Epidemic modeling using differential equations with implementation in R

• Autores: Liang Kong
• Localización: International journal of mathematical education in science and technology, ISSN 0020-739X, Vol. 55, Nº. 2, 2024, págs. 480-491
• Idioma: inglés
• DOI: 10.1080/0020739X.2023.2249902
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• Resumen

  • The COVID-19 pandemic, like past historical events such as the Vietnam War or 9/11, will shape a generation. Mathematics educators can seize this unprecedented opportunity to teach the principles of mathematical modeling in epidemiology. Compartmental epidemiological models, such as the SIR (susceptible-infected-recovered), are widely used by researchers and educators to study and teach infectious disease dynamics, particularly for COVID-19. The SIR model is considered a fundamental mathematical model for the spread of epidemic disease and employs Ordinary Differential Equations to determine the number of individuals in each compartment of a population at a given time. In this note, we demonstrate how to build a basic SIR model. We show how to simulate, plot, and interpret the results using numerical simulation with R, a popular programming language widely used in data analysis and scientific research.