Modeling the dynamics of Lassa fever in Nigeria | ||||
Journal of the Egyptian Mathematical Society | ||||
Volume 29, Issue 1, 2021, Page 1-19 PDF (2.49 MB) | ||||
Document Type: Original Article | ||||
DOI: 10.1186/s42787-021-00124-9 | ||||
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Authors | ||||
Mayowa M. Ojo* 1; B. Gbadamosi2; Temitope O. Benson3; O. Adebimpe4; A. L. Georgina5 | ||||
1Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, USA. | ||||
2Department of Computer Sciences, Landmark University, Omu-Aran, Kwara State, Nigeria. | ||||
3Institute for Computational and Data Sciences, University at Bufalo, State University of New York, Albany, USA. | ||||
4Department of Physical Sciences, Landmark University, Omu-Aran, Kwara State, Nigeria. | ||||
5Department of Microbiology, Landmark University, Omu-Aran, Kwara State, Nigeria. | ||||
Abstract | ||||
Lassa fever is a zoonotic disease spread by infected rodents known as multimammate rats. The disease has posed a signifcant 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 R0. The results show that if R0 < 1 then the system is stable, otherwise it is unstable. The model ftting was performed using the nonlinear least square method on cumulative reported cases from Nigeria between 2018 and 2020 to obtain the best ft 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 ffth-order Runge–Kutta method. Using diferent numeric values for each parameter, we investigate the efect of all highest sensitivity indices’ parameters on the population of infected humans and infected rodents. Our fndings 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. | ||||
Keywords | ||||
Lassa fever; Reproduction number; Stability; Model ftting; Sensitivity analysis; Numerical simulation | ||||
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