2606004417
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A Mathematical Model Analysis on Anthrax Disease Considering Environmental Spore Concentration

  • Iyasu Kaleb

Received: 19 May 2026 | Revised: 27 May 2026 | Accepted: 25 Jun 2026 | Published: 27 Jul 2026

Abstract

This study presents a mathematical model of an anthrax disease, which focuses on the role of the concentration of spores in the environment. The main objective is to analyse the dynamics of the disease and to assess the stability of its equilibrium points—in particular, those of the endemic and anthrax-free states. The relevance of this research is its potential to inform public health strategies for the management of anthrax attacks. This study used the Castillo–Chavez and LaSalle invariant principles to establish the boundedness, positivity, and existence of the solutions to the system. In addition, the basic reproduction number was calculated (R0) using the next-generation matrix approach and performed sensitivity analyses to assess the effect of parameters such as host-to-host transmission coefficient (β1), environmental transmission coefficient (β2), and spore production rate (p) on the R0 parameter. To confirm my analytical findings, numerical simulations have been performed to confirm that a decrease in these parameters leads to a decrease in reproductive rate. The simulation shows that if R0 < 1 is stable both locally and globally, the anthrax disease-free equilibrium is stable, indicating the presence of effective control measures. On the other hand, the endemic equilibrium is stabilised at R0 > 1, which highlights the need for immediate intervention.

References 

  • 1.

    Raza, A.; Baleanu, D.; Yousaf, M.; et al. Modeling of anthrax disease via efficient computing techniques. Intell. Autom. Soft Comput. 2022, 32, 1109–1124.

  • 2.

    Rudolph, F.J.; Luong, T.M.; Do, T. M.; et al. Modeling the Impact of Anthrax Vaccination on Buffalo Outbreak Dynamics in Northern Vietnam. One Health 2025, 22, 101294.

  • 3.

    Lewerin, S.S.; Elvander, M.; Westermark, T.; et al. Anthrax outbreak in a Swedish beef cattle herd-1st case in 27 years: Case report. Acta. Vet. Scand. 2010, 52, 7. https://doi.org/10.1186/1751-0147-52-7.

  • 4.

    Kashyap, A.J.; Bordoloi, A.J.; Mohan, F.; et al. Dynamical analysis of an anthrax disease model in animals with nonlinear transmission rate. Math. Model. Control 2023, 3, 370–386.

  • 5.

    Sitali, D.C.; Mumba, C.; Skjerve, E.; et al. Awareness and attitudes towards anthrax and meat consumption practices among affected communities in Zambia: A mixed methods approach. PLoS Negl. Trop. Dis. 2017, 11, e0005580.

  • 6.

    Mwakapeje, E.R.; Høgset, S.; Fyumagwa, R.; et al. Anthrax outbreaks in the humans-livestock and wildlife interface areas of Northern Tanzania: A retrospective record review 2006–2016. BMC Public Health 2018, 18, 106.

  • 7.

    Croicu, A.M. An optimal control model to reduce and eradicate anthrax disease in herbivorous animals. Bull. Math. Biol. 2019, 81, 235–255.

  • 8.

    Alam, M.E.; Kamal, M.M.; Rahman, M.; et al. Review of anthrax: A disease of farm animals. J. Adv. Vet. Anim. Res. 2022, 9, 323.

  • 9.

    Githire, G.T.O.; Kimathi, G.; Wainaina, M. Analysis of transmission dynamics of anthrax in animals: a modeling approach. J. Sci. Res. Rep. 2019, 23, 1–9.

  • 10.

    Osman, S.; Makinde, O.D. A mathematical model for coinfection of listeriosis and anthrax diseases. Int. J. Math. Math. Sci. 2018, 2018, 1725671.

  • 11.

    Borucki, M.K.; Reynolds, J.; Gay, C.C.; et al. Dairy farm reservoir of Listeria monocytogenes sporadic and epidemic strains. J. Food Prot. 2004, 67, 2496–2499.

  • 12.

    Hu, R.; Aziz, M.H.N.; Mohamed, N.A.; et al. Modeling and analysis of dynamical behavior in a fractional-order COVID-19 epidemic model with media coverage. Alex. Eng. J. 2025, 127, 1081–1095.

  • 13.

    Gurmu, E.D.; Bole, B.K.; Koya, P.R. Mathematical modelling of HIV/AIDS transmission dynamics with optimal control strategy. Int. J. Math. Comput. Res. 2021, 9, 2237–2254.

  • 14.

    Kaleb, I.; Endiriyas, E. A mathematical model analysis on the dynamics of online game addiction with optimal control. Int. J. Dyn. Control 2025, 13, 406.

  • 15.

    Endashaw, E.E.; Gebru, D.M.; Alemneh, H.T. Coinfection Dynamics of HBV-HIV/AIDS with Mother-to-Child Transmission and Medical Interventions. Comput. Math. Methods Med. 2022, 2022, 4563577.

  • 16.

    Endashaw, E.E.; Mekonnen, T.T. Modeling the effect of vaccination and treatment on the transmission dynamics of hepatitis B virus and HIV/AIDS coinfection. J. Appl. Math. 2022, 2022, 5246762.

  • 17.

    Fantaye, A.K.; Birhanu, Z.K. Chewing Khat Transmission Dynamics: A Mathematical Model and Stability Analysis. J. Appl. Math. 2022, 2022, 3844885.

  • 18.

    Saman, A.; Side, S.; Pratama, M.I.; et al. Optimal control of the SEIR model of online game addiction using guidance and counseling. Eng. Lett. 2022, 30, 27–31.

  • 19.

    Balatif, O.; Khajji, B.; Rachik, M. Mathematical modeling, analysis, and optimal control of abstinence behavior of registration on the electoral lists. Discrete Dyn. Nat. Soc. 2020, 2020, 9738934.

  • 20.

    Martcheva, M. An Introduction to Mathematical Epidemiology; Springer: New York, NY, USA, 2015; Vol. 61, pp. 9–31.

  • 21.

    Saad-Roy, C.M.; Van den Driessche, P.; Yakubu, A.A. A mathematical model of anthrax transmission in animal populations. Bull. Math. Biol. 2017, 79, 303–324.

  • 22.

    Zhao, B.; Lyu, S.; Zhang, Q. Dynamics and density function for a stochastic anthrax epidemic model. Electron. Res. Arch. 2024, 32, 1574–1617.

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How to Cite
Kaleb, I. A Mathematical Model Analysis on Anthrax Disease Considering Environmental Spore Concentration. Complex Systems Stability & Control 2026, 2 (3), 8. https://doi.org/10.53941/cssc.2026.100019.
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