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Boletim COVID-PA: Reports on artificial intelligence-based forecasting to the facing of pandemic COVID-19 in the state of Pará, Brazil

##article.authors##

  • Gilberto Nerino de Souza Jr. Universidade Federal Rural da Amazônia https://orcid.org/0000-0002-8452-3938
  • Marcus de Barros Braga Universidade Federal Rural da Amazônia https://orcid.org/0000-0003-1621-4460
  • Luana Lorena Silva Rodrigues Universidade Federal do Oeste do Pará https://orcid.org/0000-0001-9480-7689
  • Rafael da Silva Fernandes Universidade Federal Rural da Amazônia https://orcid.org/0000-0002-3035-8025
  • Rommel Thiago Jucá Ramos Universidade Federal do Pará
  • Adriana Ribeiro Carneiro Universidade Federal do Pará
  • Silvana Rossy de Brito Universidade Federal Rural da Amazônia
  • Cícero Jorge Fonseca Dolácio Universidade Federal do Paraná
  • Ivaldo da Silva Tavares Jr. Universidade Federal de Viçosa
  • Fernando Napoleão Noronha Universidade Federal Rural da Amazônia
  • Raphael Rodrigues Pinheiro Universidade Federal Rural da Amazônia https://orcid.org/0000-0002-2457-7571
  • Hugo Alex Carneiro Diniz Universidade Federal do Oeste do Pará
  • Marcel do Nascimento Botelho Universidade Federal Rural da Amazônia
  • Antonio Carlos Rosário Vallinoto Universidade Federal do Pará
  • Jonas Elias Castro da Rocha Universidade Federal Rural da Amazônia https://orcid.org/0000-0002-0255-087X

DOI:

https://doi.org/10.1590/s1679-49742021000400012

Keywords:

COVID-19, Artificial Intelligence, Forecasting, Neural Networks, Decision Making

Abstract

Objective: Report the university research and extension product denominated ‘Boletim COVID-PA’ which presented projections about the pandemic in the State of Pará, Brazil, with practical, mathematically rigorous and computationally efficient approaches. Methods: The artificial intelligence technique known as Artificial Neural Networks was used to generate thirteen bulletins with short-term projections based on historical data from the State Department of Public Health system. Results: After eight months of projections, the technique generated reliable results with an average accuracy of 97% (147 days observed) for confirmed cases, 96% (161 observed days) for deaths and 86% (72 days observed) for occupancy of intensive care unit beds. Conclusion: These bulletins have become a useful tool for decision making by public managers, assisting in reallocating hospital resources and optimizing COVID-19 control strategies for the various regions of the State of Pará.

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Posted

08/11/2021

How to Cite

Souza Jr., G. N. de ., Braga, M. de B. ., Rodrigues, L. L. S. ., Fernandes, R. da S. ., Ramos, R. T. J. ., Carneiro, A. R. ., Brito, S. R. de ., Dolácio, C. J. F. ., Tavares Jr., I. da S. ., Noronha, F. N. ., Pinheiro, R. R. ., Diniz, H. A. C. ., Botelho, M. do N. ., Vallinoto, A. C. R. ., & Rocha, J. E. C. da . (2021). Boletim COVID-PA: Reports on artificial intelligence-based forecasting to the facing of pandemic COVID-19 in the state of Pará, Brazil. In SciELO Preprints. https://doi.org/10.1590/s1679-49742021000400012

Section

Health Sciences