从流行病学的角度来看,不同新兴病毒性疾病的共同循环是一个巨大的挑战。症状的相似性,病毒共同感染的病例,交叉反应会误导疾病的诊断。在这篇文章中,一种新的COVID-19,Zika,基孔肯雅,并开发和研究了登革热协动力学,以评估COVID-19对寨卡的影响,登革热,和基孔肯雅动力学,反之亦然。进行了局部和全局稳定性分析。该模型在一定条件下经历了向后分叉。还对模型的参数进行全局敏感性分析,以确定最主要的参数。如果将zika相关的再现数0Z用作响应函数,那么重要的参数是:寨卡病媒人传播的有效接触率(β2h,正相关),人的自然死亡率(h,正相关),和向量招募率(Φv,也呈正相关)。此外,使用共同感染COVID-19和Zika(CZh)的个体类别作为反应函数,最主要的参数是:COVID-19传播的有效接触率(β1,正相关),寨卡病媒人传播的有效接触率(β2h,正相关)。在地方性环境下充分控制所有疾病的共同循环,以COVID-19,Zika,登革热,基孔肯雅热的预防措施被纳入模型,并使用Pontryagin原理进行分析。该模型适合真实的COVID-19,Zika,登革热,和圣埃斯皮里图(所有疾病共同流通的城市)的基孔肯雅数据集,并对每种疾病的累积病例进行了预测。通过模拟,结果表明,预防COVID-19可以极大地减轻寨卡共感染的负担,登革热,还有基孔肯雅.还强调了COVID-19大流行对控制虫媒病毒疾病的负面影响。此外,据观察,zika的预防控制,登革热,基孔肯雅热可以显著减轻与COVID-19合并感染的负担。
The co-circulation of different emerging viral diseases is a big challenge from an epidemiological point of view. The similarity of symptoms, cases of virus co-infection, and cross-reaction can mislead in the diagnosis of the disease. In this article, a new mathematical model for COVID-19,
zika, chikungunya, and dengue co-dynamics is developed and studied to assess the impact of COVID-19 on
zika, dengue, and chikungunya dynamics and vice-versa. The local and global stability analyses are carried out. The model is shown to undergo a backward bifurcation under a certain condition. Global sensitivity analysis is also performed on the parameters of the model to determine the most dominant parameters. If the
zika-related reproduction number ℛ 0Z is used as the response function, then important parameters are: the effective contact rate for vector-to-human transmission of
zika ( β 2 h , which is positively correlated), the human natural death rate ( ϑ h , positively correlated), and the vector recruitment rate ( Ψ v , also positively correlated). In addition, using the class of individuals co-infected with COVID-19 and zika ( ℐ CZ h ) as response function, the most dominant parameters are: the effective contact rate for COVID-19 transmission ( β 1 , positively correlated), the effective contact rate for vector-to-human transmission of zika ( β 2 h , positively correlated). To control the co-circulation of all the diseases adequately under an endemic setting, time dependent controls in the form of COVID-19, zika, dengue, and chikungunya preventions are incorporated into the model and analyzed using the Pontryagin\'s principle. The model is fitted to real COVID-19,
zika, dengue, and chikungunya datasets for Espirito Santo (a city with the co-circulation of all the diseases), in Brazil and projections made for the cumulative cases of each of the diseases. Through simulations, it is shown that COVID-19 prevention could greatly reduce the burden of co-infections with zika, dengue, and chikungunya. The negative impact of the COVID-19 pandemic on the control of the arbovirus diseases is also highlighted. Furthermore, it is observed that prevention controls for zika, dengue, and chikungunya can significantly reduce the burden of co-infections with COVID-19.