Modeling the dynamics of Lassa fever in Nigeria

Mayowa M. Ojo, B. Gbadamosi, Temitope O. Benson, O. Adebimpe, A. L. Georgina
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引用次数: 4

Abstract

Lassa fever is a zoonotic disease spread by infected rodents known as multimammate rats. The disease has posed a significant and major health challenge in West African countries, including Nigeria. To have a deeper understanding of Lassa fever epidemiology in Nigeria, we present a deterministic dynamical model to study its dynamical transmission behavior in the population. To mimic the disease’s biological history, we divide the population into two groups: humans and rodents. We established the quantity known as reproduction number $${\mathcal {R}}_{0}$$ . The results show that if $${\mathcal {R}}_{0} <1$$ then the system is stable, otherwise it is unstable. The model fitting was performed using the nonlinear least square method on cumulative reported cases from Nigeria between 2018 and 2020 to obtain the best fit that describes the dynamics of this disease in Nigeria. In addition, sensitivity analysis was performed, and the numerical solution of the system was derived using an iterative scheme, the fifth-order Runge–Kutta method. Using different numeric values for each parameter, we investigate the effect of all highest sensitivity indices’ parameters on the population of infected humans and infected rodents. Our findings indicate that any control strategies and methods that reduce rodent populations and the risk of transmission from rodents to humans and rodents would aid in the population’s control of Lassa fever.
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模拟尼日利亚拉沙热的动态
拉沙热是一种人畜共患疾病,由被称为多母鼠的受感染啮齿动物传播。该疾病对包括尼日利亚在内的西非国家构成了重大的健康挑战。为了更深入地了解尼日利亚拉沙热流行病学,我们提出了一个确定性动力学模型来研究其在人群中的动态传播行为。为了模拟这种疾病的生物学历史,我们将种群分为两组:人类和啮齿动物。我们建立了称为繁殖数$${\mathcal {R}}_{0}$$的数量。结果表明:$${\mathcal {R}}_{0} <1$$为稳定,反之为不稳定。使用非线性最小二乘法对2018年至2020年尼日利亚累计报告病例进行模型拟合,以获得描述尼日利亚该病动态的最佳拟合。此外,还进行了灵敏度分析,并采用五阶龙格-库塔法进行了系统的数值求解。采用不同的数值为每个参数,我们研究了所有最高灵敏度指数的参数对受感染的人类和受感染的啮齿动物种群的影响。我们的研究结果表明,任何减少啮齿动物种群数量和减少啮齿动物向人类和啮齿动物传播风险的控制策略和方法都将有助于拉沙热的种群控制。
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来源期刊
自引率
0.00%
发文量
18
审稿时长
9 weeks
期刊最新文献
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