A Brazilian Classified Data Set For Supporting The Differential Diagnosis of Severe Acute Respiratory Syndrome (sars) By Covid-19 and Influenza

By 2022, there were over 600 million reported cases and 6.7 million deaths attributed to COVID-19; Brazil was one of the countries with the highest number of reported deaths. Speedy testing and timely communication of results can significantly reduce disease transmission however in times of high demand for laboratory testing, delayed receipt of results can not only adversely impact the mitigation of disease transmission but complicate the differential diagnosis of COVID-19 and other acute respiratory syndromes such as influenza. This paper presents a set of public data from patients diagnosed with COVID-19 and influenza through laboratory testing, extracted from the Sistema de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) between 2020 and 2021, containing approximately 2.6 million patient records and 168 attributes. After pre-processing, the data set presented in this paper comprised 19,401 records and 46 attributes with 9,167 cases of Severe Acute Respiratory Syndrome (SARS) from COVID-19 and 9,874 cases of SARS from Influenza. The data set presented in this paper can be used for training artificial intelligence models to support differential diagnosis between SARS from COVID-19 or influenza thus supporting a potential low-cost rapid decision support system to assist healthcare professionals in decision-making.