Document Type : Original Article
Authors
1
Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, USA.
2
Department of Computer Sciences, Landmark University, Omu-Aran, Kwara State, Nigeria.
3
Institute for Computational and Data Sciences, University at Bufalo, State University of New York, Albany, USA.
4
Department of Physical Sciences, Landmark University, Omu-Aran, Kwara State, Nigeria.
5
Department 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
)
View on SCiNiTO