Costa, MarceloRodrigues, MargaridaBaptista, PedroHenriques, JoãoPires, Ivan MiguelWanzeller, CristinaCaldeira, Filipe2023-07-042023-07-0420211867-82111867-822Xhttp://hdl.handle.net/10400.19/7851Historically, 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.engKNNCOVID-19 casestemperatureconference object2023-06-14cv-prod-263202910.1007/978-3-030-91421-9_4