Resumen
COVID-19 caused many mathematical models to be formulated in order to address questions about the evolution of COVID-19 disease, in an attempt to diminish the effects of the disease on social health and the economy. This chapter explores how these questions have been changing since the beginning of the pandemic as well as the models used to answer them. Special emphasis is given to the limitations of the mathematical modeling that appeared with this ongoing disease, and whenever possible, strategies will be proposed to address these limitations. Mexico will be used as a case study.
Idioma original | Inglés |
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Título de la publicación alojada | Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases |
Subtítulo de la publicación alojada | Lessons Learned From COVID-19 |
Editorial | Elsevier |
Capítulo | 3 |
Páginas | 43-72 |
Número de páginas | 30 |
ISBN (versión digital) | 9780323950640 |
ISBN (versión impresa) | 9780323950657 |
DOI | |
Estado | Publicada - 24 mar. 2023 |
Nota bibliográfica
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