## 4 Methods
### Dataset  
A public dataset ([[https://repositoriodatasharingfapesp.uspdigital.usp.br/handle/it](https://repositoriodatasharingfapesp.uspdigital.usp.br/handle/it)]([https://repositoriodatasharingfapesp.uspdigital.usp.br/handle/it](https://repositoriodatasharingfapesp.uspdigital.usp.br/handle/it)) em/2, accessed on 17 january 2022) was used for this study. The dataset was made available on the COVID-19 Data Sharing/BR platform by two hospitals in Sao Paulo, Brazil: Clinics Hospital (Faculty of Medicine, University of Sao Paulo) on 17 February 2021 and Sriao-Libanes Hospital on 30 June 2020. More than 500 different kinds of tests from 18,424 patients allocated at the hospitals were used in the analysis, including: RT-PCR for SARSCoV-2, patient identification, patient gender, patient year of birth, patient country, federation unit and city of residence, patient test date, test description and test result. The processes of the data collection, elimination of patients' personal information and dataset generation were performed by the above-mentioned institutions. For more accurate identification of COVID-19 cases and their severity, 2453 patient records were chosen for analysis in this study. The established selection criteria included the following rules: the first result for SARS-CoV-2 RT-PCR of the patient and the results of a blood test on the same date. These selected records contained consistent data for the following variables: hematocrit, hemoglobin, platelets, mean platelet volume, red blood cells, lymphocytes, mean corpuscular hemoglobin concentration (MCHC), leukocytes, basophils, mean corpuscular hemoglobin (MCH), eosinophils, mean corpuscular volume (MCV), monocytes and red blood cell distribution width (RDW). These variables were selected due to their frequent presence in routine automated blood test worldwide [59,60]. In the remaining records, empty data were found in one or more selected variables, and for this reason they were excluded from the pre-processing step. Of the 2453 included patients, 1912 of them tested positive and 541 negative by SARS-CoV-2 RT-PCR. The list of blood factors that were part of this study and what they biologically represent follows:  
* _Hematocrit_: Calculation of the percentage of red blood cells (also known as erythrocytes) present in the blood. A low level indicates respiratory problems, and may reflect severity in cases of COVID-19 [15,61]. * _Hemoglobin_: A substance is responsible for the transport of oxygen in the bloodstream, located in the red blood cells. A decrease in _Hb_ level during the short period after  
Figure 9: Variable heatmap—synthetic database, level 2, neuron 2.  
pneumonia diagnosis might be a predictor of worsening pneumonia in COVID-19 patients. In addition, anemia is a common manifestation in COVID-19 [62]. * _Red blood cells_: Blood component responsible for transporting oxygen. Changes in their shape (deformities), size or quantity can indicate anemia, problems related to hypoxia (lack of oxygenation) or even a reduction in the ability of these cells to transport oxygen [63]. RBC count is an important indicator in the evaluation of the treatment of patients with COVID-19 [17], but it is not a good indicator for detecting cases in initial examinations. In [15], time series imaging studies of the cells were performed to analyze the evolution of clinical cases related to COVID-19, and how these cells change. * _Red blood cell distribution width RDW_: This is also known as the RDW coefficient of variation. It provides a measure of heterogeneity in the size of red blood cells. Originally used to identify anemia, it has also become a marker for infections and more serious diseases, such as cancer and cardiovascular and cerebrovascular diseases. In cases of COVID-19, it is not a good indicator for the disease itself, but it was identified as a marker of the severity of cases, as high RDW values are related to death, according to studies by [64; 65; 61].