Evaluating COVID-19 in Portugal: Bootstrap confidence interval

Sofia Tedim; Vera Afreixo; Miguel Felgueiras; Rui Pedro Leitão; Sofia J. Pinheiro; Cristiana J. Silva; Sofia Tedim; Vera Afreixo; Miguel Felgueiras; Rui Pedro Leitão; Sofia J. Pinheiro; Cristiana J. Silva

doi:10.3934/math.2024136

AIMS Mathematics

2024, Volume 9, Issue 2: 2756-2765. doi: 10.3934/math.2024136

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Research article

Evaluating COVID-19 in Portugal: Bootstrap confidence interval

1.
Center for Research and Development in Mathematics and Applications (CIDMA), Department of Mathematics, University of Aveiro, 3810-193 Aveiro, Portugal
2.
ESTG, Polytechnic Institute of Leiria and CEAUL, Faculdade de Ciências, Universidade de Lisboa, Portugal
3.
Public Health Unit, Baixo Vouga Primary Care Cluster, Administração Regional de Saúde (ARS) Centro, Av. Dr. Lourenço Peixinho, n 42, 4 andar, 3804-502 Aveiro, Portugal
4.
Iscte - Instituto Universitário de Lisboa, ISTA, Av. das Forças Armadas, 1649-026 Lisboa, Portugal

Received: 18 November 2023 Revised: 17 December 2023 Accepted: 22 December 2023 Published: 29 December 2023
MSC : 62F40, 62F25, 62P10

In this paper, we consider a compartmental model to fit the real data of confirmed active cases with COVID-19 in Portugal, from March 2, 2020 until September 10, 2021 in the Primary Care Cluster in Aveiro region, ACES BV, reported to the Public Health Unit. The model includes a deterministic component based on ordinary differential equations and a stochastic component based on bootstrap methods in regression. The main goal of this work is to take into account the variability underlying the data set and analyse the estimation accuracy of the model using a residual bootstrapped approach in order to compute confidence intervals for the prediction of COVID-19 confirmed active cases. All numerical simulations are performed in R environment ( version. 4.0.5). The proposed algorithm can be used, after a suitable adaptation, in other communicable diseases and outbreaks.
- COVID-19,
- bootstrap confidence interval,
- SAIRP model,
- centre of Portugal region
Citation: Sofia Tedim, Vera Afreixo, Miguel Felgueiras, Rui Pedro Leitão, Sofia J. Pinheiro, Cristiana J. Silva. Evaluating COVID-19 in Portugal: Bootstrap confidence interval[J]. AIMS Mathematics, 2024, 9(2): 2756-2765. doi: 10.3934/math.2024136

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Abstract

In this paper, we consider a compartmental model to fit the real data of confirmed active cases with COVID-19 in Portugal, from March 2, 2020 until September 10, 2021 in the Primary Care Cluster in Aveiro region, ACES BV, reported to the Public Health Unit. The model includes a deterministic component based on ordinary differential equations and a stochastic component based on bootstrap methods in regression. The main goal of this work is to take into account the variability underlying the data set and analyse the estimation accuracy of the model using a residual bootstrapped approach in order to compute confidence intervals for the prediction of COVID-19 confirmed active cases. All numerical simulations are performed in R environment ( version. 4.0.5). The proposed algorithm can be used, after a suitable adaptation, in other communicable diseases and outbreaks.

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