COVID-PA Bulletin: reports on artificial intelligence-based forecasting in coping with COVID-19 pandemic in the state of Para, Brazil

被引:1
|
作者
de Souza Jr, Gilberto Nerino [1 ]
Braga, Marcus de Barros [1 ]
Silva Rodrigues, Luana Lorena [2 ]
Fernandes, Rafael da Silva [3 ]
Juca Ramos, Rommel Thiago [4 ]
Carneiro, Adriana Ribeiro [4 ]
de Brito, Silvana Rossy [5 ]
Fonseca Dolacio, Cicero Jorge [6 ]
Tavares Jr, Ivaldo da Silva [7 ]
Noronha, Fernando Napoleao [3 ]
Pinheiro, Raphael Rodrigues [8 ]
Carneiro Diniz, Hugo Alex [9 ]
Botelho, Marcel do Nascimento [10 ]
Rosario Vallinoto, Antonio Carlos [4 ]
Castro da Rocha, Jonas Elias [1 ]
机构
[1] Univ Fed Rural Amazonia, Campus Paragominas, Paragominas, Para, Brazil
[2] Univ Fed Oeste Para, Programa Posgrad Ciencias Saude, Santarem, Para, Brazil
[3] Univ Fed Rural Amazonia, Campus Parauapebas, Parauapebas, Para, Brazil
[4] Univ Fed Para, Inst Ciencias Biol, Belem, Para, Brazil
[5] Univ Fed Rural Amazonia, Inst Ciberespacial, Belem, Para, Brazil
[6] Univ Fed Parana, Dept Engn & Tecnol Florestal, Curitiba, Parana, Brazil
[7] Univ Fed Vicosa, Dept Engn Florestal, Vicosa, MG, Brazil
[8] Univ Fed Rural Amazonia, Campus Belem, Belem, Para, Brazil
[9] Univ Fed Oeste Para, Inst Ciencias Educ, Santarem, Para, Brazil
[10] Univ Fed Rural Amazonia, Inst Socioambiental & Recursos Hidr, Belem, Para, Brazil
来源
EPIDEMIOLOGIA E SERVICOS DE SAUDE | 2021年 / 30卷 / 04期
关键词
COVID-19; Artificial Intelligence; Forecast; Neural Networks; Decision Making; PREDICTION; MODELS;
D O I
10.1590/S1679-49742021000400012
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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 Para, 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 Para.
引用
收藏
页数:9
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