https://doi.org/10.1140/epjp/s13360-025-06902-z
Regular Article
A nonlinear optimization framework for a Lassa fever model capturing zoogenic transmission and disability risks
1
Department of Mathematics, Shanghai University, 99 Shangda Road, 200444, Shanghai, China
2
Institute of Mathematics, University of the Punjab, 54590, Lahore, Pakistan
3
Mechanical Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, P. O. Box 5555, 21955, Makkah, Saudi Arabia
4
Center for Theoretical Physics, Khazar University, 41 Mehseti Str., 1096, Baku, Azerbaijan
5
Department of Clinical Microbiology and Immunology Faculty of Medicine, King Abdulaziz University and Hospital, 21589, Jeddah, Saudi Arabia
6
King Salman Center for Disability Research, 11614, Riyadh, Saudi Arabia
7
Department of Mathematics, Umm Al-Qura University, 24382, Makkah, Saudi Arabia
a
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Received:
17
August
2025
Accepted:
23
September
2025
Published online:
13
October
2025
Abstract
This study aims to formulate, develop and analyze a mathematical model that captures the transmission dynamics of Lassa fever. The model incorporates a nonlinear saturated incidence rate to represent gender-specific transmission between humans, as well as transmission through contact with rodents. The mathematical analysis of the model involves establishing the positivity, existence and uniqueness of solutions, followed by a stability analysis. The 53-week dataset provided by the Nigerian Centre for Disease Control is divided into male and female cases based on the population gender ratio and then calibrated with a model to estimate parameter values. A sensitivity analysis is subsequently conducted, underscoring the importance of holistic control measures that integrate medical treatment with rodent population control and enhanced environmental hygiene. The Pontryagin principle of control theory, with the integration of real-life data and gender-specific data, is utilized to visualize the weekly percentage efficacy of each proposed control measure that contributes to its novelty, providing valuable insights for public health planning focused on disease management and reducing the risk of disability.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
