Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead

Detalhes bibliográficos
Autor(a) principal: Carvalho, Kathleen Carolina
Data de Publicação: 2021
Outros Autores: Vicente, João Paulo, Jakovljevic, Mihajlo, Teixeira, João Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10198/24604
Resumo: The use of artificial neural networks (ANNs) is a great contribution to medical studies since the application of forecasting concepts allows for the analysis of future diseases propagation. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures and massive vaccination campaigns. There were two proposed methodologies in making predictions 28 days ahead for the number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy, the United Kingdom, and Germany. A case study of the results of massive immunization in Israel was also considered. The data input of cases, deaths, and daily ICU patients was normalized to reduce discrepant numbers due to the countries’ size and the cumulative vaccination values by the percentage of population immunized (with at least one dose of the vaccine). As a comparative criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best methodology, targeting other possibilities of use for the method proposed. The best architecture achieved a general MAE for the 1-to-28-day ahead forecast, which is lower than 30 cases, 0.6 deaths, and 2.5 ICU patients per million people.
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spelling Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks aheadTime series predictionANN forecastingNew coronavirusCOVID-19 prediction casesCOVID-19 prediction ICUCOVID-19 vaccinationCOVID-19 in EuropeCOVID-19 in IsraelCOVID-19 wearing of face maskThe use of artificial neural networks (ANNs) is a great contribution to medical studies since the application of forecasting concepts allows for the analysis of future diseases propagation. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures and massive vaccination campaigns. There were two proposed methodologies in making predictions 28 days ahead for the number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy, the United Kingdom, and Germany. A case study of the results of massive immunization in Israel was also considered. The data input of cases, deaths, and daily ICU patients was normalized to reduce discrepant numbers due to the countries’ size and the cumulative vaccination values by the percentage of population immunized (with at least one dose of the vaccine). As a comparative criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best methodology, targeting other possibilities of use for the method proposed. The best architecture achieved a general MAE for the 1-to-28-day ahead forecast, which is lower than 30 cases, 0.6 deaths, and 2.5 ICU patients per million people.This work has been supported by Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.Biblioteca Digital do IPBCarvalho, Kathleen CarolinaVicente, João PauloJakovljevic, MihajloTeixeira, João Paulo2022-01-12T16:53:45Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/24604engCarvalho, Kathleen; Vicente, João Paulo; Jakovljevic, Mihajlo; Teixeira, João Paulo (2021). Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead. Bioengineering. ISSN 2306-5354. 8:6, p. 1-192306-535410.3390/bioengineering8060084info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-21T10:55:32Zoai:bibliotecadigital.ipb.pt:10198/24604Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:15:36.130409Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
title Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
spellingShingle Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
Carvalho, Kathleen Carolina
Time series prediction
ANN forecasting
New coronavirus
COVID-19 prediction cases
COVID-19 prediction ICU
COVID-19 vaccination
COVID-19 in Europe
COVID-19 in Israel
COVID-19 wearing of face mask
title_short Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
title_full Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
title_fullStr Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
title_full_unstemmed Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
title_sort Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead
author Carvalho, Kathleen Carolina
author_facet Carvalho, Kathleen Carolina
Vicente, João Paulo
Jakovljevic, Mihajlo
Teixeira, João Paulo
author_role author
author2 Vicente, João Paulo
Jakovljevic, Mihajlo
Teixeira, João Paulo
author2_role author
author
author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Carvalho, Kathleen Carolina
Vicente, João Paulo
Jakovljevic, Mihajlo
Teixeira, João Paulo
dc.subject.por.fl_str_mv Time series prediction
ANN forecasting
New coronavirus
COVID-19 prediction cases
COVID-19 prediction ICU
COVID-19 vaccination
COVID-19 in Europe
COVID-19 in Israel
COVID-19 wearing of face mask
topic Time series prediction
ANN forecasting
New coronavirus
COVID-19 prediction cases
COVID-19 prediction ICU
COVID-19 vaccination
COVID-19 in Europe
COVID-19 in Israel
COVID-19 wearing of face mask
description The use of artificial neural networks (ANNs) is a great contribution to medical studies since the application of forecasting concepts allows for the analysis of future diseases propagation. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures and massive vaccination campaigns. There were two proposed methodologies in making predictions 28 days ahead for the number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy, the United Kingdom, and Germany. A case study of the results of massive immunization in Israel was also considered. The data input of cases, deaths, and daily ICU patients was normalized to reduce discrepant numbers due to the countries’ size and the cumulative vaccination values by the percentage of population immunized (with at least one dose of the vaccine). As a comparative criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best methodology, targeting other possibilities of use for the method proposed. The best architecture achieved a general MAE for the 1-to-28-day ahead forecast, which is lower than 30 cases, 0.6 deaths, and 2.5 ICU patients per million people.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01T00:00:00Z
2022-01-12T16:53:45Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/24604
url http://hdl.handle.net/10198/24604
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Carvalho, Kathleen; Vicente, João Paulo; Jakovljevic, Mihajlo; Teixeira, João Paulo (2021). Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead. Bioengineering. ISSN 2306-5354. 8:6, p. 1-19
2306-5354
10.3390/bioengineering8060084
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dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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