Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da FIOCRUZ (ARCA) |
Texto Completo: | https://www.arca.fiocruz.br/handle/icict/60774 |
Resumo: | Fundação Oswaldo Cruz . Fundação Rockefeller. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Brasil). Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). |
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Boaventura, Viviane S.Grave, MalúSilva, Thiago CerqueiraCarreiro, RobertoPinheiro, AdéliaCoutinho, AlvaroBarral Netto, Manoel2023-10-11T16:04:05Z2023-10-11T16:04:05Z2023BOAVENTURA, Viviane S. et al. Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil. JMIR Public Health and Surveillance, v. 9, p. 1-10, 2023.2369-2960https://www.arca.fiocruz.br/handle/icict/6077410.2196/40036Fundação Oswaldo Cruz . Fundação Rockefeller. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Brasil). Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Doenças Infecciosas Transmitidas por Vetores. Salvador, BA, Brasil / Universidade Federal da Bahia. Faculdade de Medicina. Salvador, BA, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Engenharia Civil. Rio de Janeiro, RJ, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / Universidade Federal Fluminense. Departamento de Engenharia Civil. Niterói, RJ, Brasil.Universidade Federal da Bahia. Faculdade de Medicina. Salvador, BA, Brasil /Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimento para Saúde. Salvador, BA, Brasil.Universidade Estadual de Santa Cruz. Departamento de Ciências da Saúde. Salvador, BA, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Engenharia Civil. Rio de Janeiro, RJ, Brasil.Universidade Federal da Bahia. Faculdade de Medicina. Salvador, BA, Brasil /Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil.Background: Telehealth has been widely used for new case detection and telemonitoring during the COVID-19 pandemic. It safely provides access to health care services and expands assistance to remote, rural areas and underserved communities in situations of shortage of specialized health professionals. Qualified data are systematically collected by health care workers containing information on suspected cases and can be used as a proxy of disease spread for surveillance purposes. However, the use of this approach for syndromic surveillance has yet to be explored. Besides, the mathematical modeling of epidemics is a well-established field that has been successfully used for tracking the spread of SARS-CoV-2 infection, supporting the decision-making process on diverse aspects of public health response to the COVID-19 pandemic. The response of the current models depends on the quality of input data, particularly the transmission rate, initial conditions, and other parameters present in compartmental models. Telehealth systems may feed numerical models developed to model virus spread in a specific region. Objective: Herein, we evaluated whether a high-quality data set obtained from a state-based telehealth service could be used to forecast the geographical spread of new cases of COVID-19 and to feed computational models of disease spread. Methods: We analyzed structured data obtained from a statewide toll-free telehealth service during 4 months following the first notification of COVID-19 in the Bahia state, Brazil. Structured data were collected during teletriage by a health team of medical students supervised by physicians. Data were registered in a responsive web application for planning and surveillance purposes. The data set was designed to quickly identify users, city, residence neighborhood, date, sex, age, and COVID-19–like symptoms. We performed a temporal-spatial comparison of calls reporting COVID-19–like symptoms and notification of COVID-19 cases. The number of calls was used as a proxy of exposed individuals to feed a mathematical model called “susceptible, exposed, infected, recovered, deceased.” Results: For 181 (43%) out of 417 municipalities of Bahia, the first call to the telehealth service reporting COVID-19–like symptoms preceded the first notification of the disease. The calls preceded, on average, 30 days of the notification of COVID-19 in the municipalities of the state of Bahia, Brazil. Additionally, data obtained by the telehealth service were used to effectively reproduce the spread of COVID-19 in Salvador, the capital of the state, using the “susceptible, exposed, infected, recovered, deceased” model to simulate the spatiotemporal spread of the disease.engJMIR PublicationsTelessaúdeTelemedicinaVigilância de doençasCOVID 19Monitoramento VigilânciaModelagem computacionalTransmissãoDoenças infecciosasSindrômicoTelehealthTelemedicineDisease surveillanceCOVID-19MonitoringSurveillanceComputational modelingTransmissionInfectious diseasesSyndromicTelemedicinaControle de Vetores de DoençasCOVID 19Simulação por ComputadorDoenças TransmissíveisSyndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-82991https://www.arca.fiocruz.br/bitstream/icict/60774/1/license.txt5a560609d32a3863062d77ff32785d58MD51ORIGINALBoaventura, Viviane S. - Syndromic Surveillance Using Structured Telehealth Data.pdfBoaventura, Viviane S. - Syndromic Surveillance Using Structured Telehealth Data.pdfapplication/pdf1167751https://www.arca.fiocruz.br/bitstream/icict/60774/2/Boaventura%2c%20Viviane%20%20S.%20-%20Syndromic%20Surveillance%20Using%20Structured%20Telehealth%20Data.pdf42b2bad1791cd3d84c2f3ac47d41dc0fMD52icict/607742023-10-11 13:04:05.932oai:www.arca.fiocruz.br:icict/60774Q0VTU8ODTyBOw4NPIEVYQ0xVU0lWQSBERSBESVJFSVRPUyBBVVRPUkFJUwoKQW8gYWNlaXRhciBvcyBURVJNT1MgZSBDT05EScOHw5VFUyBkZXN0YSBDRVNTw4NPLCBvIEFVVE9SIGUvb3UgVElUVUxBUiBkZSBkaXJlaXRvcwphdXRvcmFpcyBzb2JyZSBhIE9CUkEgZGUgcXVlIHRyYXRhIGVzdGUgZG9jdW1lbnRvOgoKKDEpIENFREUgZSBUUkFOU0ZFUkUsIHRvdGFsIGUgZ3JhdHVpdGFtZW50ZSwgw6AgRklPQ1JVWiAtIEZVTkRBw4fDg08gT1NXQUxETyBDUlVaLCBlbQpjYXLDoXRlciBwZXJtYW5lbnRlLCBpcnJldm9nw6F2ZWwgZSBOw4NPIEVYQ0xVU0lWTywgdG9kb3Mgb3MgZGlyZWl0b3MgcGF0cmltb25pYWlzIE7Dg08KQ09NRVJDSUFJUyBkZSB1dGlsaXphw6fDo28gZGEgT0JSQSBhcnTDrXN0aWNhIGUvb3UgY2llbnTDrWZpY2EgaW5kaWNhZGEgYWNpbWEsIGluY2x1c2l2ZSBvcyBkaXJlaXRvcwpkZSB2b3ogZSBpbWFnZW0gdmluY3VsYWRvcyDDoCBPQlJBLCBkdXJhbnRlIHRvZG8gbyBwcmF6byBkZSBkdXJhw6fDo28gZG9zIGRpcmVpdG9zIGF1dG9yYWlzLCBlbQpxdWFscXVlciBpZGlvbWEgZSBlbSB0b2RvcyBvcyBwYcOtc2VzOwoKKDIpIEFDRUlUQSBxdWUgYSBjZXNzw6NvIHRvdGFsIG7Do28gZXhjbHVzaXZhLCBwZXJtYW5lbnRlIGUgaXJyZXZvZ8OhdmVsIGRvcyBkaXJlaXRvcyBhdXRvcmFpcwpwYXRyaW1vbmlhaXMgbsOjbyBjb21lcmNpYWlzIGRlIHV0aWxpemHDp8OjbyBkZSBxdWUgdHJhdGEgZXN0ZSBkb2N1bWVudG8gaW5jbHVpLCBleGVtcGxpZmljYXRpdmFtZW50ZSwKb3MgZGlyZWl0b3MgZGUgZGlzcG9uaWJpbGl6YcOnw6NvIGUgY29tdW5pY2HDp8OjbyBww7pibGljYSBkYSBPQlJBLCBlbSBxdWFscXVlciBtZWlvIG91IHZlw61jdWxvLAppbmNsdXNpdmUgZW0gUmVwb3NpdMOzcmlvcyBEaWdpdGFpcywgYmVtIGNvbW8gb3MgZGlyZWl0b3MgZGUgcmVwcm9kdcOnw6NvLCBleGliacOnw6NvLCBleGVjdcOnw6NvLApkZWNsYW1hw6fDo28sIHJlY2l0YcOnw6NvLCBleHBvc2nDp8OjbywgYXJxdWl2YW1lbnRvLCBpbmNsdXPDo28gZW0gYmFuY28gZGUgZGFkb3MsIHByZXNlcnZhw6fDo28sIGRpZnVzw6NvLApkaXN0cmlidWnDp8OjbywgZGl2dWxnYcOnw6NvLCBlbXByw6lzdGltbywgdHJhZHXDp8OjbywgZHVibGFnZW0sIGxlZ2VuZGFnZW0sIGluY2x1c8OjbyBlbSBub3ZhcyBvYnJhcyBvdQpjb2xldMOibmVhcywgcmV1dGlsaXphw6fDo28sIGVkacOnw6NvLCBwcm9kdcOnw6NvIGRlIG1hdGVyaWFsIGRpZMOhdGljbyBlIGN1cnNvcyBvdSBxdWFscXVlciBmb3JtYSBkZQp1dGlsaXphw6fDo28gbsOjbyBjb21lcmNpYWw7CgooMykgUkVDT05IRUNFIHF1ZSBhIGNlc3PDo28gYXF1aSBlc3BlY2lmaWNhZGEgY29uY2VkZSDDoCBGSU9DUlVaIC0gRlVOREHDh8ODTyBPU1dBTERPCkNSVVogbyBkaXJlaXRvIGRlIGF1dG9yaXphciBxdWFscXVlciBwZXNzb2Eg4oCTIGbDrXNpY2Egb3UganVyw61kaWNhLCBww7pibGljYSBvdSBwcml2YWRhLCBuYWNpb25hbCBvdQplc3RyYW5nZWlyYSDigJMgYSBhY2Vzc2FyIGUgdXRpbGl6YXIgYW1wbGFtZW50ZSBhIE9CUkEsIHNlbSBleGNsdXNpdmlkYWRlLCBwYXJhIHF1YWlzcXVlcgpmaW5hbGlkYWRlcyBuw6NvIGNvbWVyY2lhaXM7CgooNCkgREVDTEFSQSBxdWUgYSBvYnJhIMOpIGNyaWHDp8OjbyBvcmlnaW5hbCBlIHF1ZSDDqSBvIHRpdHVsYXIgZG9zIGRpcmVpdG9zIGFxdWkgY2VkaWRvcyBlIGF1dG9yaXphZG9zLApyZXNwb25zYWJpbGl6YW5kby1zZSBpbnRlZ3JhbG1lbnRlIHBlbG8gY29udGXDumRvIGUgb3V0cm9zIGVsZW1lbnRvcyBxdWUgZmF6ZW0gcGFydGUgZGEgT0JSQSwKaW5jbHVzaXZlIG9zIGRpcmVpdG9zIGRlIHZveiBlIGltYWdlbSB2aW5jdWxhZG9zIMOgIE9CUkEsIG9icmlnYW5kby1zZSBhIGluZGVuaXphciB0ZXJjZWlyb3MgcG9yCmRhbm9zLCBiZW0gY29tbyBpbmRlbml6YXIgZSByZXNzYXJjaXIgYSBGSU9DUlVaIC0gRlVOREHDh8ODTyBPU1dBTERPIENSVVogZGUKZXZlbnR1YWlzIGRlc3Blc2FzIHF1ZSB2aWVyZW0gYSBzdXBvcnRhciwgZW0gcmF6w6NvIGRlIHF1YWxxdWVyIG9mZW5zYSBhIGRpcmVpdG9zIGF1dG9yYWlzIG91CmRpcmVpdG9zIGRlIHZveiBvdSBpbWFnZW0sIHByaW5jaXBhbG1lbnRlIG5vIHF1ZSBkaXogcmVzcGVpdG8gYSBwbMOhZ2lvIGUgdmlvbGHDp8O1ZXMgZGUgZGlyZWl0b3M7CgooNSkgQUZJUk1BIHF1ZSBjb25oZWNlIGEgUG9sw610aWNhIEluc3RpdHVjaW9uYWwgZGUgQWNlc3NvIEFiZXJ0byBkYSBGSU9DUlVaIC0gRlVOREHDh8ODTwpPU1dBTERPIENSVVogZSBhcyBkaXJldHJpemVzIHBhcmEgbyBmdW5jaW9uYW1lbnRvIGRvIHJlcG9zaXTDs3JpbyBpbnN0aXR1Y2lvbmFsIEFSQ0EuCgpBIFBvbMOtdGljYSBJbnN0aXR1Y2lvbmFsIGRlIEFjZXNzbyBBYmVydG8gZGEgRklPQ1JVWiAtIEZVTkRBw4fDg08gT1NXQUxETyBDUlVaIHJlc2VydmEKZXhjbHVzaXZhbWVudGUgYW8gQVVUT1Igb3MgZGlyZWl0b3MgbW9yYWlzIGUgb3MgdXNvcyBjb21lcmNpYWlzIHNvYnJlIGFzIG9icmFzIGRlIHN1YSBhdXRvcmlhCmUvb3UgdGl0dWxhcmlkYWRlLCBzZW5kbyBvcyB0ZXJjZWlyb3MgdXN1w6FyaW9zIHJlc3BvbnPDoXZlaXMgcGVsYSBhdHJpYnVpw6fDo28gZGUgYXV0b3JpYSBlIG1hbnV0ZW7Dp8OjbwpkYSBpbnRlZ3JpZGFkZSBkYSBPQlJBIGVtIHF1YWxxdWVyIHV0aWxpemHDp8Ojby4KCkEgUG9sw610aWNhIEluc3RpdHVjaW9uYWwgZGUgQWNlc3NvIEFiZXJ0byBkYSBGSU9DUlVaIC0gRlVOREHDh8ODTyBPU1dBTERPIENSVVoKcmVzcGVpdGEgb3MgY29udHJhdG9zIGUgYWNvcmRvcyBwcmVleGlzdGVudGVzIGRvcyBBdXRvcmVzIGNvbSB0ZXJjZWlyb3MsIGNhYmVuZG8gYW9zIEF1dG9yZXMKaW5mb3JtYXIgw6AgSW5zdGl0dWnDp8OjbyBhcyBjb25kacOnw7VlcyBlIG91dHJhcyByZXN0cmnDp8O1ZXMgaW1wb3N0YXMgcG9yIGVzdGVzIGluc3RydW1lbnRvcy4KRepositório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352023-10-11T16:04:05Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false |
dc.title.en_US.fl_str_mv |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
title |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
spellingShingle |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil Boaventura, Viviane S. Telessaúde Telemedicina Vigilância de doenças COVID 19 Monitoramento Vigilância Modelagem computacional Transmissão Doenças infecciosas Sindrômico Telehealth Telemedicine Disease surveillance COVID-19 Monitoring Surveillance Computational modeling Transmission Infectious diseases Syndromic Telemedicina Controle de Vetores de Doenças COVID 19 Simulação por Computador Doenças Transmissíveis |
title_short |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
title_full |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
title_fullStr |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
title_full_unstemmed |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
title_sort |
Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil |
author |
Boaventura, Viviane S. |
author_facet |
Boaventura, Viviane S. Grave, Malú Silva, Thiago Cerqueira Carreiro, Roberto Pinheiro, Adélia Coutinho, Alvaro Barral Netto, Manoel |
author_role |
author |
author2 |
Grave, Malú Silva, Thiago Cerqueira Carreiro, Roberto Pinheiro, Adélia Coutinho, Alvaro Barral Netto, Manoel |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Boaventura, Viviane S. Grave, Malú Silva, Thiago Cerqueira Carreiro, Roberto Pinheiro, Adélia Coutinho, Alvaro Barral Netto, Manoel |
dc.subject.other.en_US.fl_str_mv |
Telessaúde Telemedicina Vigilância de doenças COVID 19 Monitoramento Vigilância Modelagem computacional Transmissão Doenças infecciosas Sindrômico |
topic |
Telessaúde Telemedicina Vigilância de doenças COVID 19 Monitoramento Vigilância Modelagem computacional Transmissão Doenças infecciosas Sindrômico Telehealth Telemedicine Disease surveillance COVID-19 Monitoring Surveillance Computational modeling Transmission Infectious diseases Syndromic Telemedicina Controle de Vetores de Doenças COVID 19 Simulação por Computador Doenças Transmissíveis |
dc.subject.en.en_US.fl_str_mv |
Telehealth Telemedicine Disease surveillance COVID-19 Monitoring Surveillance Computational modeling Transmission Infectious diseases Syndromic |
dc.subject.decs.en_US.fl_str_mv |
Telemedicina Controle de Vetores de Doenças COVID 19 Simulação por Computador Doenças Transmissíveis |
description |
Fundação Oswaldo Cruz . Fundação Rockefeller. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Brasil). Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-10-11T16:04:05Z |
dc.date.available.fl_str_mv |
2023-10-11T16:04:05Z |
dc.date.issued.fl_str_mv |
2023 |
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 |
BOAVENTURA, Viviane S. et al. Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil. JMIR Public Health and Surveillance, v. 9, p. 1-10, 2023. |
dc.identifier.uri.fl_str_mv |
https://www.arca.fiocruz.br/handle/icict/60774 |
dc.identifier.issn.en_US.fl_str_mv |
2369-2960 |
dc.identifier.doi.none.fl_str_mv |
10.2196/40036 |
identifier_str_mv |
BOAVENTURA, Viviane S. et al. Syndromic surveillance using structured telehealth data: case study of the first wave of COVID-19 in Brazil. JMIR Public Health and Surveillance, v. 9, p. 1-10, 2023. 2369-2960 10.2196/40036 |
url |
https://www.arca.fiocruz.br/handle/icict/60774 |
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eng |
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eng |
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JMIR Publications |
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JMIR Publications |
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