Ayele Tigabu Kasie, Doungmo Goufo Emile Franc, Mugisha Stella
Department of Mathematics, College of Natural and Applied Science, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.
Department of Mathematical Sciences, College of Science, Engineering and Technology, University of South Africa, South Africa.
PLoS One. 2024 Dec 10;19(12):e0312539. doi: 10.1371/journal.pone.0312539. eCollection 2024.
The co-epidemics of HIV/AIDS and Tuberculosis (TB) outbreak is one of a serious disease in Ethiopia that demands integrative approaches to combat its transmission. In contrast, epidemiological co-infection models often considered a single latent case and recovered individuals with TB. To bridge this gap, we presented a new optimal HIV-TB co-infection model that considers both high risk and low risk latent TB cases with taking into account preventive efforts of both HIV and TB diseases, case finding for TB and HIV/AIDS treatment. This study aimed to develop optimal HIV/AIDS-TB co-infection mathematical model to explore the best cost-effective measure to mitigate the disease burden. The model is analysed analytically by firstly segregating TB and HIV only sub models followed by the full TB-HIV co-infection model. The Disease Free Equilibrium (DFE) and Endemic Equilibrium (EE) points are found and the basic reproduction number R0 is obtained using the next generation matrix method (NGM). Based on the threshold value R0, the stabilities of equilibria for each sub-model are analysed. The DFE point is locally asymptotically stable when R0 < 1 and unstable when R0 > 1. The EE point is also asymptotically stable when R0 > 1 and does not exist otherwise. At R0 = 1, the existence of backward bifurcation phenomena is discussed. To curtail the cost and disease fatality, an optimal control model is formulated via time based controlling efforts. The optimal mathematical model is analysed both analytically and numerically. The numerical results are presented for two or more control measures at a time. In addition, the Incremental Cost-Effectiveness Ratio(ICER) has identified the best strategy which is crucial in limited resource. Hence, the model outcomes illustrated that applying HIV/AIDS prevention efforts and TB case finding concurrently is the most cost-effective strategy to offer substantial relief from the burden of the pandemic in the community. All results found in this study have significant public health lessons. We anticipated that the results will notify evidence based approaches to control the disease. Thus, this study will aids in the fight against HIV/AIDS, TB, and their co-infection policy-makers and other concerned organizations.
艾滋病毒/艾滋病和结核病共同流行疫情是埃塞俄比亚的严重疾病之一,需要采取综合方法来抗击其传播。相比之下,流行病学共感染模型通常只考虑单个潜伏病例以及结核病康复个体。为弥补这一差距,我们提出了一种新的最优艾滋病毒-结核病共感染模型,该模型考虑了高风险和低风险潜伏结核病病例,同时兼顾了艾滋病毒和结核病的预防措施、结核病病例发现以及艾滋病毒/艾滋病治疗。本研究旨在建立最优艾滋病毒/艾滋病-结核病共感染数学模型,以探索减轻疾病负担的最佳成本效益措施。该模型首先通过分离仅结核病和仅艾滋病毒子模型,然后是完整的结核病-艾滋病毒共感染模型进行分析。找到无病平衡点(DFE)和地方病平衡点(EE),并使用下一代矩阵法(NGM)获得基本再生数R0。基于阈值R0,分析每个子模型平衡点的稳定性。当R0<1时,DFE点局部渐近稳定,当R0>1时不稳定。当R0>1时,EE点也渐近稳定,否则不存在。在R0 = 1时,讨论向后分岔现象的存在。为了降低成本和疾病死亡率,通过基于时间的控制措施制定了最优控制模型。对最优数学模型进行了分析和数值分析。一次给出两种或更多控制措施的数值结果。此外,增量成本效益比(ICER)确定了在资源有限情况下至关重要的最佳策略。因此,模型结果表明,同时应用艾滋病毒/艾滋病预防措施和结核病病例发现是最具成本效益的策略,可大幅减轻社区大流行的负担。本研究中发现的所有结果都有重要的公共卫生意义。我们预计这些结果将为控制疾病提供基于证据的方法。因此,本研究将有助于抗击艾滋病毒/艾滋病、结核病及其共感染的政策制定者和其他相关组织。