Modeling the dynamics of Lassa fever in Nigeria

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 determini...

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Main Authors: Mayowa M. Ojo, B. Gbadamosi, Temitope O. Benson, O. Adebimpe, A. L. Georgina
Format: Article
Language:English
Published: SpringerOpen 2021-07-01
Series:Journal of the Egyptian Mathematical Society
Subjects:
Online Access:https://doi.org/10.1186/s42787-021-00124-9
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spelling doaj-6a8dcfa83b9b4bc79a3a38c063873e002021-07-11T11:30:44ZengSpringerOpenJournal of the Egyptian Mathematical Society2090-91282021-07-0129111910.1186/s42787-021-00124-9Modeling the dynamics of Lassa fever in NigeriaMayowa M. Ojo0B. Gbadamosi1Temitope O. Benson2O. Adebimpe3A. L. Georgina4Department of Ecology and Evolutionary Biology, University of KansasDepartment of Computer Sciences, Landmark UniversityInstitute for Computational and Data Sciences, University at Buffalo, State University of New YorkDepartment of Physical Sciences, Landmark UniversityDepartment of Microbiology, Landmark UniversityAbstract 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 $${\mathcal {R}}_{0}$$ R 0 . The results show that if $${\mathcal {R}}_{0} <1$$ 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.https://doi.org/10.1186/s42787-021-00124-9Lassa feverReproduction numberStabilityModel fittingSensitivity analysisNumerical simulation
collection DOAJ
language English
format Article
sources DOAJ
author Mayowa M. Ojo
B. Gbadamosi
Temitope O. Benson
O. Adebimpe
A. L. Georgina
spellingShingle Mayowa M. Ojo
B. Gbadamosi
Temitope O. Benson
O. Adebimpe
A. L. Georgina
Modeling the dynamics of Lassa fever in Nigeria
Journal of the Egyptian Mathematical Society
Lassa fever
Reproduction number
Stability
Model fitting
Sensitivity analysis
Numerical simulation
author_facet Mayowa M. Ojo
B. Gbadamosi
Temitope O. Benson
O. Adebimpe
A. L. Georgina
author_sort Mayowa M. Ojo
title Modeling the dynamics of Lassa fever in Nigeria
title_short Modeling the dynamics of Lassa fever in Nigeria
title_full Modeling the dynamics of Lassa fever in Nigeria
title_fullStr Modeling the dynamics of Lassa fever in Nigeria
title_full_unstemmed Modeling the dynamics of Lassa fever in Nigeria
title_sort modeling the dynamics of lassa fever in nigeria
publisher SpringerOpen
series Journal of the Egyptian Mathematical Society
issn 2090-9128
publishDate 2021-07-01
description 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 $${\mathcal {R}}_{0}$$ R 0 . The results show that if $${\mathcal {R}}_{0} <1$$ 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.
topic Lassa fever
Reproduction number
Stability
Model fitting
Sensitivity analysis
Numerical simulation
url https://doi.org/10.1186/s42787-021-00124-9
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