Interactive Effects of Long-term Exposure to Air Pollutants on SARS-CoV-2 Infection and Severity: A Northern Italian Population-based Cohort Study.

Background: We examined interactions, to our knowledge not yet explored, between long-term exposures to particulate matter (PM 10 ) with nitrogen dioxide (NO 2 ) and ozone (O 3 ) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity and severity.

Methods: We followed 709,864 adult residents of Varese Province from 1 February 2020 until the first positive test, COVID-19 hospitalization, or death, up to 31 December 2020. We estimated residential annual means of PM 10 , NO 2 , and O 3 in 2019 from chemical transport and random-forest models.

Long-term residential exposure to air pollution and risk of chronic respiratory diseases in Italy: The BIGEPI study.

Long-term exposure to air pollution has adverse respiratory health effects. We investigated the cross-sectional relationship between residential exposure to air pollutants and the risk of suffering from chronic respiratory diseases in some Italian cities. In the BIGEPI project, we harmonised questionnaire data from two population-based studies conducted in 2007-2014.

Association between short-term exposure to air pollutants and cause-specific daily mortality in Italy. A nationwide analysis.

Background/aim: Daily air pollution has been linked with mortality from urban studies. Associations in rural areas are still unclear and there is growing interest in testing the role that air pollution has on other causes of death. This study aims to evaluate the association between daily air pollution and cause-specific mortality in all 8092 Italian municipalities.

A nationwide study of air pollution from particulate matter and daily hospitalizations for respiratory diseases in Italy.

Background/aim: The relationship between air pollution and respiratory morbidity has been widely addressed in urban and metropolitan areas but little is known about the effects in non-urban settings. Our aim was to assess the short-term effects of PM10 and PM2.5 on respiratory admissions in the whole country of Italy during 2006-2015.

Short-Term Effects of Air Pollution on Cardiovascular Hospitalizations in the Pisan Longitudinal Study.

Air pollution effects on cardiovascular hospitalizations in small urban/suburban areas have been scantly investigated. Such effects were assessed among the participants in the analytical epidemiological survey carried out in Pisa and Cascina, Tuscany, Italy (2009-2011). Cardiovascular hospitalizations from 1585 subjects were followed up (2011-2015).

Impact of different exposure models and spatial resolution on the long-term effects of air pollution.

Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging.

A multi-city air pollution population exposure study: Combined use of chemical-transport and random-Forest models with dynamic population data.

Cities are severely affected by air pollution. Local emissions and urban structures can produce large spatial heterogeneities. We aim to improve the estimation of NO, O, PM and PM concentrations in 6 Italian metropolitan areas, using chemical-transport and machine learning models, and to assess the effect on population exposure by using information on urban population mobility.

Estimating Daily PM and PM over Italy Using an Ensemble Model.

Spatiotemporally resolved particulate matter (PM) estimates are essential for reconstructing long and short-term exposures in epidemiological research. Improved estimates of PM and PM concentrations were produced over Italy for 2013-2015 using satellite remote-sensing data and an ensemble modeling approach. The following modeling stages were used: (1) missing values of the satellite-based aerosol optical depth (AOD) product were imputed using a spatiotemporal land-use random-forest (RF) model incorporating AOD data from atmospheric ensemble models; (2) daily PM estimations were produced using four modeling approaches: linear mixed effects, RF, extreme gradient boosting, and a chemical transport model, the flexible air quality regional model.