Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI

Bibliographic Details
Main Author: Paixão, Balthazar
Publication Date: 2021
Other Authors: Baroni, Lais, Pedroso, Marcel, Salles, Rebecca, Escobar, Luciana, Sousa, Carlos de, Saldanha, Raphael de Freitas, Soares, Jorge, Coutinho, Rafaelli, Porto, Fabio, Ogasawara, Eduardo
Format: Article
Language: eng
Source: Repositório Institucional da FIOCRUZ (ARCA)
Download full: https://www.arca.fiocruz.br/handle/icict/52627
Summary: BP, LB, FP were supported by CNPq. RS was supported by CAPES (finance code 001). MP was supported by FAPERJ. EO was supported by both CNPq and FAPERJ. The content is solely the responsibility of the authors. It does not necessarily represent the official views of the funding agencies. The funding agencies had no role in the study design, data collection, and analyses, decision to publish, or preparation of the manuscript.
id CRUZ_5fb1d18262af8d3b349bd9a169d32adf
oai_identifier_str oai:www.arca.fiocruz.br:icict/52627
network_acronym_str CRUZ
network_name_str Repositório Institucional da FIOCRUZ (ARCA)
repository_id_str 2135
spelling Paixão, BalthazarBaroni, LaisPedroso, MarcelSalles, RebeccaEscobar, LucianaSousa, Carlos deSaldanha, Raphael de FreitasSoares, JorgeCoutinho, RafaelliPorto, FabioOgasawara, Eduardo2022-05-11T22:40:56Z2022-05-11T22:40:56Z2021PAIXÃO, Balthazar et al. Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI. New Generation Computing, v. 39, n. (3-4), p. 623-645, 2021.0288-3635https://www.arca.fiocruz.br/handle/icict/5262710.1007/s00354-021-00125-3BP, LB, FP were supported by CNPq. RS was supported by CAPES (finance code 001). MP was supported by FAPERJ. EO was supported by both CNPq and FAPERJ. The content is solely the responsibility of the authors. It does not necessarily represent the official views of the funding agencies. The funding agencies had no role in the study design, data collection, and analyses, decision to publish, or preparation of the manuscript.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.National Laboratory of Scientific Computing. Rio de Janeiro, RJ, Brazil.Federal Center for Technological Education of Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Due to its impact, COVID-19 has been stressing the academy to search for curing, mitigating, or controlling it. It is believed that under-reporting is a relevant factor in determining the actual mortality rate and, if not considered, can cause significant misinformation. Therefore, this work aims to estimate the under-reporting of cases and deaths of COVID-19 in Brazilian states using data from the InfoGripe. InfoGripe targets notifications of Severe Acute Respiratory Infection (SARI). The methodology is based on the combination of data analytics (event detection methods) and time series modeling (inertia and novelty concepts) over hospitalized SARI cases. The estimate of real cases of the disease, called novelty, is calculated by comparing the difference in SARI cases in 2020 (after COVID-19) with the total expected cases in recent years (2016-2019). The expected cases are derived from a seasonal exponential moving average. The results show that under-reporting rates vary significantly between states and that there are no general patterns for states in the same region in Brazil. The states of Minas Gerais and Mato Grosso have the highest rates of under-reporting of cases. The rate of under-reporting of deaths is high in the Rio Grande do Sul and the Minas Gerais. This work can be highlighted for the combination of data analytics and time series modeling. Our calculation of under-reporting rates based on SARI is conservative and better characterized by deaths than for cases.engOhmsha, Ltd. and Springer Japan KK, part of Springer NatureEstimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARIinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleCOVID-19Data analyticsSARITime series modelingUnder-reportinginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-83134https://www.arca.fiocruz.br/bitstream/icict/52627/1/license.txt0ab46789d568c4ba27c7b5d29a9fe9c4MD51ORIGINALPaixão_Balthazar_etal_ICICT_COVID-19_2021.pdfPaixão_Balthazar_etal_ICICT_COVID-19_2021.pdfapplication/pdf2802127https://www.arca.fiocruz.br/bitstream/icict/52627/2/Paix%c3%a3o_Balthazar_etal_ICICT_COVID-19_2021.pdf872190ab6956301110e031ec56c17698MD52icict/526272022-05-11 19:41:48.958oai:www.arca.fiocruz.br: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Repositório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352022-05-11T22:41:48Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false
dc.title.pt_BR.fl_str_mv Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
title Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
spellingShingle Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
Paixão, Balthazar
COVID-19
Data analytics
SARI
Time series modeling
Under-reporting
title_short Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
title_full Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
title_fullStr Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
title_full_unstemmed Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
title_sort Estimation of COVID‑19 Under‑Reporting in the Brazilian States Through SARI
author Paixão, Balthazar
author_facet Paixão, Balthazar
Baroni, Lais
Pedroso, Marcel
Salles, Rebecca
Escobar, Luciana
Sousa, Carlos de
Saldanha, Raphael de Freitas
Soares, Jorge
Coutinho, Rafaelli
Porto, Fabio
Ogasawara, Eduardo
author_role author
author2 Baroni, Lais
Pedroso, Marcel
Salles, Rebecca
Escobar, Luciana
Sousa, Carlos de
Saldanha, Raphael de Freitas
Soares, Jorge
Coutinho, Rafaelli
Porto, Fabio
Ogasawara, Eduardo
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Paixão, Balthazar
Baroni, Lais
Pedroso, Marcel
Salles, Rebecca
Escobar, Luciana
Sousa, Carlos de
Saldanha, Raphael de Freitas
Soares, Jorge
Coutinho, Rafaelli
Porto, Fabio
Ogasawara, Eduardo
dc.subject.en.pt_BR.fl_str_mv COVID-19
Data analytics
SARI
Time series modeling
Under-reporting
topic COVID-19
Data analytics
SARI
Time series modeling
Under-reporting
description BP, LB, FP were supported by CNPq. RS was supported by CAPES (finance code 001). MP was supported by FAPERJ. EO was supported by both CNPq and FAPERJ. The content is solely the responsibility of the authors. It does not necessarily represent the official views of the funding agencies. The funding agencies had no role in the study design, data collection, and analyses, decision to publish, or preparation of the manuscript.
publishDate 2021
dc.date.issued.fl_str_mv 2021
dc.date.accessioned.fl_str_mv 2022-05-11T22:40:56Z
dc.date.available.fl_str_mv 2022-05-11T22:40:56Z
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.citation.fl_str_mv PAIXÃO, Balthazar et al. Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI. New Generation Computing, v. 39, n. (3-4), p. 623-645, 2021.
dc.identifier.uri.fl_str_mv https://www.arca.fiocruz.br/handle/icict/52627
dc.identifier.issn.pt_BR.fl_str_mv 0288-3635
dc.identifier.doi.none.fl_str_mv 10.1007/s00354-021-00125-3
identifier_str_mv PAIXÃO, Balthazar et al. Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI. New Generation Computing, v. 39, n. (3-4), p. 623-645, 2021.
0288-3635
10.1007/s00354-021-00125-3
url https://www.arca.fiocruz.br/handle/icict/52627
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Ohmsha, Ltd. and Springer Japan KK, part of Springer Nature
publisher.none.fl_str_mv Ohmsha, Ltd. and Springer Japan KK, part of Springer Nature
dc.source.none.fl_str_mv reponame:Repositório Institucional da FIOCRUZ (ARCA)
instname:Fundação Oswaldo Cruz (FIOCRUZ)
instacron:FIOCRUZ
instname_str Fundação Oswaldo Cruz (FIOCRUZ)
instacron_str FIOCRUZ
institution FIOCRUZ
reponame_str Repositório Institucional da FIOCRUZ (ARCA)
collection Repositório Institucional da FIOCRUZ (ARCA)
bitstream.url.fl_str_mv https://www.arca.fiocruz.br/bitstream/icict/52627/1/license.txt
https://www.arca.fiocruz.br/bitstream/icict/52627/2/Paix%c3%a3o_Balthazar_etal_ICICT_COVID-19_2021.pdf
bitstream.checksum.fl_str_mv 0ab46789d568c4ba27c7b5d29a9fe9c4
872190ab6956301110e031ec56c17698
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)
repository.mail.fl_str_mv repositorio.arca@fiocruz.br
_version_ 1798324613985337344

Similar Items