Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/31289
Author(s): | Tedim, S. Afreixo, V. Felgueiras, M. Leitão, R. P. Pinheiro, S. J. Silva, C. J. |
Date: | 2024 |
Title: | Evaluating COVID-19 in Portugal: Bootstrap confidence interval |
Journal title: | AIMS Mathematics |
Volume: | 9 |
Number: | 2 |
Pages: | 2756 - 2765 |
Reference: | Tedim, S., Afreixo, V., Felgueiras, M., Leitão, R. P., Pinheiro, S. J., & Silva, C. J. (2023). Evaluating COVID-19 in Portugal: Bootstrap confidence interval. AIMS Mathematics, 9(2). 2756-2765. https://dx.doi.org/10.3934/math.2024136 |
ISSN: | 2473-6988 |
DOI (Digital Object Identifier): | 10.3934/math.2024136 |
Keywords: | COVID-19 Bootstrap confidence interval SAIRP model Centre of Portugal region |
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. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | DM-RI - Artigos em revistas científicas internacionais com arbitragem científica |
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