Omame Andrew, Abbas Mujahid
Department of Mathematics, Federal University of Technology, Owerri, Nigeria.
Abdus Salam School of Mathematical Sciences, Government College University Katchery Road, Lahore 54000, Pakistan.
Healthc Anal (N Y). 2023 Nov;3:100151. doi: 10.1016/j.health.2023.100151. Epub 2023 Feb 24.
This paper aims to study the impacts of COVID-19 and dengue vaccinations on the dynamics of zika transmission by developing a vaccination model with the incorporation of saturated incidence rates. Analyses are performed to assess the qualitative behavior of the model. Carrying out bifurcation analysis of the model, it was concluded that co-infection, super-infection and also re-infection with same or different disease could trigger backward bifurcation. Employing well-formulated Lyapunov functions, the model's equilibria are shown to be globally stable for a certain scenario. Moreover, global sensitivity analyses are performed out to assess the impact of dominant parameters that drive each disease's dynamics and its co-infection. Model fitting is performed on the actual data for the state of Amazonas in Brazil. The fittings reveal that our model behaves very well with the data. The significance of saturated incidence rates on the dynamics of three diseases is also highlighted. Based on the numerical investigation of the model, it was observed that increased vaccination efforts against COVID-19 and dengue could positively impact zika dynamics and the co-spread of triple infections.
本文旨在通过建立一个纳入饱和发病率的疫苗接种模型，研究新冠病毒（COVID-19）疫苗接种和登革热疫苗接种对寨卡病毒传播动态的影响。进行分析以评估该模型的定性行为。对该模型进行分岔分析后得出结论，同一疾病或不同疾病的共同感染、重复感染可能引发反向分岔。通过使用精心构建的李雅普诺夫函数，该模型的平衡点在特定情况下被证明是全局稳定的。此外，还进行了全局敏感性分析，以评估驱动每种疾病动态及其共同感染的主要参数的影响。对巴西亚马孙州的实际数据进行了模型拟合。拟合结果表明我们的模型与数据拟合得很好。还强调了饱和发病率对三种疾病动态的重要性。基于对该模型的数值研究，观察到加强针对COVID-19和登革热的疫苗接种工作可能对寨卡病毒动态以及三重感染的共同传播产生积极影响。
