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A generalized multi-population model for Ebola virus transmission incorporating environmental reservoir dynamics

Muhammad Farhan HakeemSchool of Computer Science and Technology, North University of China, Taiyuan 030051, ChinaShajar AbbasDepartment of Computer Engineering, Biruni University, Istanbul 34010, TurkeyImran SiddiqueCenter for Theoretical Physics, Khazar University, Baku, AZ1096, AzerbaijanIlyas KhanDepartment of Mathematics, College of Science Al-Zulfi, Majmaah University, Al-Majmaah 11952, Saudi ArabiaMohsen BakouriDepartment of Medical Equipment Technology, College of Applied Medical Science, Majmaah University, Al-Majmaah 11952, Saudi ArabiaRashid JanDepartment of Mathematics, College of Science, Qassim University, Buraydah 51452, Saudi ArabiaRakhmonjon AkhmadjonovNational University of UzbekistanRasul TuraevDepartment of Exact and Natural Sciences, Termez State University of Engineering and Agrotechnologies, Termez 190100, Uzbekistan
2026en
ABI

Annotatsiya

Background: Ebola virus disease (EVD) remains a serious public health hazard due to high mortality, multiple modes of transmission, and persistence in the environment. The existing Ebola transmission models have been constrained to a single or two-population framework, which are insufficient to capture multiple-population interaction transmission structures. Methods: This study proposes a multi-population autonomous Ebola transmission model with Susceptible, Exposed, Infectious, Hospitalized, Recovered, and Deceased infected corpse compartments and a shared viral reservoir in the environment. This model proposes that transmission is direct, hospital-acquired, corpse-mediated, and indirect environmental, and these modes are documented by a bilinear incidence formulation. Results: Positivity and boundedness properties of solutions were established via a mathematical analysis, and the basic reproduction number was derived using the next-generation matrix approach. The analytical findings show that whereas supercritical transmission results in persistent behaviour and the occurrence of endemic equilibria under the suggested parameters, the disease-free equilibrium is stable under the subcritical transmission condition. Conclusions: The numerical simulations support the applicability of the suggested multi-population paradigm for comprehending threshold-dependent Ebola transmission behaviour and show its qualitative dynamics under various transmission conditions.

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