Mathematical Modelling of HIV-HCV Co-infection Dynamics in Presence of HIV Therapy

Q2 Agricultural and Biological Sciences Biomath Pub Date : 2022-08-11 DOI:10.55630/j.biomath.2022.07.158
Edison Mayanja, L. Luboobi, Juma Kasozi, R. Nsubuga
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Abstract

In this work, we formulated and analysed a deterministic model to study the HIV-HCV co-infection dynamics in presence of HIV therapy. The HCV chronic stage was split into two periods: the period before and the period after onset of cirrhosis. This was done because the HCV chronic stage of infection is long, asymptomatic and infectious. The effective reproduction numbers, one of our outcome measures, were computed using the next generation matrix method. Numerical simulations were performed to support the analytical results from the model. The different parameters in the model were subjected to a sensitivity analysis to determine their relative importance on the HIV-HCV co-infection dynamics. The results indicated that both HIV and HCV infections enhance each other; and in the long run, increasing the rates at which people are put on HIV treatment reduces the prevalence of HCV in the community; however, it increases the prevalence of HIV. Therefore, there should be increased safer sexual behaviour campaigns among individuals on HIV treatment.
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HIV治疗条件下HIV-HCV共感染动力学的数学模型
在这项工作中,我们制定并分析了一个确定性模型,以研究在HIV治疗的情况下HIV-HCV共感染的动力学。HCV慢性期分为两个时期:肝硬化发作前和发作后。之所以这样做,是因为丙型肝炎病毒的慢性感染期较长,无症状且具有传染性。有效繁殖数是我们的结果测量之一,使用下一代矩阵方法计算。进行了数值模拟,以支持模型的分析结果。对模型中的不同参数进行敏感性分析,以确定它们对HIV-HCV共感染动力学的相对重要性。结果表明,HIV和HCV感染相互增强;从长远来看,提高人们接受艾滋病毒治疗的比率可以降低社区中丙型肝炎的流行率;然而,它增加了艾滋病毒的流行率。因此,应在接受艾滋病毒治疗的个人中加强更安全的性行为宣传。
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来源期刊
Biomath
Biomath Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
6
审稿时长
20 weeks
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