Musa Salihu S, Yusuf Abdullahi, Bakare Emmanuel A, Abdullahi Zainab U, Adamu Lukman, Mustapha Umar T, He Daihai
Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
Department of Mathematics, Kano University of Science and Technology, Wudil, Kano, Nigeria.
Math Biosci Eng. 2022 Sep 6;19(12):13114-13136. doi: 10.3934/mbe.2022613.
Epidemic models have been broadly used to comprehend the dynamic behaviour of emerging and re-emerging infectious diseases, predict future trends, and assess intervention strategies. The symptomatic and asymptomatic features and environmental factors for Lassa fever (LF) transmission illustrate the need for sophisticated epidemic models to capture more vital dynamics and forecast trends of LF outbreaks within countries or sub-regions on various geographic scales. This study proposes a dynamic model to examine the transmission of LF infection, a deadly disease transmitted mainly by rodents through environment. We extend prior LF models by including an infectious stage to mild and severe as well as incorporating environmental contributions from infected humans and rodents. For model calibration and prediction, we show that the model fits well with the LF scenario in Nigeria and yields remarkable prediction results. Rigorous mathematical computation divulges that the model comprises two equilibria. That is disease-free equilibrium, which is locally-asymptotically stable (LAS) when the basic reproduction number, $ {\mathcal{R}}_{0} $, is $ < 1 $; and endemic equilibrium, which is globally-asymptotically stable (GAS) when $ {\mathcal{R}}_{0} $ is $ > 1 $. We use time-dependent control strategy by employing Pontryagin's Maximum Principle to derive conditions for optimal LF control. Furthermore, a partial rank correlation coefficient is adopted for the sensitivity analysis to obtain the model's top rank parameters requiring precise attention for efficacious LF prevention and control.
流行病模型已被广泛用于理解新出现和再次出现的传染病的动态行为、预测未来趋势以及评估干预策略。拉沙热(LF)传播的症状性和无症状特征以及环境因素表明,需要复杂的流行病模型来捕捉更重要的动态,并预测不同地理尺度上国家或次区域内拉沙热疫情的趋势。本研究提出了一个动态模型,以研究拉沙热感染的传播,拉沙热是一种主要由啮齿动物通过环境传播的致命疾病。我们扩展了先前的拉沙热模型,纳入了轻度和重度感染阶段,并考虑了受感染人类和啮齿动物对环境的影响。对于模型校准和预测,我们表明该模型与尼日利亚的拉沙热情况拟合良好,并产生了显著的预测结果。严格的数学计算表明,该模型包含两个平衡点。即无病平衡点,当基本再生数${\mathcal{R}}_{0}<1$时,它是局部渐近稳定(LAS)的;以及地方病平衡点,当${\mathcal{R}}_{0}>1$时,它是全局渐近稳定(GAS)的。我们采用时间依赖控制策略,运用庞特里亚金极大值原理推导最优拉沙热控制的条件。此外,采用偏秩相关系数进行敏感性分析,以获得模型中对于有效预防和控制拉沙热需要精确关注的顶级参数。