Please use this identifier to cite or link to this item:
Title: Evaluating COVID-19 in Portugal: Bootstrap confidence interval
Author: Tedim, Sofia
Afreixo, Vera
Felgueiras, Miguel
Leitão, Rui Pedro
Pinheiro, Sofia J.
Silva, Cristiana J.
Keywords: COVID-19
Bootstrap confidence interval
SAIRP model
Centre of Portugal region
Issue Date: Dec-2023
Publisher: AIMS Press
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.
Peer review: yes
DOI: 10.3934/math.2024136
ISSN: 2473-6988
Appears in Collections:CIDMA - Artigos
PSG - Artigos

Files in This Item:
File Description SizeFormat 
10.3934_math.2024136.pdf378.91 kBAdobe PDFView/Open

Formato BibTex MendeleyEndnote Degois 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.