IJMSC Vol. 11, No. 4, 8 Dec. 2025
Cover page and Table of Contents: PDF (size: 1010KB)
PDF (1010KB), PP.11-23
Views: 0 Downloads: 0
SIR Model, Diarrhea Disease, Epidemic, Reproduction Number, Bangladesh
Diarrhea is responsible for killing around 525,000 children every year, even though it is preventable and treatable. More than 130 nations are affected by the illness of diarrhea. Mathematical models provide a valuable tool for understanding the dynamics of infectious diseases like diarrhea and evaluating potential control strategies. To understand its transmission dynamics in Bangladesh, this study develops a Susceptible-Infectious-Recovered (SIR) mathematical model that incorporates both the human (host) and housefly (vector) populations. The model consists of five nonlinear ordinary differential equations (ODEs). We analyze the model to determine its equilibrium points and the basic reproduction number (R0 ). Using demographic and epidemiological parameters for Jashore and Khulna, Bangladesh, we calculate the basic reproduction number to be R0=1.35. This value, being greater than 1, indicates that the disease-free state is unstable and predicts a stable endemic equilibrium where diarrhea persists in the population. Numerical simulations for Khulna and Jashore illustrate this endemic dynamic, showing a decline in initial infections followed by long-term persistence. The findings confirm the model's utility in explaining the endemic nature of diarrhea in the region and highlight that interventions targeting vector (housefly) control are essential for effective public health strategies.
Nazrul Islam, Rayhan Prodhan, Md. Asaduzzaman, "A Host-Vector SIR Model for Diarrhea Transmission: Analyzing the Role of Houseflies in Bangladesh", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.11, No.4, pp. 11-23, 2025. DOI: 10.5815/ijmsc.2025.04.02
[1]Kandhway, K., & Kuri, J. (2014). How to run a campaign: Optimal control of SIS and SIR information epidemics. Applied Mathematics and Computation, 231, 79-92.
[2]Rodrigues, H. S. (2016). Application of SIR epidemiological model: new trends. arXiv preprint arXiv:1611.02565.
[3]Ehrhardt, M., Gašper, J., & Kilianová, S. (2019). SIR-based mathematical modeling of infectious diseases with vaccination and waning immunity. Journal of Computational Science, 37, 101027.
[4]Zaman, G., Kang, Y. H., & Jung, I. H. (2008). Stability analysis and optimal vaccination of an SIR epidemic model. BioSystems, 93(3), 240-249.
[5]Barro, M., Guiro, A., & Ouedraogo, D. (2018). Optimal control of a SIR epidemic model with general incidence function and a time delays. Cubo (Temuco), 20(2), 53-66.
[6]Chaturvedi, O., Jeffrey, M., Lungu, E., & Masupe, S. (2017). Epidemic model formulation and analysis for diarrheal infections caused by salmonella. Simulation, 93(7), 543-552.
[7]Rahmadani, F., & Lee, H. (2020). Dynamic model for the epidemiology of diarrhea and simulation considering multiple disease carriers. International Journal of Environmental Research and Public Health, 17(16), 5692.
[8]Affandi, P., & Salam, N. (2021, April). Optimal Control of diarrhea Disease model with Vaccination and Treatment. In Journal of Physics: Conference Series (Vol. 1807, No. 1, p. 012032). IOP Publishing.
[9]Gaff, H., & Schaefer, E. (2009). Optimal control applied to vaccination and treatment strategies for various epidemiological models. Mathematical biosciences & engineering, 6(3), 469-492.
[10]Berhe, H. W., Makinde, O. D., & Theuri, D. M. (2019). Modelling the dynamics of direct and pathogens-induced dysentery diarrhea epidemic with controls. Journal of biological dynamics, 13(1), 192-217.
[11]Yu, X., & Ma, Y. (2021). Complex Dynamics of a Dysentery Diarrhea Epidemic Model With Treatment and Sanitation Under Environmental Stochasticity: Persistence, Extinction and Ergodicity. IEEE Access, 9, 161129-161140.
[12]Zhou, Y., & Liu, H. (2003). Stability of periodic solutions for an SIS model with pulse vaccination. Mathematical and Computer Modelling, 38(3-4), 299-308.
[13]Ogwel, B., Mzazi, V., Nyawanda, B. O., Otieno, G., & Omore, R. (2024). Predictive modeling for infectious diarrheal disease in pediatric populations: A systematic review. Learning Health Systems, 8(1), e10382.
[14]Ji, W., Zou, S., Liu, J., Sun, Q., & Xia, L. (2020). Dynamic of non-autonomous vector infectious disease model with cross infection. American Journal of Computational Mathematics, 10(04), 591-602.
[15]Zhang, F., Li, Z. Z., & Zhang, F. (2008). Global stability of an SIR epidemic model with constant infectious period. Applied Mathematics and Computation, 199(1), 285-291.
[16]Mohajan, H. (2022). Mathematical analysis of SIR model for COVID-19 transmission.
[17]Bernardi, F., & Aminian, M. (2021). Epidemiology and the sir model: Historical context to modern applications. CODEE Journal, 14(1), 4.
[18]Sanchez, D. A. (1979). Ordinary differential equations and stability theory: an introduction. Courier Corporation.
[19]Acemoglu, D., Chernozhukov, V., Werning, I., & Whinston, M. D. (2020). A multi-risk SIR model with optimally targeted lockdown (Vol. 2020). Cambridge, MA: National Bureau of Economic Research.
[20]Heesterbeek, J. A. P., & Roberts, M. G. (2007). The type-reproduction number T in models for infectious disease control. Mathematical biosciences, 206(1), 3-10.
[21]Moghadas, S. M., & Gumel, A. B. (2002). Global stability of a two-stage epidemic model with generalized non-linear incidence. Mathematics and computers in simulation, 60(1-2), 107-118.
[22]Sharif, N., Nobel, N. U., Sakib, N., Liza, S. M., Khan, S. T., Billah, B., and Dey, S. K. (2020). Molecular and epidemiologic analysis of diarrheal pathogens in children with acute gastroenteritis in Bangladesh during 2014–2019. The Pediatric infectious disease journal, 39(7), 580-585.
[23]Hattaf, K., & Yousfi, N. (2012). Optimal control of a delayed HIV infection model with immune response using an efficient numerical method. International Scholarly Research Notices, 2012(1), 215124.
[24]Berhe, H. W., Makinde, O. D., & Theuri, D. M. (2019). Parameter estimation and sensitivity analysis of dysentery diarrhea epidemic model. Journal of Applied Mathematics, 2019(1), 8465747.
[25]Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the royal society of london. Series A, Containing papers of a mathematical and physical character, 115(772), 700-721.
[26]Chaturvedi, O., Lungu, E., Jeffrey, M., and Masupe, S. (2018). Rotavirus diarrhea–An analysis through epidemic modeling. Journal of Biomedical Engineering and Informatics, 4(2).
[27]Hidayati, N., Sari, E. R., and Waryanto, N. H. (2021). Mathematical model of Cholera spread based on SIR: Optimal control. Pythagoras J. Pendidik. Mat, 16(1).
[28]https://worldpopulationreview.com/cities/bangladesh/khulna
[29]https://www.cia.gov/the-world-factbook/field/life-expectancy-at-birth/country-comparison/
[30]https://www.orkin.com/pests/flies/house-flies/life-expectancy-of-house-flies
[31]Extreme heat wave causes patients surge in Khulna https://www.bssnews.net/district/185219
[32]https://www.uptodate.com/contents/acute-diarrhea-in-adults-beyond-the-basics/print