and heterosexual transmission of human immunodeficiency virus type 1. Rakai Project Study Group, N. Engl. J. Med., 342, 921 (2000)
[14] Rapatski, B. L.; Suppe, F.; Yorke, J. A., Hiv epidemics driven by late disease stage transmission, J. Acquired Immune. Defic. Syndr., 38, 241 (2005)
[15] Wawer, M. J.; Gray, R. H.; Sewankambo, N. K., Rates of HIV-1 transmission per coital act, by stage of HIV-1 infection, in Rakai, Uganda, J. Infect. Dis., 191, 1403 (2005)
[16] Fraser, C.; Hollingsworth, T. D.; Chapman, R.; de Wolf, F.; Hanage, W. P., Variation in HIV set-point viral load: epidemiological analysis and an evolutionary hypothesis, Proc. Natl. Acad. Sci. U.S.A., 104, 17441 (2007)
[17] Wilson, D. P.; Law, M. G.; Grulich, A. E.; Cooper, D. A.; Kaldor, J. M., Relation between HIV viral load and infectiousness: a model-based analysis, Lancet, 372, 314 (2008)
[18] Hollingsworth, T. D.; Anderson, R. M.; Fraser, C., HIV-1 transmission, by stage of infection, J. Infect. Dis., 198, 687 (2008)
[19] Abu-Raddad, L. J.; Barnabas, R. V.; Janes, H.; Weiss, H. A.; Kublin, J. G.; JR, I. M.L.; Wasserheit, J. N., Have the explosive HIV epidemics in sub-Saharan Africa been driven by higher community viral load?, AIDS, 27, 981 (2013)
[20] Gilchrist, M. A.; Coombs, D., Evolution of virulence: interdependence, constrains, and selection using nested models, Theor. Popul. Biol., 69, 145 (2006) · Zbl 1089.92044
[21] Coombs, D.; Gilchrist, M. A.; Ball, C. L., Evaluating the importance of within- and between-host selection pressures on the evolution of chronic pathogens, Theor. Popul. Biol., 72, 576 (2007) · Zbl 1141.92036
[22] Feng, Z. L.; Hernandez, J. V.; Santos, B. T.; Leite, M. C.A., A model for coupling within-host and between-host dynamics in an infectious disease, Nonlinear Dyn., 68, 401 (2012) · Zbl 1254.92077
[23] Gilchrist, M. A.; Sasaki, A., Modeling host-parasite coevolution: a nested approach based on mechanistic models, J. Theor. Biol., 218, 289 (2002)
[24] Sasaki, A.; Iwasa, Y., Optimal growth schedule of pathogens within a host: switching between lytic and latent cycles, Theor. Popul. Biol., 39, 201 (1991) · Zbl 0728.92024
[25] Mideo, N.; Alizon, S.; Day, T., Linking within- and between-host dynamics in the evolutionary epidemiology of infectious diseases, Trends Ecol. Evol., 23, 511 (2008)
[26] Martcheva, M.; Li, X. Z., Linking immunological and epidemiological dynamics of HIV: the case of super-infection, J. Biol. Dyn., 7, 161 (2013) · Zbl 1447.92451
[27] Numfor, E.; Bhattacharya, S.; Lenhart, S.; Martcheva, M., Optimal control of nested within-host and between-host model, Math. Modell. Nat. Phenom., 7, 32 (2014) · Zbl 1294.49013
[28] Magal, P.; McCluskey, C. C.; Webb, G. F., Lyapunov functional and global asymptotic stability for an infection-age model, Appl. Anal., 89, 1109 (2010) · Zbl 1208.34126
[29] McCluskey, C. C., Global stability for an SEI epidemiological model with continuous age-structure in the exposed and infectious classes, Math. Biosci. Eng., 9, 819 (2012) · Zbl 1259.34068
[30] Brauer, F.; Shuai, Z. S.; van den Driessche, P., Dynamics of an age-of-infection cholera model, Math. Biosci. Eng., 10, 1335 (2013) · Zbl 1273.92050
[31] De Leenheer, P.; Smith, H. L., Virus dynamics: a global analysis, SIAM J. Appl. Math., 63, 1313 (2003) · Zbl 1035.34045
[32] Gurtin, M. E.; MacCamy, R. C., Nonlinear age-dependent population dynamics, Arch. Ration. Mech. Anal., 54, 281 (1974) · Zbl 0286.92005
[33] Webb, G. F., Theory of Nonlinear Age-Dependent Population Dynamics (1985), Marcel Dekker: Marcel Dekker New York · Zbl 0555.92014
[34] Hale, J. K.; Waltman, P., Persistence in finite dimensional systems, SIAM J. Math. Anal., 20, 388 (1989) · Zbl 0692.34053
[36] Hallett, T. B.; Gregson, S.; Mugurungi, O.; Gonese, E.; Garnett, G. P., Assessing evidence for behaviour change affecting the course of HIV epidemics: a new mathematical modelling approach and application to data from Zimbabwe, Epidemics, 1, 108 (2009)
[37] Yang, Y. P.; Xiao, Y. N.; Wang, N.; Wu, J. H., Optimal control of drug therapy: melding pharmacokinetics with viral dynamics, Biosystems, 107, 174 (2012)
[38] Stafford, M. A.; Corey, L.; Cao, Y.; Daar, E. S.; Ho, D. D.; Perelson, A. S., Modeling plasma virus concentration during primary HIV infection, J. Theor. Biol., 203, 285 (2000)
[39] Sun, X. D.; Xiao, Y. N.; Peng, Z. H.; Wang, N., Modelling hiv/aids epidemic among men who have sex with men in china, BioMed Res. Int. (2013)
[40] Blower, S. M.; Dowlatabadi, H., Sensitivity and uncertainty analysis of complex-models of disease transmission an HIV model, as an example, Int. Stat. Rev., 62, 229 (1994) · Zbl 0825.62860
[41] Marino, S.; Hogue, I. B.; Ray, C. J.; Kirschner, D. E., A methodology for performing global uncertainty and sensitivity analysis in systems biology, J. Theor. Biol., 254, 178 (2008) · Zbl 1400.92013
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.