Mathematical models and simulations of different scenarios of COVID-19 in Brazil

• Lima, Marina ^[1] ; Silva, Anny ^[2] ; Meyer, João Frederico ^[1]
  1. [1] IMECC- UNICAMP, Department of Applied Mathematics, Campinas, Brazil
  2. [2] Federal Institute of Paraná, IFPR, Pinhais, Brazil
• Localización: Revista de Matemática: Teoría y Aplicaciones, ISSN 2215-3373, ISSN-e 2215-3373, Vol. 30, Nº. 1, 2023 (Ejemplar dedicado a: Revista de Matemática: Teoría y Aplicaciones), págs. 87-111
• Idioma: inglés
• DOI: 10.15517/rmta.v30i1.50566
• Títulos paralelos:
  • Modelos matemáticos y simulaciones de diferentes escenarios de COVID-19 en Brasil
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    En este artículo, desarrollamos modelos matemáticos sucesivos para describir la primera y la segunda ola de COVID-19 en Brasil, incluida la cepa original, las dos variantes de mayor circulación (variantes Gamma y Delta) y la vacunación de la población. Partimos de un modelo inicial simple y utilizando técnicas de modelado matemático y la función escalón de Heaviside, lo mejoramos según las necesidades de describir el comportamiento de la enfermedad, tanto considerando las nuevas variantes como la vacunación. En todos los casos, realizamos simulaciones informáticas y comparamos la curva obtenida con datos reales de los casos activos, lo que reforzó la eficiencia del modelo para describir el comportamiento de la pandemia y destacó la importancia de la vacunación de la población para describir la dinámica de los contagios y reducir los casos.

  • English

    In this paper, we develop successive mathematical models for describing the first and second waves of COVID-19 in Brazil, including the origi[1]nal strain, the two variants with the highest circulation (Gamma and Delta variants) and population vaccination. We started with a a simple initial model and using mathematical modelling techniques and the Heaviside step function, we improved it according to the necessities of describing the disease’s behaviour, both considering the new variants or vaccination. In all cases, we performed computer simulations and compared the obtained curve with real data from the active cases, which reinforced the model’s efficiency in describing the behaviour of the pandemic and highlighted the importance of population vaccination in describing the dynam[1]ics of the infections and reducing cases.

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