Abstract
The paper presents an innovative application to identify areas vulnerable to coronavirus disease 2019 (COVID-19) considering a combination of spatial analysis and a multi-criteria learning approach. We applied this methodology in the state of Pernambuco, Brazil identifying vulnerable areas by considering a set of determinants and risk factors for COVID-19, including demographic, economic and spatial characteristics and the number of human COVID-19 infections. Examining possible patterns over a set number of days taking the number of cases recorded, we arrived at a set of compatible decision rules to explain the relation between risk factors and COVID-19 cases. The results reveal why certain municipalities are critically vulnerable to COVID-19 highlighting locations for which knowledge can be gained about environmental factors.
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