Objective: To analyze the spatial pattern of the incidence of COVID-19 in association with social determinants of health (SDH) in the Northeast Region of Brazil during the first year of the pandemic. Methods: We conducted an ecological analytical study that included notifications made between 27 March 2020 and 27 March 2021. The data analysis used two global regression models: the ordinary least squares (OLS) and spatial lag model and the geographically weighted multiscale regression model (GWMSR). Results: We observed that the Gini index, illiteracy rate, percentages of people living below the poverty line, people in households who were vulnerable to poverty, and dependent elderly people are predictors of a higher incidence of COVID-19 in Northeast Brazil. Conclusions: Results of this study may contribute to generating new hypotheses for studies focusing on the syndemic process and for the formulation of intersectoral public policies targeting the population at greatest vulnerability to minimize the impact of the disease.