Mathematical Analysis of a Co-Dynamics Model of Listeriosis and Bacterial Meningitis Starting From Ready-to-Eat Foods

Article Sidebar

PDF
DOI: https://doi.org/10.28924/2291-8639-24-2026-160
Published: May 20, 2026
Cite as:
Ousmane Koutou, Cheick Abdoul Kabir Kouanda, Adama Ouédraogo, Mathematical Analysis of a Co-Dynamics Model of Listeriosis and Bacterial Meningitis Starting From Ready-to-Eat Foods, Int. J. Anal. Appl., 24 (2026), 160.

Main Article Content

Ousmane Koutou, Cheick Abdoul Kabir Kouanda, Adama Ouédraogo

Abstract

Listeriosis is a foodborne illness that can lead to bacterial meningitis. In this paper, we propose and investigate a model of co-infection involving both listeriosis and bacterial meningitis, originating from ready-to-eat food products. We begin by examining the patterns of each disease individually, as well as the dynamics of their co-infection. From our global co-infection model, we derive separate models for bacterial meningitis and listeriosis. Each model is analyzed in terms of the existence of equilibrium points, threshold dynamics parameters, stability results, sensitivity analysis, and the presence of backward and forward bifurcations. Finally, we present numerical simulation results to support our theoretical findings.

Article Details

References

  1. Meningitis Research Foundation, The History of Meningitis, Meningitis Research Foundation. https://www.meningitis.org/blogs/the-history-of-meningitis.
  2. A.B. Diabaté, B. Sangaré, O. Koutou, Optimal Control Analysis of a Mathematical Model of Malaria and COVID-19 Co-Infection Dynamics, J. Biol. Dyn. 19 (2025), 2568392. https://doi.org/10.1080/17513758.2025.2568392.
  3. A.B. Diabaté, B. Sangaré, O. Koutou, Optimal Control Analysis of a COVID-19 and Tuberculosis (TB) Co-Infection Model with an Imperfect Vaccine for COVID-19, SeMA J. 81 (2023), 429–456. https://doi.org/10.1007/s40324-023-00330-8.
  4. S. Barocci, A. Mancini, B. Canovari, E. Petrelli, E. Sbriscia-Fioretti, et al. Listeria Monocytogenes Meningitis in an Immunocompromised Patient, New Microbiol. 38 (2015), 113–118.
  5. B. Greenwood, Meningococcal Meningitis in Africa, Trans. R. Soc. Trop. Med. Hyg. 93 (1999), 341–353. https://doi.org/10.1016/s0035-9203(99)90106-2.
  6. B.S. kotola, T.T. Mekonnen, Mathematical Model Analysis and Numerical Simulation for Codynamics of Meningitis and Pneumonia Infection with Intervention, Sci. Rep. 12 (2022), 2639. https://doi.org/10.1038/s41598-022-06253-0.
  7. C. Castillo-Chavez, B. Song, Dynamical Models of Tuberculosis and Their Applications, Math. Biosci. Eng. 1 (2004), 361–404. https://doi.org/10.3934/mbe.2004.1.361.
  8. C. Castillo-Chavez, S. Blower, P. Van Den Driessche, D. Kirschner, A.A. Yakubu, eds., Mathematical Approaches for Emerging and Reemerging Infectious Diseases: Models, Methods, and Theory, Springer, New York, 2002. https://doi.org/10.1007/978-1-4613-0065-6.
  9. C. Ma, X. Li, Z. Zhao, F. Liu, K. Zhang, et al., Understanding Dynamics of Pandemic Models to Support Predictions of COVID-19 Transmission: Parameter Sensitivity Analysis of SIR-Type Models, IEEE J. Biomed. Health Inform. 26 (2022), 2458–2468. https://doi.org/10.1109/jbhi.2022.3168825.
  10. C.W. Chukwu, J. Mushanyu, M.L. Juga, Fatmawati, A Mathematical Model for Co-Dynamics of Listeriosis and Bacterial Meningitis Diseases, Commun. Math. Biol. Neurosci. 2020 (2020), 83. https://doi.org/10.28919/cmbn/5060.
  11. C.W. Chukwu, S.Y. Tchoumi, O. Koutou, F.F. Herdicho, Fatmawati, Exploring the Epidemiological Impact of Pneumonia–Listeriosis Co-Infection in the Human Population: A Modeling and Optimal Control Study, Int. J. Dyn. Control. 13 (2025), 197. https://doi.org/10.1007/s40435-025-01714-6.
  12. D.K. Das, T. Kar, Global Dynamics of a Tuberculosis Model with Sensitivity of the Smear Microscopy, Chaos Solitons Fractals 146 (2021), 110879. https://doi.org/10.1016/j.chaos.2021.110879.
  13. H. Hof, History and Epidemiology of Listeriosis, FEMS Immunol. Med. Microbiol. 35 (2003), 199–202. https://doi.org/10.1016/s0928-8244(02)00471-6.
  14. J. Njagarah, F. Nyabadza, A Metapopulation Model for Cholera Transmission Dynamics Between Communities Linked by Migration, Appl. Math. Comput. 241 (2014), 317–331. https://doi.org/10.1016/j.amc.2014.05.036.
  15. J.K.K. Asamoah, F. Nyabadza, Z. Jin, E. Bonyah, M.A. Khan, et al., Backward Bifurcation and Sensitivity Analysis for Bacterial Meningitis Transmission Dynamics with a Nonlinear Recovery Rate, Chaos Solitons Fractals 140 (2020), 110237. https://doi.org/10.1016/j.chaos.2020.110237.
  16. J. McLauchlin, R. Mitchell, W. Smerdon, K. Jewell, Listeria Monocytogenes and Listeriosis: A Review of Hazard Characterisation for Use in Microbiological Risk Assessment of Foods, Int. J. Food Microbiol. 92 (2004), 15–33. https://doi.org/10.1016/S0168-1605(03)00326-X.
  17. J.P. La Salle, The Stability of Dynamical Systems, SIAM, 1976. https://doi.org/10.1137/1.9781611970432.
  18. K.G. Mekonen, L.L. Obsu, Mathematical Modeling and Analysis for the Co-Infection of COVID-19 and Tuberculosis, Heliyon 8 (2022), e11195. https://doi.org/10.1016/j.heliyon.2022.e11195.
  19. K.O. Okosun, R. Smith, Optimal Control Analysis of Malaria-Schistosomiasis Co-Infection Dynamics, Math. Biosci. Eng. 14 (2017), 377–405. https//doi.org/10.3934/mbe.2017024.
  20. A.M. Oordt-Speets, R. Bolijn, R.C. van Hoorn, A. Bhavsar, M.H. Kyaw, Global Etiology of Bacterial Meningitis: A Systematic Review and Meta-Analysis, PLOS ONE 13 (2018), e0198772. https://doi.org/10.1371/journal.pone.0198772.
  21. M. Doganay, Listeriosis: Clinical Presentation, FEMS Immunol. Med. Microbiol. 35 (2003), 173–175. https://doi.org/10.1016/S0928-8244(02)00467-4.
  22. M.M. Koopmans, M.C. Brouwer, J.A. Vázquez-Boland, D. van de Beek, Human Listeriosis, Clin. Microbiol. Rev. 36 (2023), e00060–19. https://doi.org/10.1128/cmr.00060-19.
  23. N.G. Rouphael, D.S. Stephens, Neisseria Meningitidis: Biology, Microbiology, and Epidemiology, in: M. Christodoulides (eds), Neisseria Meningitidis, Methods in Molecular Biology, vol. 799, Humana, Totowa, NJ, 2012, pp. 1–20. https://doi.org/10.1007/978-1-61779-346-2_1.
  24. P. Laguna del Estal, G.M. Lledó Ibáñez, R. Ríos Garcés, I. Pintos Pascual, Meningitis Por Listeria Monocytogenes en Adultos, Rev. Neurol. 56 (2013), 13. https://doi.org/10.33588/rn.5601.2012446.
  25. P. van den Driessche, J. Watmough, Reproduction Numbers and Sub-Threshold Endemic Equilibria for Compartmental Models of Disease Transmission, Math. Biosci. 180 (2002), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6.
  26. R. Amaya-Villar, E. García-Cabrera, E. Sulleiro-Igual, P. Fernández-Viladrich, D. Fontanals-Aymerich, et al., Three-Year Multicenter Surveillance of Community-Acquired Listeria Monocytogenes Meningitis in Adults, BMC Infect. Dis. 10 (2010), 324. https://doi.org/10.1186/1471-2334-10-324.
  27. T.J. Irving, K.B. Blyuss, C. Colijn, C.L. Trotter, Modelling Meningococcal Meningitis in the African Meningitis Belt, Epidemiol. Infect. 140 (2011), 897–905. https://doi.org/10.1017/S0950268811001385.
  28. T. Khan, F.A. Rihan, H. Ahmad, Modelling the Dynamics of Acute and Chronic Hepatitis B with Optimal Control, Sci. Rep. 13 (2023), 14980. https://doi.org/10.1038/s41598-023-39582-9.