全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

Mathematical Analysis of the Role of Information on the Dynamics of Typhoid Fever

DOI: 10.4236/oalib.1110109, PP. 1-20

Subject Areas: Dynamical System

Keywords: Typhoid Fever, Mathematical Modelling, Information Intervention, Optimal Control, Basic Reproduction Number, Numerical Simulation

Full-Text   Cite this paper   Add to My Lib

Abstract

This study presents a deterministic model to examine how information affects the spread of Typhoid Fever. The model’s properties, including its stability and basic reproduction number, are analyzed. Simulations show that information can influence behavior in ways that may increase disease transmission. Notably, the rise in Typhoid cases is linked to poor adherence to health precautions. The findings highlight the critical role of public education in controlling the disease and emphasize the need to include information campaigns in prevention strategies.

Cite this paper

Masasila, N. H. , Ngeleja, R. C. and Kigodi, O. J. (2025). Mathematical Analysis of the Role of Information on the Dynamics of Typhoid Fever. Open Access Library Journal, 12, e109. doi: http://dx.doi.org/10.4236/oalib.1110109.

References

[1]  Shaikh, A.S. and Sooppy Nisar, K. (2019) Transmission Dynamics of Fractional Order Typhoid Fever Model Using Caputo-Fabrizio Operator. Chaos, Solitons & Fractals, 128, 355-365. https://doi.org/10.1016/j.chaos.2019.08.012
[2]  Stanaway, J.D., Reiner, R.C. and Blacker, B.F. (2019) The Global Burden of Typhoid and Paratyphoid Fe-vers: A Systematic Analysis for the Global Burden of Disease Study 2017. The Lancet Infectious Diseases, 19, 369-381. http://www.sciencedirect.com/science/article/pii/S1473309918306856
[3]  Mutua, J.M., Wang, F. and Vaidya, N.K. (2015) Modeling Malaria and Typhoid Fever Co-Infection Dynamics. Mathematical Biosciences, 264, 128-144. https://doi.org/10.1016/j.mbs.2015.03.014
[4]  Uwakwe, J.I., Emerenini, B.O. and Inyama, S.C. (2020) Mathematical Model, Optimal Control and Trans-mission Dynamics of Avian Spirochaetosis. Journal of Applied Mathematics and Physics,08, 270-293. https://doi.org/10.4236/jamp.2020.82022
[5]  Katende, R. (2020) Mathe-matical Modelling of Growth Dynamics of Infant Financial Markets. Journal of Mathematical Finance, 10, 388-398. https://doi.org/10.4236/jmf.2020.103023
[6]  Peter, O., Ibrahim, M., Ogun-tolu, F., Akinduko, O. and Akinyemi, S. (2018) Direct and Indirect Transmission Dynamics of Typhoid Fever Model by Differential Trans-form Method. ATBU, Journal of Science, Technology and Education (JOSTE), 6, 167-177.
[7]  Butler, T. (2011) Treatment of Typhoid Fever in the 21st Cen-tury: Promises and Shortcomings. Clinical Microbiology and Infection, 17, 959-963. https://doi.org/10.1111/j.1469-0691.2011.03552.x
[8]  Musa, S.S., Zhao, S., Hussaini, N., Usaini, S. and He, D. (2021) Dynamics Analysis of Typhoid Fever with Public Health Education Programs and Final Epidemic Size Relation. Results in Applied Mathematics, 10, Article ID: 100153. https://doi.org/10.1016/j.rinam.2021.100153
[9]  Edward, S. (2017) A De-terministic Mathematical Model for Direct and Indirect Transmission Dynamics of Typhoid Fever. OALib, 4, 1-16. https://doi.org/10.4236/oalib.1103493
[10]  van den Driessche, P. and Wat-mough, J. (2002) Reproduction Numbers and Sub-Threshold Endemic Equilib-ria for Compartmental Models of Disease Transmission. Mathematical Biosci-ences, 180, 29-48. https://doi.org/10.1016/s0025-5564(02)00108-6
[11]  Kigodi, O.J., Man-jenga, M.S., Katundu, N.C., Chacha, C.S., Mwasunda, J.A. and Nyerere, N. (2024) Modeling the Impact of Vaccination on Newcastle Disease Dynamics in Caged Chickens. Journal of Mathematical Analysis and Modeling, 5, 81-97. https://doi.org/10.48185/jmam.v5i2.1127
[12]  Allen, L.J., Brauer, F., Van den Driessche, P. and Wu, J. (2008) Mathematical Epidemiology. Spring-er.
[13]  Diekmann, O., Heesterbeek, J.A.P. and Metz, J.A.J. (1990) On the Defi-nition and the Computation of the Basic Reproduction Ratio R 0 in Models for Infectious Diseases in Heterogeneous Populations. Journal of Mathematical Bi-ology, 28, 365-382. https://doi.org/10.1007/bf00178324
[14]  Martcheva, M. (2015) Introduction to Mathematical Epidemiology. Vol. 61. Spring-er.
[15]  Castillo-Chavez, C., Blower, S., Driessche, P., Kirschner, D. and Yakubu, A.A. (2002) Mathematical Approaches for Emerging and Reemerging Infectious Diseases: Models, Methods, and Theory. Springer.
[16]  Tumwiine, J., Mugisha, J.Y.T. and Luboobi, L.S. (2007) A Mathematical Model for the Dynamics of Ma-laria in a Human Host and Mosquito Vector with Temporary Immunity. Applied Mathematics and Computation, 189, 1953-1965. https://doi.org/10.1016/j.amc.2006.12.084
[17]  Massawe, L.N., Massawe, E.S. and Makinde, O.D. (2015) Temporal Model for Dengue Disease with Treatment. Advances in Infectious Diseases, 5, 21-36. https://doi.org/10.4236/aid.2015.51003
[18]  Korobeinikov, A. (2004) Lya-punov Functions and Global Properties for SEIR and SEIS Epidemic Models. Mathematical Medicine and Biology, 21, 75-83. https://doi.org/10.1093/imammb/21.2.75
[19]  Korobeinikov, A. (2007) Global Properties of Infectious Disease Models with Nonlinear Incidence. Bulle-tin of Mathematical Biology, 69, 1871-1886. https://doi.org/10.1007/s11538-007-9196-y
[20]  Korobeinikov, A. and Wake, G.C. (2002) Lyapunov Functions and Global Stability for SIR, SIRS, and SIS Epidemiological Models. Applied Mathematics Letters, 15, 955-960. https://doi.org/10.1016/s0893-9659(02)00069-1
[21]  McCluskey, C. (2006) Lyapunov Functions for Tuberculosis Models with Fast and Slow Progression. Mathematical Biosciences and Engineering: MBE, 3, 603-614.
[22]  La Salle, J.P. (1976) The Stability of Dynamical Systems. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611970432

Full-Text


Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133