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ObjectivesTo investigate the association between long-term exposure to airborne pollutants and the incidence of SARS-CoV-2 up to March 2021 in a prospective study of residents in Varese city.MethodsCitizens of Varese aged ≥18 years as of 31 December 2019 were linked by residential address to 2018 average annual exposure to outdoor concentrations of PM2.5, PM10, NO2, NO and ozone modelled using the Flexible Air quality Regional Model (FARM) chemical transport model. Citizens were further linked to regional datasets for COVID-19 case ascertainment (positive nasopharyngeal swab specimens) and to define age, sex, living in a residential care home, population density and comorbidities. We estimated rate ratios and additional numbers of cases per 1 µg/m3 increase in air pollutants from single- and bi-pollutant Poisson regression models.ResultsThe 62 848 residents generated 4408 cases. Yearly average PM2.5 exposure was 12.5 µg/m3. Age, living in a residential care home, history of stroke and medications for diabetes, hypertension and obstructive airway diseases were independently associated with COVID-19. In single-pollutant multivariate models, PM2.5 was associated with a 5.1% increase in the rate of COVID-19 (95% CI 2.7% to 7.5%), corresponding to 294 additional cases per 100 000 person-years. The association was confirmed in bi-pollutant models; excluding subjects in residential care homes; and further adjusting for area-based indicators of socioeconomic level and use of public transportation. Similar findings were observed for PM10, NO2 and NO. Ozone was associated with a 2% decrease in disease rate, the association being reversed in bi-pollutant models.ConclusionsLong-term exposure to low levels of air pollutants, especially PM2.5, increased the incidence of COVID-19. The causality warrants confirmation in future studies; meanwhile, government efforts to further reduce air pollution should continue.

, Via Rubattino 54 -20134, Milano, Italy (Present address) 11 12 ABSTRACT 13 A hybrid modeling system (HMS) was developed to provide hourly concentrations at the urban 14 local scale. The system is based on the combination of a meteorological model (WRF), a chemical 15 and transport eulerian model (CAMx), which computes concentration levels over the regional 16 domains, and a lagrangian dispersion model (AUSTAL2000), accounting for dispersion phenomena 17 within the urban area due to local emission sources; a source apportionment algorithm is also 18 included in the HMS in order to avoid the double counting of local emissions. 19The HMS was applied over a set of nested domains, the innermost covering a 1.6x1.6 km 2 area in 20Milan city center with 20 m grid resolution, for NO X simulation in 2010. For this paper the 21 innermost domain was defined as "local", excluding usual definition of urban areas. WRF model 22 captured the overall evolution of the main meteorological features, except for some very stagnant 23 situations, thus influencing the subsequent performance of regional scale model CAMx. Indeed, 24CAMx was able to reproduce the spatial and temporal evolution of NO X concentration over the 25 regional domain, except a few episodes, when observed concentrations were higher than 100 ppb. 26The local scale model AUSTAL2000 provided high-resolution concentration fields that sensibly 27 mirrored the road and traffic pattern in the urban domain. Therefore, the first important outcome of 28 the work is that the application of the hybrid modelling system allowed a thorough and consistent 29 description of urban air quality. This result represents a relevant starting point for future evaluation 30 of pollution exposure within an urban context. 31However, the overall performance of the HMS did not provide remarkable improvements with 32 respect to stand-alone CAMx at the two only monitoring sites in Milan city center. HMS results 33 were characterized by a smaller average bias, that improved about 6-8 ppb corresponding to 12-34 13% of the observed concentration, but by a lower correlation, that worsened around 1-3% (e.g. 35 from 0.84 to 0.81 at Senato site), due to the concentration peaks produced by AUSTAL2000 during 36 nighttime stable conditions. Additionally, the HMS results showed that it was unable to correctly 37 take into account some local scale features (e.g. urban canyon effects), pointing out that the 38 emission spatialization and time modulation criteria, especially those from road traffic, need further 39 improvement. 40Nevertheless, a second important outcome of the work is that some of the most relevant 41 discrepancies between modeled and observed concentrations were not related to the horizontal 42 resolution of the dispersion models but to larger scale meteorological features not captured by the 43 meteorological model, especially during winter period. Finally, the estimated contribution of the 44 local emission sources accounted on the annual average for about 25-30% of the computed 45 concen...