Dynamics of the Diphtheria Epidemic in Nigeria: Insights from the Kano State Outbreak Data

Sani Musa, Salisu Usaini (), Idris Ahmed, Chanakarn Kiataramkul () and Jessada Tariboon
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Sani Musa: Department of Mathematics, Faculty of Natural and Applied Sciences, Sule Lamido University Kafin Hausa, P.M.B 048, Kafin Hausa 741103, Nigeria
Salisu Usaini: Department of Mathematics, Faculty of Natural and Applied Sciences, Sule Lamido University Kafin Hausa, P.M.B 048, Kafin Hausa 741103, Nigeria
Idris Ahmed: Department of Mathematics, Faculty of Natural and Applied Sciences, Sule Lamido University Kafin Hausa, P.M.B 048, Kafin Hausa 741103, Nigeria
Chanakarn Kiataramkul: Intelligent and Nonlinear Dynamic Innovations Research Center, Department of Mathematics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand
Jessada Tariboon: Intelligent and Nonlinear Dynamic Innovations Research Center, Department of Mathematics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand

Mathematics, 2025, vol. 13, issue 7, 1-17

Abstract: Diphtheria is a severely infectious and deadly bacterial disease with Corynebacterium diphtheriae as the causative agent. Since the COVID-19 pandemic, contagious diseases such as diphtheria have re-emerged due to disruptions in routine childhood immunization programs worldwide. Nigeria is witnessing a significant increase in diphtheria outbreaks likely due to an inadequate health care system and insufficient public enlightenment campaign. This paper presents a mathematical epidemic diphtheria model in Nigeria, which includes a public enlightenment campaign to assess its positive impact on the prevalence of the disease. The mathematical analysis of the model reveals two equilibrium points: the diphtheria infection-free equilibrium and the endemic equilibrium. These equilibrium points are shown to be stable globally asymptotically if R c < 1 and R c > 1 , respectively. The model was fit using the confirmed diphtheria cases data of Kano State from January to December 2023. Sensitivity analysis indicates that the transmission rate and recovery rate of asymptomatic peopleare crucial parameters to be considered in developing effective strategies for diphtheria control and prevention. This analysis also reveals that the implementation of a high-level public enlightenment campaign and its high efficacy effectively reduce the prevalence of diphtheria. Finally, numerical simulations show that combining the public enlightenment campaign and isolating infected individuals is the best strategy to contain the spread of diphtheria.

Keywords: diphtheria; public enlightenment campaign; reproduction number; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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