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Air pollution in relation to COVID-19 morbidity and mortality: A large population-based cohort study in Catalonia, Spain (COVAIR-CAT)

Principal Investigator: 
,

Barcelona Institute for Global Health (ISGlobal), Spain

This study will test whether long- or short-term exposure to air pollution increases the risk of COVID-19 hospital admissions or mortality and identify vulnerable subgroups among 6 million residents of Catalonia, Spain. The investigators will link air pollution exposures to residents’ addresses and inpatient and outpatient electronic medical records.

Funded under
Status: 
Ongoing
Abstract

There are wide disparities between and within countries in the health burden from COVID-19, and much observed heterogeneity remains poorly understood. Exposure to air pollution may contribute to these differences as it is an important risk factor for several non-communicable diseases that increase vulnerability to COVID-19. Understanding whether the role of air pollution in COVID-19 related health outcomes is different from its role in the wider suite of respiratory infections is essential for identifying public health priorities.

Our overarching objective is to test whether long or short-term exposure to air pollution increases the risk of COVID-19 hospital admissions or mortality and to identify vulnerable subgroups in the general population of Catalonia, Spain, a region that continues to face a high COVID-19 health burden. Our specific aims are to test whether: 1) long-term exposure to air pollution is associated with COVID-19 hospital admission or mortality; 2) short-term exposure to air pollution is associated with COVID-19 hospital admission or mortality following COVID-19 diagnosis; 3) the influence of long- or short-term exposure to air pollution on COVID-19 outcomes differs according to individual-level socioeconomic and demographic factors, comorbidities, area-level socioeconomic factors, or other environmental exposures; and 4) the influence of long-term air pollution exposure on COVID-19 hospital admissions and mortality differs from that for respiratory infections not due to SARS-COV-2 infection.

We will use data linkage of electronic health records to construct a large, population-based cohort covering nearly the full population of Catalonia. By leveraging, individual-level data from primary care, hospital admissions, laboratory testing, and other registries, we will follow all adult individuals registered in the public health system of Catalonia in 2015 (n=6 million). This data linkage allows us to identify individuals from first diagnosis of COVID-19 through to hospital admission and death during the period March to December 2020. Geocoded residential addresses will be linked to modeled particulate matter (PM10, PM10-2.5, PM2.5, PM2.5 absorbance), oxides of nitrogen, and ozone developed through previous projects as well as measurements from the monitoring network. Individual and area-level covariate data will be used for confounder adjustment and to identify vulnerable subgroups. We will also leverage a range of data sources to adjust for the spatio-temporal dynamics of the COVID-19 epidemic. We will use semi-parametric hazard models with time-varying covariates to quantify associations between long- and short-term air pollution and COVID-19 hospital admission and mortality.

Our project will generate new, practical knowledge related to the intersection of two major public health challenges: air pollution and COVID-19. By leveraging detailed, individual-level health and covariate data and state-of-the art models of exposure, COVAIR-CAT can shed light on the potential for air quality control to contribute to prevention of severe COVID-19 outcomes. Our project directly addresses the focus area from RFA-20-1B regarding susceptibility factors by using individual-level data to quantify the association between long- and short-term exposure to air pollution and COVID-19 hospital admission and mortality, and investigating potential effect modification in well powered epidemiological analyses.