A) To describe the methodology used to construct a deprivation index by census tract in cities, to identify the tracts with the least favorable socioeconomic conditions, and b) to analyze the association between this index and overall mortality. Several socioeconomic indicators (Census 2001) were defined by the census tracts of the following cities: Barcelona, Bilbao, Madrid, Seville and Valencia. The correlations with the standardized mortality ratio (1996-2003), and the dimensionality of the socioeconomic indicators were studied. Finally, the selected indicators were aggregated in an index, in which the results of the factor loadings from extraction of a factor by principal components were used as weighting values. The indicators with the strongest correlations with overall mortality were those related to work, education, housing conditions and single parent homes. In the analysis of dimensionality, a first dimension appeared that contained indicators related to work (unemployment, manual and eventual workers) and education (insufficient education overall and in young people). In all the cities studied, the index created with these 5 indicators explained more than 75% of their variability. The correlations between this index and mortality generally showed higher values than those obtained with each indicator separately. The deprivation index proposed could be a useful instrument for health planning as it detects small areas of large cities with unfavorable socioeconomic characteristics and is associated with mortality. This index could contribute to the study of social inequalities in health in Spain.

Background: On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. Aim: To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. Methods: A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf’s prospective space-time scan statistic (STSS) to detect daily emerging active clusters. Results: Analyses were performed daily during the summer 2020 (June 21st – August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. Conclusion: STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.

The European Pollutant Emission Register in Spain (EPER-Spain) is a public inventory of pollutant industries created by decision of the European Union. The location of these industries is geocoded and the first published data correspond to 2001. Publication of these data will allow for quantification of the effect of proximity to one or more such plant on cancer and all-cause mortality observed in nearby towns. However, as errors have been detected in the geocoding of many of the pollutant foci shown in the EPER, it was decided that a validation study should be conducted into the accuracy of these co-ordinates. EPER-Spain geographic co-ordinates were drawn from the European Environment Agency (EEA) server and the Spanish Ministry of the Environment (MOE). The Farm Plot Geographic Information System (Sistema de Información Geográfica de Parcelas Agrícolas) (SIGPAC) enables orthophotos (digitalized aerial images) of any territorial point across Spain to be obtained. Through a search of co-ordinates in the SIGPAC, all the industrial foci (except farms) were located. The quality criteria used to ascertain possible errors in industrial location were high, medium and low quality, where industries were situated at a distance of less than 500 metres, more than 500 metres but less than 1 kilometre, and more than 1 kilometre from their real locations, respectively.