Mathematical Modeling of Typhoid Fever Transmission Dynamics: A Sensitivity Analysis and Implications for Public Health Strategies
Main Article Content
Abstract
Typhoid fever remains an important public health concern, requiring robust analytical approaches to understand its transmission dynamics and support effective prevention and control strategies. This study develops a comprehensive mathematical model of typhoid fever transmission to examine the interactions among factors influencing disease spread and to provide evidence for improved control and eradication strategies. The model incorporates population replenishment through births and was validated using existing data to assess its ability to represent disease dynamics. Mathematical analysis was conducted to determine equilibrium states and the basic reproduction number, (R0), while sensitivity analysis was performed to identify parameters with substantial influence on typhoid transmission. Numerical solutions were obtained using the fourth-order Runge–Kutta method over a 40-year simulation period and implemented in MATLAB. The findings show that (R0) is a critical threshold governing the dynamics of typhoid fever. When (R0<1), the disease-free equilibrium is locally stable, indicating that disease transmission will eventually decline; conversely, when (R0>1), an endemic equilibrium exists, indicating the persistence of the disease within the population. Sensitivity analysis further demonstrates the relative influence of model parameters on disease transmission, providing insights into factors that may be prioritized in control interventions. These findings demonstrate the utility of mathematical modeling for understanding typhoid fever transmission and evaluating disease-control strategies. The study contributes a quantitative framework that can support policymakers and healthcare professionals in designing evidence-based interventions aimed at reducing typhoid transmission, strengthening prevention efforts, and improving public health outcomes.

Citation Metrics:
Downloads
Citation Metrics & Similar Scopus Articles
-
Toshov J.B. (2027)Mathematical Model of the Dynamics of the Armament of the Tricone Drill BitKompleksnoe Ispolzovanie Mineralnogo Syra, 342(3), 27-34
-
Mirzahosseini M. (2027)A Review of Constitutive Modeling of Unsaturated SoilsIranian Journal of Geophysics, 20(3), 81-128
-
Toshov J.B. (2027)Comparative Analysis of Mathematical Models of Drilling in Heterogeneous Geological SectionsKompleksnoe Ispolzovanie Mineralnogo Syra, 341(2), 60-70
Article Details

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
References
Abegye, S. Y., Akinwande, N. I., & Akpan, C. F. (2024). The stability and bifurcation analysis of COVID-19 and tuberculosis co-infection dynamics. Proceedings of the International Conference on Mathematical Modelling, Optimization and Analysis of Disease Dynamics (ICMMOADD 2024), 1(1), 2–28.
Akinwande, N. I. (2024). Proceedings of ICMMOADD 2024: Contemporary issues on the controls of diseases epidemics and pandemic. Publications of Math Model Research Group, 1(1), 1–640. https://mathmodel.com.ng/ojs-3405/index.php/icmmoadd/article/view/1
Akpan, C. E., & Ibrahim, M. O. (2020). Sensitivity analysis for avian influenza (bird flu) epidemic model with exposed class. Asian Journal of Mathematics and Applications, 2020, Article ama0563. https://scienceasia.asia/files/563.pdf
Bhan, M. K., Bahl, R., & Bhatnagar, S. (2005). Typhoid and paratyphoid fever. The Lancet, 366(9487), 749–762. https://doi.org/10.1016/S0140-6736(05)67181-4
Bhutta, Z. A. (2002). Typhoid and paratyphoid. In D. Southall, B. Coulter, C. Ronald, S. Nicholson, & S. Parke (Eds.), International child health care: A practical manual for hospitals worldwide (pp. 426–429). BMJ Books.
Bokharaie, V. S. (2012). Stability analysis of positive systems with applications to epidemiology [Doctoral dissertation, National University of Ireland Maynooth]. https://mural.maynoothuniversity.ie/id/eprint/3733
Butler, T. (2011). Treatment of typhoid fever in the 21st century: Promises and shortcomings. Clinical Microbiology and Infection, 17(7), 959–963. https://doi.org/10.1111/j.1469-0691.2011.03552.x
Derrick, W. R., & Grossman, S. I. (1976). Elementary differential equations with applications. Addison-Wesley Publishing Company.
Ferreccio, C., Levine, M. M., Manterola, A., Rodriguez, G., Rivara, I., Prenzel, I., Black, R. E., Mancuso, T., & Bulas, D. (1984). Benign bacteremia caused by Salmonella typhi and paratyphi in children younger than 2 years. The Journal of Pediatrics, 104(6), 899–901. https://doi.org/10.1016/S0022-3476(84)80492-8
González-Guzmán, J. (1989). An epidemiological model for direct and indirect transmission of typhoid fever. Mathematical Biosciences, 96(1), 33–46. https://doi.org/10.1016/0025-5564(89)90081-3
Gotuzzo, E., Frisancho, O., Sanchez, J., Liendo, G., Carrillo, C., Black, R. E., & Morris, J. G. (1991). Association between the acquired immunodeficiency syndrome and infection with Salmonella typhi or Salmonella paratyphi in an endemic typhoid area. Archives of Internal Medicine, 151(2), 381–382. https://doi.org/10.1001/archinte.1991.00400020125026
Ivanoff, B., Cordel, J., Robert, D., & Fontanges, R. (1980). Importance de la voie respiratoire dans la salmonellose expérimentale de la souris Balb/c. Comptes Rendus de l’Académie des Sciences (Paris), 1271–1274.
Ivanoff, B., Levine, M. M., & Lambert, P. H. (1994). Vaccination against typhoid fever: Present status. Bulletin of the World Health Organization, 72(6), 957–971. https://pmc.ncbi.nlm.nih.gov/articles/PMC2486740/
Levine, M. M., Black, R. E., & Lanata, C. (1982). Precise estimation of the numbers of chronic carriers of Salmonella typhi in Santiago, Chile, an endemic area. The Journal of Infectious Diseases, 146(6), 724–726. https://doi.org/10.1093/infdis/146.6.724
Mogasale, V., Maskery, B., Ochiai, R. L., Lee, J. S., Mogasale, V. V., Ramani, E., Kim, Y. E., Park, J. K., & Wierzba, T. F. (2014). Burden of typhoid fever in low-income and middle-income countries: A systematic, literature-based update with risk-factor adjustment. The Lancet Global Health, 2(10), e570–e580. https://doi.org/10.1016/S2214-109X(14)70301-8
Nsutebu, E. F., Martins, P., & Adiogo, D. (2003). Short communication: Prevalence of typhoid fever in febrile patients with symptoms clinically compatible with typhoid fever in Cameroon. Tropical Medicine & International Health, 8(6), 575–578. https://doi.org/10.1046/j.1365-3156.2003.01012.x
Nthiiri, J. K., Lawi, G. O., Akinyi, C. O., Oganga, D. O., Muriuki, W. C., Musyoka, M. J., Otieno, P. O., & Koech, L. (2016). Mathematical modelling of typhoid fever disease incorporating protection against infection. Journal of Advances in Mathematics and Computer Science, 14(1), 1–10. https://doi.org/10.9734/BJMCS/2016/23325
Peter, O. J., Afolabi, O. A., Oguntolu, F. A., Ishola, C. Y., & Victor, A. A. (2018). Solution of a deterministic mathematical model of typhoid fever by variational iteration method. Science World Journal, 13(2), 64–68. https://scienceworldjournal.org/article/view/18489
Peter, O. J., Adebisi, A. F., Ajisope, M. O., Ajibade, F. O., Abioye, A. I., & Oguntolu, F. A. (2020). Global stability analysis of typhoid fever model. Advances in Systems Science and Applications, 20(2), 20–31. https://doi.org/10.25728/assa.2020.20.2.792
Peter, O. J., Ibrahim, M. O., Edogbanya, H. O., Oguntolu, F. A., Oshinubi, K., Ibrahim, A. A., Ayoola, T. A., & Lawal, J. O. (2021). Direct and indirect transmission of typhoid fever model with optimal control. Results in Physics, 27, Article 104463. https://doi.org/10.1016/j.rinp.2021.104463
Schemmer, A. K. (2012). Heterogeneity of inflammation and host metabolism in a typhoid fever model [Doctoral dissertation, University of Basel]. https://doi.org/10.5451/unibas-005958900
Somma, S. A., Akinwande, N. I., Jiya, M., & Abdulrahman, S. (2017). Stability analysis of disease free equilibrium (DFE) state of a mathematical model of yellow fever incorporating secondary host. The Pacific Journal of Science and Technology, 18(2), 110–119. https://www.akamai.university/uploads/1/2/7/7/127725089/pjst18_2_110.pdf
Wameko, M. S., Koya, P. R., & Wedajo, A. G. (2020). Mathematical model for transmission dynamics of typhoid fever with optimal control strategies. International Journal of Industrial Mathematics, 12(3), 283–296.


















