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COVID-PA Bulletin: reports on artificial intelligence-based forecasting in coping with COVID-19 pandemic in the state of Pará, Brazil. / Boletim COVID-PA: relatos sobre projeções baseadas em inteligência artificial no enfrentamento da pandemia de COVID-19 no estado do Pará.
Souza, Gilberto Nerino de; Braga, Marcus de Barros; Rodrigues, Luana Lorena Silva; Fernandes, Rafael da Silva; Ramos, Rommel Thiago Jucá; Carneiro, Adriana Ribeiro; Brito, Silvana Rossy de; Dolácio, Cícero Jorge Fonseca; Tavares, Ivaldo da Silva; Noronha, Fernando Napoleão; Pinheiro, Raphael Rodrigues; Diniz, Hugo Alex Carneiro; Botelho, Marcel do Nascimento; Vallinoto, Antonio Carlos Rosário; Rocha, Jonas Elias Castro da.
  • Souza GN; Universidade Federal Rural da Amazônia, Campus Paragominas, Paragominas, Pará, Brasil.
  • Braga MB; Universidade Federal Rural da Amazônia, Campus Paragominas, Paragominas, Pará, Brasil.
  • Rodrigues LLS; Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Ciências da Saúde, Santarém, PA, Brasil.
  • Fernandes RDS; Universidade Federal Rural da Amazônia, Campus Parauapebas, Parauapebas, Pará, Brasil.
  • Ramos RTJ; Universidade Federal do Pará, Instituto de Ciências Biológicas, Belém, PA, Brasil.
  • Carneiro AR; Universidade Federal do Pará, Instituto de Ciências Biológicas, Belém, PA, Brasil.
  • Brito SR; Universidade Federal Rural da Amazônia, Instituto Ciberespacial, Belém, PA, Brasil.
  • Dolácio CJF; Universidade Federal do Paraná, Departamento de Engenharia e Tecnologia Florestal, Curitiba, PR, Brasil.
  • Tavares IDS; Universidade Federal de Viçosa, Departamento de Engenharia Florestal, Viçosa, MG, Brasil.
  • Noronha FN; Universidade Federal Rural da Amazônia, Campus Parauapebas, Parauapebas, Pará, Brasil.
  • Pinheiro RR; Universidade Federal Rural da Amazônia, Campus Belém, Belém, PA, Brasil.
  • Diniz HAC; Universidade Federal do Oeste do Pará, Instituto de Ciências da Educação, Santarém, PA, Brasil.
  • Botelho MDN; Universidade Federal Rural da Amazônia, Instituto Socioambiental e dos Recursos Hídricos, Belém, PA, Brasil.
  • Vallinoto ACR; Universidade Federal do Pará, Instituto de Ciências Biológicas, Belém, PA, Brasil.
  • Rocha JECD; Universidade Federal Rural da Amazônia, Campus Paragominas, Paragominas, Pará, Brasil.
Epidemiol Serv Saude ; 30(4): e2021098, 2021.
Article in English, Portuguese | MEDLINE | ID: covidwho-1502175
ABSTRACT

OBJECTIVE:

To report the university extension research result entitled 'The COVID-PA Bulletin', which presented forecasts on the behavior of the pandemic in the state of Pará, Brazil.

METHODS:

The artificial intelligence technique also known as 'artificial neural networks' was used to generate 13 bulletins with short-term forecasts based on historical data from the State Department of Public Health information system.

RESULTS:

After eight months of predictions, the technique generated reliable results, with an average accuracy of 97% (observed for147 days) for confirmed cases, 96% (observed for 161 days) for deaths and 86% (observed for 72 days) for Intensive Care Unit bed occupancy.

CONCLUSION:

These bulletins have become a useful decision-making tool for public managers, assisting in the reallocation of hospital resources and optimization of COVID-19 control strategies in various regions of the state of Pará.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Case report / Observational study / Prognostic study Limits: Humans Country/Region as subject: South America / Brazil Language: English / Portuguese Journal: Epidemiol Serv Saude Year: 2021 Document Type: Article Affiliation country: S1679-49742021000400012

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Case report / Observational study / Prognostic study Limits: Humans Country/Region as subject: South America / Brazil Language: English / Portuguese Journal: Epidemiol Serv Saude Year: 2021 Document Type: Article Affiliation country: S1679-49742021000400012