Long-term exposure to ambient air pollution and the incidence of SARS-CoV-2 infections in Italy : The EpiCovAir study
BACKGROUND: after the outbreak of the SARS-CoV-2 pandemic in 2020, several waves of pandemic cases have occurred in Italy. The role of air pollution has been hypothesized and investigated in several studies. However, to date, the role of chronic exposure to air pollutants in increasing incidence of SARS-CoV-2 infections is still debated.
OBJECTIVES: to investigate the association between long-term exposure to air pollutants and the incidence of SARS-CoV-2 infections in Italy.
DESIGN: a satellite-based air pollution exposure model with 1-km2 spatial resolution for entire Italy was applied and 2016-2019 mean population-weighted concentrations of particulate matter < 10 micron (PM10), PM <2.5 micron (PM2.5), and nitrogen dioxide (NO2) was calculated to each municipality as estimates of chronic exposures. A principal component analysis (PCA) approach was applied to 50+ area-level covariates (geography and topography, population density, mobility, population health, socioeconomic status) to account for the major determinants of the spatial distribution of incidence rates of SARS-CoV-2 infection. Detailed information was further used on intra- and inter-municipal mobility during the pandemic period. Finally, a mixed longitudinal ecological design with the study units consisting of individual municipalities in Italy was applied. Generalized negative binomial models controlling for age, gender, province, month, PCA variables, and population density were estimated.
SETTING AND PARTICIPANTS: individual records of diagnosed SARS-2-CoV-2 infections in Italy from February 2020 to June 2021 reported to the Italian Integrated Surveillance of COVID-19 were used.
MAIN OUTCOME MEASURES: percentage increases in incidence rate (%IR) and corresponding 95% confidence intervals (95% CI) per unit increase in exposure.
RESULTS: 3,995,202 COVID-19 cases in 7,800 municipalities were analysed (total population: 59,589,357 inhabitants). It was found that long-term exposure to PM2.5, PM10, and NO2 was significantly associated with the incidence rates of SARS-CoV-2 infection. In particular, incidence of COVID-19 increased by 0.3% (95%CI 0.1%-0.4%), 0.3% (0.2%-0.4%), and 0.9% (0.8%-1.0%) per 1 μg/m3 increment in PM2.5, PM10 and NO2, respectively. Associations were higher among elderly subjects and during the second pandemic wave (September 2020-December 2020). Several sensitivity analyses confirmed the main results. The results for NO2 were especially robust to multiple sensitivity analyses.
CONCLUSIONS: evidence of an association between long-term exposure to ambient air pollutants and the incidence of SARS-CoV-2 infections in Italy was found.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:47 |
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| Enthalten in: |
Epidemiologia e prevenzione - 47(2023), 3 vom: 25. Mai, Seite 125-136 |
| Sprache: |
Italienisch |
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| Weiterer Titel: |
Esposizione a lungo termine a inquinamento dell’aria ambiente e incidenza di infezioni di SARS-CoV-2 in Italia: lo studio EpiCovAir |
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| Beteiligte Personen: |
Ranzi, Andrea [VerfasserIn] |
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| Links: |
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| Themen: |
Air Pollutants |
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| Anmerkungen: |
Date Completed 10.05.2023 Date Revised 30.06.2023 published: Print Citation Status MEDLINE |
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| doi: |
10.19191/EP23.3.A605.025 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM356574423 |
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| 245 | 1 | 0 | |a Long-term exposure to ambient air pollution and the incidence of SARS-CoV-2 infections in Italy |b The EpiCovAir study |
| 246 | 3 | 3 | |a Esposizione a lungo termine a inquinamento dell’aria ambiente e incidenza di infezioni di SARS-CoV-2 in Italia: lo studio EpiCovAir |
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| 500 | |a Date Completed 10.05.2023 | ||
| 500 | |a Date Revised 30.06.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND: after the outbreak of the SARS-CoV-2 pandemic in 2020, several waves of pandemic cases have occurred in Italy. The role of air pollution has been hypothesized and investigated in several studies. However, to date, the role of chronic exposure to air pollutants in increasing incidence of SARS-CoV-2 infections is still debated | ||
| 520 | |a OBJECTIVES: to investigate the association between long-term exposure to air pollutants and the incidence of SARS-CoV-2 infections in Italy | ||
| 520 | |a DESIGN: a satellite-based air pollution exposure model with 1-km2 spatial resolution for entire Italy was applied and 2016-2019 mean population-weighted concentrations of particulate matter < 10 micron (PM10), PM <2.5 micron (PM2.5), and nitrogen dioxide (NO2) was calculated to each municipality as estimates of chronic exposures. A principal component analysis (PCA) approach was applied to 50+ area-level covariates (geography and topography, population density, mobility, population health, socioeconomic status) to account for the major determinants of the spatial distribution of incidence rates of SARS-CoV-2 infection. Detailed information was further used on intra- and inter-municipal mobility during the pandemic period. Finally, a mixed longitudinal ecological design with the study units consisting of individual municipalities in Italy was applied. Generalized negative binomial models controlling for age, gender, province, month, PCA variables, and population density were estimated | ||
| 520 | |a SETTING AND PARTICIPANTS: individual records of diagnosed SARS-2-CoV-2 infections in Italy from February 2020 to June 2021 reported to the Italian Integrated Surveillance of COVID-19 were used | ||
| 520 | |a MAIN OUTCOME MEASURES: percentage increases in incidence rate (%IR) and corresponding 95% confidence intervals (95% CI) per unit increase in exposure | ||
| 520 | |a RESULTS: 3,995,202 COVID-19 cases in 7,800 municipalities were analysed (total population: 59,589,357 inhabitants). It was found that long-term exposure to PM2.5, PM10, and NO2 was significantly associated with the incidence rates of SARS-CoV-2 infection. In particular, incidence of COVID-19 increased by 0.3% (95%CI 0.1%-0.4%), 0.3% (0.2%-0.4%), and 0.9% (0.8%-1.0%) per 1 μg/m3 increment in PM2.5, PM10 and NO2, respectively. Associations were higher among elderly subjects and during the second pandemic wave (September 2020-December 2020). Several sensitivity analyses confirmed the main results. The results for NO2 were especially robust to multiple sensitivity analyses | ||
| 520 | |a CONCLUSIONS: evidence of an association between long-term exposure to ambient air pollutants and the incidence of SARS-CoV-2 infections in Italy was found | ||
| 650 | 4 | |a English Abstract | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a COVID-19 incidence | |
| 650 | 4 | |a NO2 | |
| 650 | 4 | |a PM2.5 | |
| 650 | 4 | |a air pollution | |
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| 650 | 7 | |a S7G510RUBH |2 NLM | |
| 650 | 7 | |a Air Pollutants |2 NLM | |
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| 700 | 1 | |a Stafoggia, Massimo |e verfasserin |4 aut | |
| 700 | 1 | |a Giannini, Simone |e verfasserin |4 aut | |
| 700 | 1 | |a Ancona, Carla |e verfasserin |4 aut | |
| 700 | 1 | |a Bella, Antonino |e verfasserin |4 aut | |
| 700 | 1 | |a Cattani, Giorgio |e verfasserin |4 aut | |
| 700 | 1 | |a Pezzotti, Patrizio |e verfasserin |4 aut | |
| 700 | 1 | |a Iavarone, Ivano |e verfasserin |4 aut | |
| 700 | 0 | |a EpiCovAir Study Group |e verfasserin |4 aut | |
| 700 | 1 | |a Ancona, Carla |e investigator |4 oth | |
| 700 | 1 | |a Bauleo, Lisa |e investigator |4 oth | |
| 700 | 1 | |a Nobile, Federica |e investigator |4 oth | |
| 700 | 1 | |a Stafoggia, Massio |e investigator |4 oth | |
| 700 | 1 | |a Andrianou, Xanthi |e investigator |4 oth | |
| 700 | 1 | |a Bella, Antonino |e investigator |4 oth | |
| 700 | 1 | |a Gagliardi, Roberta |e investigator |4 oth | |
| 700 | 1 | |a Giustini, Marco |e investigator |4 oth | |
| 700 | 1 | |a Iavarone, Ivano |e investigator |4 oth | |
| 700 | 1 | |a Urdiales, Alberto Mateo |e investigator |4 oth | |
| 700 | 1 | |a Minelli, Giada |e investigator |4 oth | |
| 700 | 1 | |a Pasetto, Roberto |e investigator |4 oth | |
| 700 | 1 | |a Pezzotti, Patrizio |e investigator |4 oth | |
| 700 | 1 | |a Soggiu, Eleonora |e investigator |4 oth | |
| 700 | 1 | |a Vescio, Maria Fenicia |e investigator |4 oth | |
| 700 | 1 | |a Avenoso, Domenico |e investigator |4 oth | |
| 700 | 1 | |a Baldini, Marco |e investigator |4 oth | |
| 700 | 1 | |a Di Biagio, Katiuscia |e investigator |4 oth | |
| 700 | 1 | |a Barbiero, Fabiano |e investigator |4 oth | |
| 700 | 1 | |a Cattani, Giorgio |e investigator |4 oth | |
| 700 | 1 | |a Finocchiaro, Giovanni |e investigator |4 oth | |
| 700 | 1 | |a Galosi, Alessandra |e investigator |4 oth | |
| 700 | 1 | |a Di Giosa, Alessandro |e investigator |4 oth | |
| 700 | 1 | |a Fuser, Simonetta |e investigator |4 oth | |
| 700 | 1 | |a Giannini, Simone |e investigator |4 oth | |
| 700 | 1 | |a Ranzi, Andrea |e investigator |4 oth | |
| 700 | 1 | |a Guzzetta, Giorgio |e investigator |4 oth | |
| 700 | 1 | |a Minichilli, Fabrizio |e investigator |4 oth | |
| 700 | 1 | |a Moirano, Giovenale |e investigator |4 oth | |
| 700 | 1 | |a Richiardi, Lorenzo |e investigator |4 oth | |
| 700 | 1 | |a Mussin, Mauro |e investigator |4 oth | |
| 700 | 1 | |a Nannavecchia, Anna Maria |e investigator |4 oth | |
| 700 | 1 | |a Pastore, Tiziano |e investigator |4 oth | |
| 700 | 1 | |a Serinelli, Maria |e investigator |4 oth | |
| 700 | 1 | |a Stortini, Michele |e investigator |4 oth | |
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