Volume 13 • Issue 2 • PP: 06–09 • 2026
Using Mathematical Modeling to Predict the Spread of Epidemics
Open Access & Copyright
© 2026 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
View PDF Abstract
In this paper, we give a brief overview of the advances in mathematical modelling applied to epidemiology and the achievements that have been made in epidemiological research using mathematical models. Since the early 1900s when the well-known susceptible–infected–recovered model was proposed, mathematical treatments have played an important role in epidemiology. We introduce the deterministic SIR model and explain the value of computational tools, mathematical modelling and statistical analysis for the understanding of the development of disease and the size of emerging outbreaks. These are issues that are of major concern in everyday life and public health. With the emergence of the novel coronavirus in recent times, it has become evident that mathematical modeling along with computational and statistical tools are extremely relevant. Hence, this study explains the mathematical modelling in Epidemiology and demonstrates the advancement of the discipline over the years.
Keywords
References
[1] Gradually, “Mathematical modeling of epidemics: Advances and applications in disease prediction,” 2025, additional publication details were not provided in the source manuscript.
[2] A. S. Mata and S. M. P. Dourado, “Mathematical modeling applied to epidemics: An overview,” São Paulo Journal of Mathematical Sciences, vol. 15, no. 2, pp. 1025–1044, 2021.
[3] F. Brauer, C. Castillo-Chavez, and Z. Feng, Mathematical Models in Epidemiology, ser. Texts in Applied Mathematics. New York, NY, USA: Springer, 2019, vol. 69.
[4] V. Gadipally, T. Sri Lakshmi, B. Umadevi, S. Someshwar, C. Soma Shekar, and S. Kumar, “Mathematical modeling of epidemics: A study on the spread of infectious diseases,” Panamerican Mathematical Journal, vol. 35, no. 1, pp. 105–118, 2025.
[5] E. Vynnycky and R. G. White, An Introduction to Infectious Disease Modelling. Oxford, UK: Oxford University Press, 2010.
[6] X. Liu and P. Stechlinski, Infectious Disease Modeling: A Hybrid System Approach, ser. Nonlinear Systems and Complexity. Cham, Switzerland: Springer, 2017, vol. 19.
[7] M. J. Keeling and P. Rohani, Modeling Infectious Diseases in Humans and Animals. Princeton, NJ, USA: Princeton University Press, 2008.
[8] O. Diekmann, H. Heesterbeek, and T. Britton, Mathematical Tools for Understanding Infectious Disease Dynamics. Princeton, NJ, USA: Princeton University Press, 2013.
[9] World Health Organization, “Epidemic and pandemic preparedness guidelines,” World Health Organization, Geneva, Switzerland, 2024, additional publication details were not provided in the source manuscript.
Cite This Article
Choose your preferred format
Publisher's Note
The statements, opinions, and data presented in this article are solely those of the author(s) and do not necessarily represent those of ASPG, the journal, or its editors. ASPG and the editors disclaim responsibility for any harm arising from the use of any ideas, methods, instructions, or products described in this article, to the fullest extent permitted by applicable law.