Long-term exposure to ambient air pollutant concentrations is known to cause chronic lung inflammation, a condition that may promote increased severity of COVID-19 syndrome caused by the novel coronavirus (SARS-CoV-2). In this paper, we empirically investigate the ecologic association between long-term concentrations of area-level fine particulate matter (PM_2.5) and excess deaths in the first quarter of 2020 in municipalities of Northern Italy. The study accounts for potentially spatial confounding factors related to urbanization that may have influenced the spreading of SARS-CoV-2 and related COVID-19 mortality. Our epidemiological analysis uses geographical information (e.g., municipalities) and negative binomial regression to assess whether both ambient PM_2.5 concentration and excess mortality have a similar spatial distribution. Our analysis suggests a positive association of ambient PM_2.5 concentration on excess mortality in Northern Italy related to the COVID-19 epidemic. Our estimates suggest that a one-unit increase in PM_2.5 concentration (µg/m³) is associated with a 9% (95% confidence interval: 6–12%) increase in COVID-19 related mortality.

In this study, we identify some individual and contextual factors potentially affecting subjective well-being in developing countries and check their effect in the Ecuadorian case. Ecuador is an oil country where attempts have been made to overcome deep social and territorial inequalities by placing human well-being at the core of public policy through the National Plan for Good Living. By means of ordinary least squares and ordered logit with clustered standard errors, as well as multilevel ordered logit models, we find that oil-dependent territories negatively affect well-being. Moreover, women and indigenous people report lower well-being, while personal income, education, housing quality, institutional trust, health insurance and social relationships can improve it. From a policy perspective, we find that basic unmet needs still need to be fulfilled to increase well-being, and further improvements of the institutional framework, redistributive system and inclusion policies are required. In this respect, we observe that Good Living-based policy accurately addresses these elements and, therefore, has great potential for application in other countries with similar characteristics.

• We use the spatial panel regression model to estimate the land Kuznets curve. • We examine spatial auto-correlations in the building permits in Ecuador. • A Bayesian selection method allows selecting the right spatial model and weight matrix. • Economic development has a U-shape relationship with land use. • Spatial spillover effects have a limited extent and affect only closest neighbours.