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Analysis of Covid-19 Dynamics in Brazil by Recursive State and Parameter Estimations

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Trends in Biomathematics: Modeling Epidemiological, Neuronal, and Social Dynamics (BIOMAT 2022)

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Abstract

In this article, the epidemiological dynamics of COVID-19 in Brazil were studied for each federative unit using state and parameter estimations based on public data. Transmissibility, the severity of the disease, and mortality dynamics were estimated over time for each case study through augmented states using a constrained extended Kalman filter (CEKF) and a Rauch-Tung-Striebel smoother. The estimated parameters were defined in a proposed SEIR-based model containing mobility data and heuristic assumptions. In addition, a heuristic data preprocessing was performed for each case study to remove data outliers from underreporting and overreporting. Simulations evaluated the COVID-19 epidemiological dynamics for each case study from 1 October 2020 to 1 October 2022. The dynamic feedback approach was efficient in detecting emerging predominant variants in most federative units. In addition, it satisfactorily characterized the predominant variants circulating dynamics under time-varying model uncertainty. Nonetheless, the technique was insufficient to describe the case studies with meaningful underreporting changes or poor data quality over time.

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Authors and Affiliations

  1. Federal University of Rio de Janeiro, Center of Technology, COPPE, Rio de Janeiro, Brazil

    Daniel Martins Silva & Argimiro Resende Secchi

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  1. Daniel Martins Silva
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  2. Argimiro Resende Secchi
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Correspondence to Argimiro Resende Secchi .

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  1. BIOMAT Consortium, International Institute for Interdisciplinary, Mathematical and Biological Sciences, Rio de Janeiro, Brazil

    Rubem P. Mondaini

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Silva, D.M., Secchi, A.R. (2023). Analysis of Covid-19 Dynamics in Brazil by Recursive State and Parameter Estimations. In: Mondaini, R.P. (eds) Trends in Biomathematics: Modeling Epidemiological, Neuronal, and Social Dynamics. BIOMAT 2022. Springer, Cham. https://doi.org/10.1007/978-3-031-33050-6_20

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