Background: Given the increasing rates at which people have been infected by Covid-19 evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peaking and descending behaviours of the curve of infections.Results: This study highlights clusters of the most affected neighbourhoods and their determinant effects. We have observed the increasing phase with hotspots of confirmed cases in a well-developed and heavily densely-populated neighbourhood of Recife city, then evolving for hotspots of case-fatality rates into areas characterised by having a precarious provision of public services and low-income population. The results also help to understand the influence of the age, income, level of education of the population and, additionally, the people’s access to public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.