Impact of the COVID-19 Pandemic on the Socioeconomic Inequalities in Mortality in Spanish Provinces.

BACKGROUND: Although many studies have assessed the socioeconomic inequalities caused by COVID-19 in several health outcomes, there are numerous issues that have been poorly addressed. For instance, have socioeconomic inequalities in mortality from COVID-19 increased? What impact has the pandemic had on inequalities in specific causes of mortality other than COVID-19? Are the inequalities in COVID-19 mortality different from other causes? In this paper we have attempted to answer these questions for the case of Spain. METHODS: We used a mixed longitudinal ecological design in which we observed mortality from 2005 to 2020 in the 54 provinces into which Spain is divided. We considered mortality from all causes, not excluding, and excluding mortality from COVID-19; and cause-specific mortality. We were interested in analysing the trend of the outcome variables according to inequality, controlling for both observed and unobserved confounders. RESULTS: Our main finding was that the increased risk of dying in 2020 was greater in the Spanish provinces with greater inequality. In addition, we have found that: (i) the pandemic has exacerbated socioeconomic inequalities in mortality, (ii) COVID-19 has led to gender differences in the variations in risk of dying (higher in the case of women) and (iii) only in cardiovascular diseases and Alzheimer did the increased risk of dying differ between the most and least unequal provinces. The increase in the risk of dying was different by gender (greater in women) for cardiovascular diseases and cancer. CONCLUSION: Our results can be used to help health authorities know where and in which population groups future pandemics will have the greatest impact and, therefore, be able to take appropriate measures to prevent such effects.

PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain.

BACKGROUND: The principal objective of this paper is to introduce an online interactive application that helps in real-time monitoring of the COVID-19 pandemic in Catalonia, Spain (PandemonCAT). METHODS: This application is designed as a collection of user-friendly dashboards using open-source R software supported by the Shiny package. RESULTS: PandemonCAT reports accumulated weekly updates of COVID-19 dynamics in a geospatial interactive platform for individual basic health areas (ABSs) of Catalonia. It also shows on a georeferenced map the evolution of vaccination campaigns representing the share of population with either one or two shots of the vaccine, for populations of different age groups. In addition, the application reports information about environmental and socioeconomic variables and also provides an interactive interface to visualize monthly public mobility before, during, and after the lockdown phases. Finally, we report the smoothed standardized COVID-19 infected cases and mortality rates on maps of basic health areas ABSs and regions of Catalonia. These smoothed rates allow the user to explore geographic patterns in incidence and mortality rates. The visualization of the variables that could have some influence on the spatiotemporal dynamics of the pandemic is demonstrated. CONCLUSIONS: We believe the addition of these new dimensions, which is the key innovation of our project, will improve the current understanding of the spread and the impact of COVID-19 in the community. This application can be used as an open tool for consultation by the public of Catalonia and Spain in general. It could also have implications in facilitating the visualization of public health data, allowing timely interpretation due to the unpredictable nature of the pandemic.

Methodological limitations in studies assessing the effects of environmental and socioeconomic variables on the spread of COVID-19: a systematic review.

BACKGROUND: While numerous studies have assessed the effects of environmental (meteorological variables and air pollutants) and socioeconomic variables on the spread of the COVID-19 pandemic, many of them, however, have significant methodological limitations and errors that could call their results into question. Our main objective in this paper is to assess the methodological limitations in studies that evaluated the effects of environmental and socioeconomic variables on the spread of COVID-19. MAIN BODY: We carried out a systematic review by conducting searches in the online databases PubMed, Web of Science and Scopus up to December 31, 2020. We first excluded those studies that did not deal with SAR-CoV-2 or COVID-19, preprints, comments, opinion or purely narrative papers, reviews and systematic literature reviews. Among the eligible full-text articles, we then excluded articles that were purely descriptive and those that did not include any type of regression model. We evaluated the risk of bias in six domains: confounding bias, control for population, control of spatial and/or temporal dependence, control of non-linearities, measurement errors and statistical model. Of the 5631 abstracts initially identified, we were left with 132 studies on which to carry out the qualitative synthesis. Of the 132 eligible studies, we evaluated 63.64% of the studies as high risk of bias, 19.70% as moderate risk of bias and 16.67% as low risk of bias. CONCLUSIONS: All the studies we have reviewed, to a greater or lesser extent, have methodological limitations. These limitations prevent conclusions being drawn concerning the effects environmental (meteorological and air pollutants) and socioeconomic variables have had on COVID-19 outcomes. However, we dare to argue that the effects of these variables, if they exist, would be indirect, based on their relationship with social contact. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12302-021-00550-7.

Effects of long-term exposure to air pollutants on the spatial spread of COVID-19 in Catalonia, Spain.

BACKGROUND: The risk of infection and death by COVID-19 could be associated with a heterogeneous distribution at a small area level of environmental, socioeconomic and demographic factors. Our objective was to investigate, at a small area level, whether long-term exposure to air pollutants increased the risk of COVID-19 incidence and death in Catalonia, Spain, controlling for socioeconomic and demographic factors. METHODS: We used a mixed longitudinal ecological design with the study population consisting of small areas in Catalonia for the period February 25 to May 16, 2020. We estimated Generalized Linear Mixed models in which we controlled for a wide range of observed and unobserved confounders as well as spatial and temporal dependence. RESULTS: We have found that long-term exposure to nitrogen dioxide (NO2) and, to a lesser extent, to coarse particles (PM10) have been independent predictors of the spatial spread of COVID-19. For every 1 µm/m3 above the mean the risk of a positive test case increased by 2.7% (95% credibility interval, ICr: 0.8%, 4.7%) for NO2 and 3.0% (95% ICr: -1.4%,7.44%) for PM10. Regions with levels of NO2 exposure in the third and fourth quartile had 28.8% and 35.7% greater risk of a death, respectively, than regions located in the first two quartiles. CONCLUSION: Although it is possible that there are biological mechanisms that explain, at least partially, the association between long-term exposure to air pollutants and COVID-19, we hypothesize that the spatial spread of COVID-19 in Catalonia is attributed to the different ease with which some people, the hosts of the virus, have infected others. That facility depends on the heterogeneous distribution at a small area level of variables such as population density, poor housing and the mobility of its residents, for which exposure to pollutants has been a surrogate.