Center for Pharmacometrics and Systems Pharmacology, University of Florida, USA.
Department of Mathematical Sciences, Florida Atlantic University, USA.
Math Biosci Eng. 2023 Jan;20(2):4040-4068. doi: 10.3934/mbe.2023189. Epub 2022 Dec 19.
In this paper, we introduce a novel multi-scale network model of two epidemics: HIV infection and opioid addiction. The HIV infection dynamics is modeled on a complex network. We determine the basic reproduction number of HIV infection, $ \mathcal{R}{v} $, and the basic reproduction number of opioid addiction, $ \mathcal{R}{u} $. We show that the model has a unique disease-free equilibrium which is locally asymptotically stable when both $ \mathcal{R}{u} $ and $ \mathcal{R}{v} $ are less than one. If $ \mathcal{R}{u} > 1 $ or $ \mathcal{R}{v} > 1 $, then the disease-free equilibrium is unstable and there exists a unique semi-trivial equilibrium corresponding to each disease. The unique opioid only equilibrium exist when the basic reproduction number of opioid addiction is greater than one and it is locally asymptotically stable when the invasion number of HIV infection, $ \mathcal{R}^{1}{v_i} $ is less than one. Similarly, the unique HIV only equilibrium exist when the basic reproduction number of HIV is greater than one and it is locally asymptotically stable when the invasion number of opioid addiction, $ \mathcal{R}^{2}{u_i} $ is less than one. Existence and stability of co-existence equilibria remains an open problem. We performed numerical simulations to better understand the impact of three epidemiologically important parameters that are at the intersection of two epidemics: $ q_v $ the likelihood of an opioid user being infected with HIV, $ q_u $ the likelihood of an HIV-infected individual becoming addicted to opioids, and $ \delta $ recovery from opioid addiction. Simulations suggest that as the recovery from opioid use increases, the prevalence of co-affected individuals, those who are addicted to opioids and are infected with HIV, increase significantly. We demonstrate that the dependence of the co-affected population on $ q_u $ and $ q_v $ are not monotone.
在本文中,我们介绍了一种新的两种传染病(HIV 感染和阿片类药物成瘾)的多尺度网络模型。HIV 感染动力学建模于复杂网络上。我们确定了 HIV 感染的基本繁殖数,$ \mathcal{R}{v} $,以及阿片类药物成瘾的基本繁殖数,$ \mathcal{R}{u} $。我们表明,当$ \mathcal{R}{u} $和$ \mathcal{R}{v} $均小于 1 时,模型具有唯一的无病平衡点,该平衡点在局部渐近稳定。如果$ \mathcal{R}{u} > 1 $或$ \mathcal{R}{v} > 1 $,则无病平衡点不稳定,并且存在与每种疾病相对应的唯一半平凡平衡点。当阿片类药物成瘾的基本繁殖数大于 1 时,存在唯一的阿片类药物仅平衡点,当 HIV 感染的入侵数,$ \mathcal{R}^{1}{v_i} $小于 1 时,该平衡点在局部渐近稳定。类似地,当 HIV 的基本繁殖数大于 1 时,存在唯一的 HIV 仅平衡点,当阿片类药物成瘾的入侵数,$ \mathcal{R}^{2}{u_i} $小于 1 时,该平衡点在局部渐近稳定。共存平衡点的存在和稳定性仍然是一个未解决的问题。我们进行了数值模拟,以更好地理解两种传染病交叉点的三个流行病学上重要的参数的影响:$ q_v $阿片类药物使用者感染 HIV 的可能性,$ q_u $感染 HIV 的个体成瘾于阿片类药物的可能性,以及$ \delta $阿片类药物成瘾的康复。模拟表明,随着阿片类药物使用的康复率增加,同时感染 HIV 和成瘾于阿片类药物的共同感染个体的流行率显著增加。我们证明了共同感染人群对$ q_u $和$ q_v $的依赖性不是单调的。