Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil

By Matheus Ribeiro, Ramon Gomes da Silva, Viviana Cocco Mariani, Leandro dos S. Coelho. Chaos, Solitons & Fractals, 2020

440 citations recorded by the source corpus.

Highlights • Regression models are employed to forecasting COVID-19 cases in the Brazilian context.• Data from ten states with a high incidence of COVID-19 are adopted.• Models for multi-step-ahead forecasting are evaluated.• Out-of-sample forecasting errors lower than 6.9% are achieved by best models.• SVR and stacking ensemble are the most suitable tools to forecasting COVID-19 cases in the evaluated scenarios.

Subfields: Artificial Intelligence, Modeling and Simulation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/36e5a0246ac03433c026fb6f927d0b72f6140b6f