Symptom-based predictive model of COVID-19 disease in children

Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is neither always accessible nor easy to perform in children. We aimed to propose a machine learning model to assess the need for a SARS-CoV-2 test in children (<16 years old), depending on their clinical symptoms. Methods: Epidemiological and clinical data were obtained from the REDCap® registry. Overall, 4434 SARS-CoV-2 tests were performed in symptomatic children between 1 November 2020 and 31 March 2021, 784 were positive (17.68%). We pre-processed the data to be suitable for a machine learning (ML) algorithm, balancing the positive-negative rate and preparing subsets of data by ageThis research has received external funding from the Fundació la Marató tv3 after being awarded in the COVID-19 research call with the expedient number 202134-30-31.Objectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (published version