Past works on partially diffusive models of diseases typically rely on a strong assumption regarding the initial data of their infection-related compartments in order to demonstrate uniform persistence in the case that the basic reproduction number $ \mathcal{R}_0 $ is above 1. Such a model for avian influenza was proposed, and its uniform persistence was proven for the case $ \mathcal{R}_0 > 1 $ when all of the infected bird population, recovered bird population and virus concentration in water do not initially vanish. Similarly, a work regarding a model of the Ebola virus disease required that the infected human population does not initially vanish to show an analogous result. We introduce a modification on the standard method of proving uniform persistence, extending both of these results by weakening their respective assumptions to requiring that only one (rather than all) infection-related compartment is initially non-vanishing. That is, we show that, given $ \mathcal{R}_0 > 1 $, if either the infected bird population or the viral concentration are initially nonzero anywhere in the case of avian influenza, or if any of the infected human population, viral concentration or population of deceased individuals who are under care are initially nonzero anywhere in the case of the Ebola virus disease, then their respective models predict uniform persistence. The difficulty which we overcome here is the lack of diffusion, and hence the inability to apply the minimum principle, in the equations of the avian influenza virus concentration in water and of the population of the individuals deceased due to the Ebola virus disease who are still in the process of caring.
Citation: Ryan Covington, Samuel Patton, Elliott Walker, Kazuo Yamazaki. Improved uniform persistence for partially diffusive models of infectious diseases: cases of avian influenza and Ebola virus disease[J]. Mathematical Biosciences and Engineering, 2023, 20(11): 19686-19709. doi: 10.3934/mbe.2023872
Past works on partially diffusive models of diseases typically rely on a strong assumption regarding the initial data of their infection-related compartments in order to demonstrate uniform persistence in the case that the basic reproduction number $ \mathcal{R}_0 $ is above 1. Such a model for avian influenza was proposed, and its uniform persistence was proven for the case $ \mathcal{R}_0 > 1 $ when all of the infected bird population, recovered bird population and virus concentration in water do not initially vanish. Similarly, a work regarding a model of the Ebola virus disease required that the infected human population does not initially vanish to show an analogous result. We introduce a modification on the standard method of proving uniform persistence, extending both of these results by weakening their respective assumptions to requiring that only one (rather than all) infection-related compartment is initially non-vanishing. That is, we show that, given $ \mathcal{R}_0 > 1 $, if either the infected bird population or the viral concentration are initially nonzero anywhere in the case of avian influenza, or if any of the infected human population, viral concentration or population of deceased individuals who are under care are initially nonzero anywhere in the case of the Ebola virus disease, then their respective models predict uniform persistence. The difficulty which we overcome here is the lack of diffusion, and hence the inability to apply the minimum principle, in the equations of the avian influenza virus concentration in water and of the population of the individuals deceased due to the Ebola virus disease who are still in the process of caring.
[1] | P. van den Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6 |
[2] | H. R. Thieme, Spectral bound and reproduction number for infinite-dimensional population structure and time heterogeneity, SIAM J. Appl. Math., 70 (2009), 188–211. https://doi.org/10.1137/080732870 doi: 10.1137/080732870 |
[3] | W. Wang, X. Q. Zhao, Basic reproduction numbers for reaction-diffusion epidemic models, SIAM J. Appl. Dyn. Syst., 11 (2012), 1652–1673. https://doi.org/10.1137/120872942 doi: 10.1137/120872942 |
[4] | K. Yamazaki, Global well-posedness of infectious disease models without life-time immunity: the cases of cholera and avian influenza, Math. Med. Biol., 35 (2018), 427–445. https://doi.org/10.1093/imammb/dqx016 doi: 10.1093/imammb/dqx016 |
[5] | H. M. Yin, On a reaction-diffusion system modelling infectious diseases without lifetime immunity, Eur. J. Appl. Math., 33 (2021), 803–827. https://doi.org/10.1017/S0956792521000231 doi: 10.1017/S0956792521000231 |
[6] | W. Wang, X. Q. Zhao, A nonlocal and time-delayed reaction-diffusion model of dengue transmission, SIAM J. Appl. Math., 71 (2011), 147–168. https://doi.org/10.1137/090775890 doi: 10.1137/090775890 |
[7] | Y. Lou, X. Q. Zhao, A reaction-diffusion malaria model with incubation period in the vector population, J. Math. Biol., 62 (2011), 543–568. https://doi.org/10.1007/s00285-010-0346-8 doi: 10.1007/s00285-010-0346-8 |
[8] | X. Q. Zhao, Global dynamics of a reaction and diffusion model for Lyme disease, J. Math. Biol., 65 (2012), 787–808. https://doi.org/10.1007/s00285-011-0482-9 doi: 10.1007/s00285-011-0482-9 |
[9] | K. Yamazaki, X. Wang, Global well-posedness and asymptotic behavior of solutions to a reaction-convection-diffusion cholera epidemic model, Discrete Contin. Dyn. Syst. Ser. -B, 21 (2016), 1297–1316. https://doi.org/10.3934/dcdsb.2016.21.1297 doi: 10.3934/dcdsb.2016.21.1297 |
[10] | K. Yamazaki, X. Wang, Global stability and uniform persistence of the reaction-convection-diffusion cholera epidemic model, Math. Biosci. Eng., 14 (2017), 559–579. https://doi.org/10.3934/mbe.2017033 doi: 10.3934/mbe.2017033 |
[11] | K. Yamazaki, Zika virus dynamics partial differential equations model with sexual transmission route, Nonlinear Anal. Real World Appl., 50 (2019), 290–315. https://doi.org/10.1016/j.nonrwa.2019.05.003 doi: 10.1016/j.nonrwa.2019.05.003 |
[12] | S. B. Hsu, J. Jiang, F. B. Wang, On a system of reaction-diffusion equations arising from competition with internal storage in an unstirred chemostat, J. Differ. Equations, 248 (2010), 2470–2496. https://doi.org/10.1016/j.jde.2009.12.014 doi: 10.1016/j.jde.2009.12.014 |
[13] | S. B. Hsu, F. B. Wang, X. Q. Zhao, Dynamics of a periodically pulsed bio-reactor model with a hydraulic storage zone, J. Dyn. Differ. Equations, 23 (2011), 817–842. https://doi.org/10.1007/s10884-011-9224-3 doi: 10.1007/s10884-011-9224-3 |
[14] | J. P. Grover, S. B. Hsu, F. B. Wang, Competition and coexistence in flowing habitats with a hydraulic storage zone, Math. Biosci., 222 (2009), 42–52. https://doi.org/10.1016/j.mbs.2009.08.006 doi: 10.1016/j.mbs.2009.08.006 |
[15] | S. B. Hsu, F. B. Wang, X. Q. Zhao, Global dynamics of zooplankton and harmful algae in flowing habitats, J. Differ. Equations, 255 (2013), 265–297. https://doi.org/10.1016/j.jde.2013.04.006 doi: 10.1016/j.jde.2013.04.006 |
[16] | X. Q. Zhao, Dynamical Systems in Population Biology, Springer-Verlag, New York, Inc., 2003. https://doi.org/10.1007/978-0-387-21761-1 |
[17] | N. K. Vaidya, F. B. Wang, X. Zou, Avian influenza dynamics in wild birds with bird mobility and spatial heterogeneous environment, Discrete Contin. Dyn. Syst. Ser. -B, 17 (2012), 2829–2848. https://doi.org/10.3934/dcdsb.2012.17.2829 doi: 10.3934/dcdsb.2012.17.2829 |
[18] | K. Yamazaki, Threshold dynamics of reaction-diffusion partial differential equations model of Ebola virus disease, Int. J. Biomath., 11 (2018), 1850108. https://doi.org/10.1142/S1793524518501085 doi: 10.1142/S1793524518501085 |
[19] | Z. J. Cheng, J. Shan, Novel coronavirus: where we are and what we know, Infection, 48 (2020), 155–163. https://doi.org/10.1007/s15010-020-01401-y doi: 10.1007/s15010-020-01401-y |
[20] | C. Yang, J. Wang, A mathematical model for the novel coronavirus epidemic in Wuhan, China, Math. Biosci. Eng., 17 (2020), 2708–2724. https://doi.org/10.3934/mbe.2020148 doi: 10.3934/mbe.2020148 |
[21] | J. D. Brown, G. Goekjian, R. Poulson, S. Valeika, D. E. Stallknecht, Avian influenza virus in water: Infectivity is dependent on pH, salinity and temperature, Vet. Microbiol., 136 (2009), 20–26. https://doi.org/10.1016/j.vetmic.2008.10.027 doi: 10.1016/j.vetmic.2008.10.027 |
[22] | V. S. Hinshaw, R. G. Webster, B. Turner, The perpetuation of orthomyxoviruses and paramyxoviruses in Canadian waterfowl, Can. J. Microbiol., 26 (1980), 622–629. https://doi.org/10.1139/m80-108 doi: 10.1139/m80-108 |
[23] | R. G. Webster, M. Yakhno, V. S. Hinshaw, W. J. Bean, K. G. Murti, Intestinal influenza: replication and characterization of influenza viruses in ducks, Virology, 84 (1978), 268–278. https://doi.org/10.1016/0042-6822(78)90247-7 doi: 10.1016/0042-6822(78)90247-7 |
[24] | World Health Organization, Ebola virus disease, 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/ebola-virus-disease. |
[25] | L. Evans, Partial Differential Equations, American Mathematics Society, Providence, Rhode Island, 1998. |
[26] | R. Covington, S. Patton, E. Walker, K. Yamazaki, Stability analysis on a partially diffusive model of the coronavirus disease of 2019, submitted. |
[27] | W. Puryear, K. Sawatzki, N. Hill, A. Foss, J. J. Stone, L. Doughty, et al., Pathogenic Avian Influenza A(H5N1) virus outbreak in New England Seals, United States, Emerging Infect. Dis., 29 (2023), 786–791. https://doi.org/10.3201/eid2904.221538 doi: 10.3201/eid2904.221538 |
[28] | T. Berge, J. M. S. Luburma, G. M. Moremedi, N. Morris, R. Kondera-Shava, A simple mathematical model for Ebola in Africa, J. Biol. Dyn., 11 (2017), 42–74. https://doi.org/10.1080/17513758.2016.1229817 doi: 10.1080/17513758.2016.1229817 |
[29] | World Health Organization, Ebola disease caused by Sudan ebolavirus - Uganda, 2023. Available from: https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON433. |
[30] | C. Freeman, Meet the world's bravest undertakers - Liberia's Ebola burial squad, The Telegraph, 2014. Available from: https://www.telegraph.co.uk/news/worldnews/ebola/11024042/Meet-the-worlds-bravest-undertakers-Liberias-Ebola-burial-squad.html. |
[31] | H. L. Smith, X. Q. Zhao, Robust persistence for semidynamical systems, Nonlinear Anal. Theory Methods Appl., 47 (2001), 6169–6179. https://doi.org/10.1016/S0362-546X(01)00678-2 doi: 10.1016/S0362-546X(01)00678-2 |
[32] | H. L. Smith, Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems, Mathematical Surveys and Monographs, American Mathematical Society, Providence, Rhode Island, 41 (1995). |
[33] | H. R. Thieme, Convergence results and a Poincar$\acute{e}$-Bendixson trichotomy for asymptotically autonomous differential equations, J. Math. Biol., 30 (1992), 755–763. https://doi.org/10.1007/BF00173267 doi: 10.1007/BF00173267 |
[34] | P. Magal, X. Q. Zhao, Global attractors and steady states for uniformly persistent dynamical systems, SIAM J. Math. Anal., 37 (2005), 251–275. https://doi.org/10.1137/S0036141003439173 doi: 10.1137/S0036141003439173 |
[35] | K. Deimling, Nonlinear Functional Analysis, Dover Publications, Inc., Mineola, New York, 1985. https://doi.org/10.1007/978-3-662-00547-7 |
[36] | J. K. Hale, Asymptotic Behavior of Dissipative Systems, Mathematical Surveys and Monographs, American Mathematics Society, Providence, Rhode Island, 1988. https://doi.org/10.1090/surv/025 |
[37] | J. Wang, C. Yang, K. Yamazaki, A partially diffusive cholera model based on a general second-order differential operator, J. Math. Anal. Appl., 501 (2021), 125181. https://doi.org/10.1016/j.jmaa.2021.125181 doi: 10.1016/j.jmaa.2021.125181 |