Research Article
COVID-19 Next Day Trend Forecast
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@INPROCEEDINGS{10.1007/978-3-030-91421-9_4, author={Marcelo Costa and Margarida Rodrigues and Pedro Baptista and Jo\"{a}o Henriques and Ivan Miguel Pires and Cristina Wanzeller and Filipe Caldeira}, title={COVID-19 Next Day Trend Forecast}, proceedings={Smart Objects and Technologies for Social Good. 7th EAI International Conference, GOODTECHS 2021, Virtual Event, September 15--17, 2021, Proceedings}, proceedings_a={GOODTECHS}, year={2022}, month={1}, keywords={KNN COVID-19 cases Temperature}, doi={10.1007/978-3-030-91421-9_4} }- Marcelo Costa
Margarida Rodrigues
Pedro Baptista
João Henriques
Ivan Miguel Pires
Cristina Wanzeller
Filipe Caldeira
Year: 2022
COVID-19 Next Day Trend Forecast
GOODTECHS
Springer
DOI: 10.1007/978-3-030-91421-9_4
Abstract
Historically, weather conditions are depicted as an essential factor to be considered in predicting variation infections due to respiratory diseases, including influenza and Severe Acute Respiratory Syndrome SARS-CoV-2, best known as COVID-19. Predicting the number of cases will contribute to plan human and non-human resources in hospital facilities, including beds, ventilators, and support policy decisions on sanitary population warnings, and help to provision the demand for COVID-19 tests. In this work, an integrated framework predicts the number of cases for the upcoming days by considering the COVID-19 cases and temperature records supported by a kNN algorithm.
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