## 3 Materials and Methods  
### Datasets and Pre-Processing  
The data for this study were obtained from the official COVID-19 repository of Ministry of Science, Technology, Knowledge and Innovation (MICITEC), which contains national, regional, and communal data associated with COVID-19. We used the commune of Concepcion as a study case for feature importance analysis and incidence classification (refer to Figure 1). This commune is located in one of the most densely populated regions of the country: Biobio Region [46]. From the official COVID-19 repository, we used databases containing national summaries, regional summaries, and commune data for the period from April 2020 to March 2021.  
At the commune level, we used the following features:* Mobility: This feature was reported as the movements of mobile phones (antenna transitions) connected to Telefonica's national network, in a grouped and anonymous way. The internal mobility is measured as the evolution of travel occurring within the commune, and the external mobility is calculated as the movement from outside the commune into the commune. The mobility index corresponds to the number of trips within a specific commune normalized by the number of commune residents.
* Deaths: Number of deaths by residence and date in the commune of Concepcion. At the regional level, we used the following features:
* Patients in ICU: Number of patients in an ICU who are COVID-19 confirmed cases by region, reported daily.
* Deaths: Number of COVID-19 diagnosed deaths per day, according to the region of residence, reported daily.
* Critical bed occupancy: Number of beds in an adult ICU by region, total occupation, and occupation by COVID-19.  
Finally, at the national level, we used the following features:  
* Patients in ICU (age group): Number of patients in an ICU by age groups (<=39; 40-49; 50-59; 60-69; and >=70) who are COVID-19 confirmed cases, reported daily.
* Deaths (age group): Number of people who died of COVID-19, grouped by age ranges (<=39; 40-49; 50-59; 60-69; 70-79; 80-89; and >=90) reported daily.
* Mechanical ventilator availability: Number of mechanical ventilators available and the number of ventilators occupied for each date reported.
* Patient hospitalization (bed type): Number of hospitalized patients with a COVID-19 diagnosis according to the type of bed they occupy: basic, medium, ITU and ICU.
* Patients on mechanical ventilation: Number of hospitalized patients in the ICU. The number of patients who require invasive mechanical ventilation, patients without mechanical ventilation and those connected to noninvasive mechanical ventilation who are COVID-19 confirmed cases.  
Figure 1: Evolution of some COVID-19 features together with the incidence behavior over the study time.  
We standardized these datasets, i.e., we centered the values around the mean with unit standard deviation [47]. Standardization is one of the feature scaling techniques that aim to make the gradient descent converge faster to minimum values in neural network-based algorithms or make all features contribute equally in the case of distance-based algorithms such as SVM [48]. In addition to describing the variables provided in this section, we will perform a descriptive statistical analysis for a better understanding of the study.