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Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy
Globally, it is estimated that of the 36.7 million people infected with human immunodeficiency virus (HIV), 6.3% are coinfected with hepatitis C virus (HCV). Coinfection with HIV reduces the chance of HCV spontaneous clearance. In this work, we formulated and analysed a deterministic model to study...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566217/ https://www.ncbi.nlm.nih.gov/pubmed/33082837 http://dx.doi.org/10.1155/2020/2106570 |
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author | Mayanja, Edison Luboobi, Livingstone S. Kasozi, Juma Nsubuga, Rebecca N. |
author_facet | Mayanja, Edison Luboobi, Livingstone S. Kasozi, Juma Nsubuga, Rebecca N. |
author_sort | Mayanja, Edison |
collection | PubMed |
description | Globally, it is estimated that of the 36.7 million people infected with human immunodeficiency virus (HIV), 6.3% are coinfected with hepatitis C virus (HCV). Coinfection with HIV reduces the chance of HCV spontaneous clearance. In this work, we formulated and analysed a deterministic model to study the HIV and HCV coinfection dynamics in absence of therapy. Due to chronic stage of HCV infection being long, asymptomatic, and infectious, our model formulation was based on the splitting of the chronic stage into the following: before onset of cirrhosis and its complications and after onset of cirrhosis. We computed the basic reproduction numbers using the next generation matrix method. We performed numerical simulations to support the analytical results. We carried out sensitivity analysis to determine the relative importance of the different parameters influencing the HIV-HCV coinfection dynamics. The findings reveal that, in the long run, there is a substantial number of individuals coinfected with HIV and latent HCV. Therefore, HIV and latently HCV-infected individuals need to seek early treatment so as to slow down the progression of HIV to AIDS and latent HCV to advanced HCV. |
format | Online Article Text |
id | pubmed-7566217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-75662172020-10-19 Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy Mayanja, Edison Luboobi, Livingstone S. Kasozi, Juma Nsubuga, Rebecca N. Comput Math Methods Med Research Article Globally, it is estimated that of the 36.7 million people infected with human immunodeficiency virus (HIV), 6.3% are coinfected with hepatitis C virus (HCV). Coinfection with HIV reduces the chance of HCV spontaneous clearance. In this work, we formulated and analysed a deterministic model to study the HIV and HCV coinfection dynamics in absence of therapy. Due to chronic stage of HCV infection being long, asymptomatic, and infectious, our model formulation was based on the splitting of the chronic stage into the following: before onset of cirrhosis and its complications and after onset of cirrhosis. We computed the basic reproduction numbers using the next generation matrix method. We performed numerical simulations to support the analytical results. We carried out sensitivity analysis to determine the relative importance of the different parameters influencing the HIV-HCV coinfection dynamics. The findings reveal that, in the long run, there is a substantial number of individuals coinfected with HIV and latent HCV. Therefore, HIV and latently HCV-infected individuals need to seek early treatment so as to slow down the progression of HIV to AIDS and latent HCV to advanced HCV. Hindawi 2020-10-06 /pmc/articles/PMC7566217/ /pubmed/33082837 http://dx.doi.org/10.1155/2020/2106570 Text en Copyright © 2020 Edison Mayanja et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Mayanja, Edison Luboobi, Livingstone S. Kasozi, Juma Nsubuga, Rebecca N. Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy |
title | Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy |
title_full | Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy |
title_fullStr | Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy |
title_full_unstemmed | Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy |
title_short | Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy |
title_sort | mathematical modelling of hiv-hcv coinfection dynamics in absence of therapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566217/ https://www.ncbi.nlm.nih.gov/pubmed/33082837 http://dx.doi.org/10.1155/2020/2106570 |
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