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A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB
In this article, a novel fractional order model has been introduced in Caputo sense for HIV-TB co-infection in the presence of exogenous reinfection and recurrent TB along with the treatment for both HIV and TB. The main aim of considering the fractional order model is to incorporate the memory effe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8159726/ https://www.ncbi.nlm.nih.gov/pubmed/34075277 http://dx.doi.org/10.1007/s11071-021-06518-9 |
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author | A, Tanvi Aggarwal, Rajiv Raj, Yashi A. |
author_facet | A, Tanvi Aggarwal, Rajiv Raj, Yashi A. |
author_sort | A, Tanvi |
collection | PubMed |
description | In this article, a novel fractional order model has been introduced in Caputo sense for HIV-TB co-infection in the presence of exogenous reinfection and recurrent TB along with the treatment for both HIV and TB. The main aim of considering the fractional order model is to incorporate the memory effect of both diseases. We have analyzed both sub-models separately with fractional order. The basic reproduction number, which measures the contagiousness of the disease, is determined. The HIV sub-model is shown to have a locally asymptotically stable disease-free equilibrium point when the corresponding reproduction number, [Formula: see text] , is less than unity, whereas, for [Formula: see text] , the endemic equilibrium point comes into existence. For the TB sub-model, the disease-free equilibrium point has been proved to be locally asymptotically stable for [Formula: see text] . The existence of TB endemic equilibrium points in the presence of reinfection and recurrent TB for [Formula: see text] justifies the existence of backward bifurcation under certain restrictions on the parameters. Further, we numerically simulate the fractional order model to verify the analytical results and highlight the role of fractional order in co-infection modeling. The fractional order derivative is shown to have a crucial role in determining the transmission dynamics of HIV-TB co-infection. It is concluded that the memory effect plays a significant role in reducing the infection prevalence of HIV-TB co-infection. An increment in the number of recovered individuals can also be observed when the memory effect is taken into consideration by introducing fractional order model. |
format | Online Article Text |
id | pubmed-8159726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-81597262021-05-28 A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB A, Tanvi Aggarwal, Rajiv Raj, Yashi A. Nonlinear Dyn Original Paper In this article, a novel fractional order model has been introduced in Caputo sense for HIV-TB co-infection in the presence of exogenous reinfection and recurrent TB along with the treatment for both HIV and TB. The main aim of considering the fractional order model is to incorporate the memory effect of both diseases. We have analyzed both sub-models separately with fractional order. The basic reproduction number, which measures the contagiousness of the disease, is determined. The HIV sub-model is shown to have a locally asymptotically stable disease-free equilibrium point when the corresponding reproduction number, [Formula: see text] , is less than unity, whereas, for [Formula: see text] , the endemic equilibrium point comes into existence. For the TB sub-model, the disease-free equilibrium point has been proved to be locally asymptotically stable for [Formula: see text] . The existence of TB endemic equilibrium points in the presence of reinfection and recurrent TB for [Formula: see text] justifies the existence of backward bifurcation under certain restrictions on the parameters. Further, we numerically simulate the fractional order model to verify the analytical results and highlight the role of fractional order in co-infection modeling. The fractional order derivative is shown to have a crucial role in determining the transmission dynamics of HIV-TB co-infection. It is concluded that the memory effect plays a significant role in reducing the infection prevalence of HIV-TB co-infection. An increment in the number of recovered individuals can also be observed when the memory effect is taken into consideration by introducing fractional order model. Springer Netherlands 2021-05-28 2021 /pmc/articles/PMC8159726/ /pubmed/34075277 http://dx.doi.org/10.1007/s11071-021-06518-9 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper A, Tanvi Aggarwal, Rajiv Raj, Yashi A. A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB |
title | A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB |
title_full | A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB |
title_fullStr | A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB |
title_full_unstemmed | A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB |
title_short | A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB |
title_sort | fractional order hiv-tb co-infection model in the presence of exogenous reinfection and recurrent tb |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8159726/ https://www.ncbi.nlm.nih.gov/pubmed/34075277 http://dx.doi.org/10.1007/s11071-021-06518-9 |
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