Feasibility of very short-term forecast models for COVID-19 hospital-based surveillance

Martinez, Edson Zangiacomi; Passos, Afonso Dinis Costa; Cinto, Antônio Fernando; Escarso, Andreia Cássia; Monteiro, Rosane Aparecida; Silva, Jorgete Maria e; Bellissimo-Rodrigues, Fernando; Aragon, Davi Casale

Feasibility of very short-term forecast models for COVID-19 hospital-based surveillance

Martinez, Edson Zangiacomi; Passos, Afonso Dinis Costa; Cinto, Antônio Fernando; Escarso, Andreia Cássia; Monteiro, Rosane Aparecida; Silva, Jorgete Maria e; Bellissimo-Rodrigues, Fernando; Aragon, Davi Casale.

Rev. Soc. Bras. Med. Trop; 54 (), 2021

Publication year: 2021

Abstract INTRODUCTION:

We evaluated the performance of Bayesian vector autoregressive (BVAR) and Holt's models to forecast the weekly COVID-19 reported cases in six units of a large hospital.

METHODS:

Cases reported from epidemiologic weeks (EW) 12-37 were selected as the training period, and from EW 38-41 as the test period.

RESULTS:

The models performed well in forecasting cases within one or two weeks following the end of the time-series, but forecasts for a more distant period were inaccurate.

CONCLUSIONS:

Both models offered reasonable performance in very short-term forecasts for confirmed cases of COVID-19.

Teorema de Bayes, Infecciones por Coronavirus, Estudios de Factibilidad, Predicción, Hospitales, Modelos Teóricos, Betacoronavirus

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