Autor(es): Costa, Marcelo ; Rodrigues, Margarida ; Baptista, Pedro ; Henriques, João ; Pires, Ivan Miguel ; Wanzeller, Cristina ; Caldeira, Filipe
Data: 2021
Identificador Persistente: http://hdl.handle.net/10400.19/7851
Origem: Repositório Científico do Instituto Politécnico de Viseu
Assunto(s): KNN; COVID-19 cases; temperature
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.
