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Dynamical analysis for hybrid virus infection system in switching environment |
Dong-Xi Li(李东喜)1, Ni Zhang(张妮)2 |
1 College of Data Science, Taiyuan University of Technology, Taiyuan 030024, China; 2 College of Mathematics, Taiyuan University of Technology, Taiyuan 030024, China |
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Abstract We investigate the dynamical behavior of hybrid virus infection systems with nonlytic immune response in switching environment, which is modeled as a stochastic process of telegraph noise and represented as a multi-state Markov chains. Firstly, The existence of unique positive solution and boundedness of the new hybrid system is proved. Furthermore, the sufficient conditions for extinction and persistence of virus are established. Finally, stochastic simulations are performed to test and demonstrate the conclusions. As a consequence, our work suggests that stochastic switching environment plays a crucial role in the process of virus prevention and treatment.
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Received: 05 March 2020
Revised: 16 April 2020
Accepted manuscript online: 23 April 2020
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PACS:
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02.50.-r
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(Probability theory, stochastic processes, and statistics)
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05.40.-a
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(Fluctuation phenomena, random processes, noise, and Brownian motion)
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 11571009) and the Applied Basic Research Programs of Shanxi Province of China (Grant No. 201901D111086). |
Corresponding Authors:
Dong-Xi Li
E-mail: dxli0426@126.com
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Cite this article:
Dong-Xi Li(李东喜), Ni Zhang(张妮) Dynamical analysis for hybrid virus infection system in switching environment 2020 Chin. Phys. B 29 090201
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[1] |
Levin B R, Lipsitch M and Bonhoeffer S 1999 Science 283 806
|
[2] |
Bowers R 2001 Proc. R. Soc. B: Biol. Sci. 268 243
|
[3] |
Nowak M A and Bangham C R M 1996 Science 272 74
|
[4] |
Liu W M 1997 Theor. Popul. Biol. 52 224
|
[5] |
Doherty P C and Christensen J P 2000 Annu. Rev. Immunol. 18 561
|
[6] |
Lin H and Shuai J W 2010 New J. Phys. 12 043051
|
[7] |
Nagai M, Kubota R, Leist T, Jacobson S, Greten T and Schneck J 2001 J. Infectious Dis. 183 197
|
[8] |
Wodarz D 2003 J. Gen. Virol. 84 1743
|
[9] |
Wodarz D, Christensen J P and Thomsen A R 2002 Trends Immunol. 23 194
|
[10] |
Dalal N, Greenhalgh D and Mao X 1993 Math. Biosci. 114 81
|
[11] |
Merrill S J 1989 Modeling the Interaction of HIV with Cells of the Immune System (Berlin: Springer-Verlag) pp. 371-385
|
[12] |
Perelson A, Kirschner D and Boer R 1993 Math. Biosci. 114 81
|
[13] |
Wain-Hobson S 2000 J. Virol. 74 10304
|
[14] |
Bartholdy C, Christensen J P, Wodarz D and Thomsen A R 2000 J. Virol. 74 10304
|
[15] |
Li D X and Cui X W 2017 Chaos Solitons Fractals. 99 124
|
[16] |
Li D X, Zhao Y and Song S L 2019 Physica A 528 121463
|
[17] |
Wang K F, Wang W D and Liu X N 2006 Comput. Math. Appl. 51 1593
|
[18] |
Chen M Y and You L 2015 Disc. Dyn. Nat. Soc. 2015 1
|
[19] |
Greenhalgh D, Liang Y and Mao X 2016 Physica A 462 684
|
[20] |
Xu W, Wang X Y and Liu X Z 2015 Chin. Phys. B 24 050204
|
[21] |
Gray A, Greenhalgh D, Mao X and Pan J F 2012 J. Math. Anal. Appl. 394 496
|
[22] |
Du N H, Kon R, Sato K and Takeuchi Y 2004 Comput. Appl. Math. 170 399
|
[23] |
Iannelli M, Milner F A and Pugliese A 1992 SIAM J. Math. Anal. 23 662
|
[24] |
Feng Z, Huang W and Castillo-Chavez C 2005 J. Differ. Eq. 218 292
|
[25] |
Neal P 2006 Adv. Appl. Probab. 38 943
|
[26] |
Neal P 2008 Adv. Appl. Probab. 45 513
|
[27] |
Li J, Ma Z and Zhou Y 2006 Acta Math. Sci. 26 83
|
[28] |
Van P, Driessche D and Watmough J 2000 J. Math. Biol. 40 525
|
[29] |
Andersson P and Lindenstrand D 2011 J. Math. Biol. 62 333
|
[30] |
Zhang X H and Jiang D Q 2016 Appl. Math. Lett. 59 87
|
[31] |
Anderson D R 1975 Ecology 56 1281
|
[32] |
Padilla D K and Adolph S C 1996 Evolutionary Ecol. 10 105
|
[33] |
Peccoud J and Ycart B 1995 Theor. Popul. Biol. 48 222
|
[34] |
Caswell R and Cohen J E 1995 Theor. Popul. Biol. 176 301
|
[35] |
Yang Q S and Mao X R 2013 Nonlinear Anal.: Real World Appl. 14 1434
|
[36] |
Liu M and Wang K 2011 J. Biol. Syst. 19 183
|
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