Título: Epidemic Modeling of COVID -19 in Ceará: Parameter Estimation in a Reduced SIR Model Using Computational Intelligence Metaheuristics
Autores: João Samuel Maciel de Sales, Ricardo Coelho & João Paulo do Vale Madeiro
Resumo: A comprehensive analysis of COVID-19 transmission dynamics in Cear á, Brazil, is presented using a reduced SIR epidemiological model calibrated with empirical data from March 2020 to March 2023. Several computational intelligence optimization algorithms were systematically applied and compared for parameter estimation. Results demonstrate that temporal segmentation, particularly with bimonthly intervals, significantly improves model accuracy, achieving the lowest mean squared errors. The temporal evolution of the basic reproduction number revealed substantial variability, reflecting periods of uncontrolled transmission as well as the impact of public health interventions. These findings reinforce the value of computational intelligence for robust and accurate epidemiological modeling, offering insights to support effective public health strategies during epidemic scenarios.
Palavras-chave: COVID-19; SIR model; parameter estimation; computational intelligence.
Páginas: 8
Código DOI: 10.21528/CBIC2025-1175416
Artigo em PDF: CBIC_2025_paper1175416.pdf
Arquivo BibTeX:
CBIC_2025_1175416.bib