| Global threshold dynamics in an HIV virus model with nonlinear infection rate and distributed invasion and production delays. | |
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MedLine Citation:
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PMID: 23458310 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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We consider a mathematical model that describes the interactions of the HIV virus, CD4 cells and CTLs within host, which is a modification of some existing models by incorporating (i) two distributed kernels reflecting the variance of time for virus to invade into cells and the variance of time for invaded virions to reproduce within cells; (ii) a nonlinear incidence function f for virus infections, and (iii) a nonlinear removal rate function h for infected cells. By constructing Lyapunov functionals and subtle estimates of the derivatives of these Lyapunov functionals, we shown that the model has the threshold dynamics: if the basic reproduction number (BRN) is less than or equal to one, then the infection free equilibrium is globally asymptotically stable, meaning that HIV virus will be cleared; whereas if the BRN is larger than one, then there exist an infected equilibrium which is globally asymptotically stable, implying that the HIV-1 infection will persist in the host and the viral concentration will approach a positive constant level. This together with the dependence/independence of the BRN on f and h reveals the effect of the adoption of these nonlinear functions. |
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Authors:
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Zhaohui Yuan; Xingfu Zou |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Mathematical biosciences and engineering : MBE Volume: 10 ISSN: 1551-0018 ISO Abbreviation: Math Biosci Eng Publication Date: 2013 Apr |
Date Detail:
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Created Date: 2013-03-05 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101197794 Medline TA: Math Biosci Eng Country: United States |
Other Details:
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Languages: eng Pagination: 483-98 Citation Subset: IM |
Affiliation:
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College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, China. yzhh312@tom.com. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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