Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus.
Infectious disease modeling is crucial for predicting disease progression over time and helps guide decision makers in public health policy. Hepatitis C virus (HCV) prevalence is still increasing in Zimbabwe, a low-middle-income country (LMIC), despite the availability of effective treatments, and t...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0329543 |
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| author | Tinashe Victor Mupedza Laurette Mhlanga Dennis Mamutse Mlyashimbi Helikumi Paride Oresto Lolika Shingirai Tangakugara Murambiwa Adquate Mhlanga |
| author_facet | Tinashe Victor Mupedza Laurette Mhlanga Dennis Mamutse Mlyashimbi Helikumi Paride Oresto Lolika Shingirai Tangakugara Murambiwa Adquate Mhlanga |
| author_sort | Tinashe Victor Mupedza |
| collection | DOAJ |
| description | Infectious disease modeling is crucial for predicting disease progression over time and helps guide decision makers in public health policy. Hepatitis C virus (HCV) prevalence is still increasing in Zimbabwe, a low-middle-income country (LMIC), despite the availability of effective treatments, and the reasons for this increase are not well understood. Our study employed a mathematical model to explain the impact of poor treatment adherence on HCV transmission dynamics in Zimbabwe. We computed the basic reproduction number ([Formula: see text]), a vital metric of disease spread. Equilibrium states of the model were determined, and their stability was investigated. The study demonstrated that an adherence level exceeding 52% causes the reproduction number to drop below 1, curtailing further spread. Our HCV model indicates that variations in re-susceptibility minimally impact outcomes, suggesting that re-susceptibility can often be excluded in such analyses. Our model unraveled the synergistic impact of simultaneously enhancing the recovery rate of acutely infected individuals and treatment adherence on reducing [Formula: see text]. The study underlines the pressing need for stronger health interventions, including patient education, financial assistance, and rigorous monitoring, to improve treatment adherence. These interventions are paramount in curbing HCV proliferation, particularly in LMICs like Zimbabwe, and can serve as a template for similar settings globally. |
| format | Article |
| id | doaj-art-affed03fdcde4d53bc5ce747640f3775 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-affed03fdcde4d53bc5ce747640f37752025-08-23T05:31:52ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01208e032954310.1371/journal.pone.0329543Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus.Tinashe Victor MupedzaLaurette MhlangaDennis MamutseMlyashimbi HelikumiParide Oresto LolikaShingirai Tangakugara MurambiwaAdquate MhlangaInfectious disease modeling is crucial for predicting disease progression over time and helps guide decision makers in public health policy. Hepatitis C virus (HCV) prevalence is still increasing in Zimbabwe, a low-middle-income country (LMIC), despite the availability of effective treatments, and the reasons for this increase are not well understood. Our study employed a mathematical model to explain the impact of poor treatment adherence on HCV transmission dynamics in Zimbabwe. We computed the basic reproduction number ([Formula: see text]), a vital metric of disease spread. Equilibrium states of the model were determined, and their stability was investigated. The study demonstrated that an adherence level exceeding 52% causes the reproduction number to drop below 1, curtailing further spread. Our HCV model indicates that variations in re-susceptibility minimally impact outcomes, suggesting that re-susceptibility can often be excluded in such analyses. Our model unraveled the synergistic impact of simultaneously enhancing the recovery rate of acutely infected individuals and treatment adherence on reducing [Formula: see text]. The study underlines the pressing need for stronger health interventions, including patient education, financial assistance, and rigorous monitoring, to improve treatment adherence. These interventions are paramount in curbing HCV proliferation, particularly in LMICs like Zimbabwe, and can serve as a template for similar settings globally.https://doi.org/10.1371/journal.pone.0329543 |
| spellingShingle | Tinashe Victor Mupedza Laurette Mhlanga Dennis Mamutse Mlyashimbi Helikumi Paride Oresto Lolika Shingirai Tangakugara Murambiwa Adquate Mhlanga Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus. PLoS ONE |
| title | Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus. |
| title_full | Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus. |
| title_fullStr | Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus. |
| title_full_unstemmed | Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus. |
| title_short | Modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis C virus. |
| title_sort | modeling the effects of treatment adherence challenges on the transmission dynamics of hepatitis c virus |
| url | https://doi.org/10.1371/journal.pone.0329543 |
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