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Machine learning reveals that prolonged exposure to air pollution is associated with SARS-CoV-2 mortality and infectivity in Italy.

ABSTRACT: Air pollution can increase the risk of respiratory diseases, enhancing the susceptibility to viral and bacterial infections. Some studies suggest that small air particles facilitate the spread of viruses and also of the new coronavirus, besides the direct person-to-person contagion. However, the effects of the exposure to particulate matter and other contaminants on SARS-CoV-2 has been poorly explored. Here we examined the possible reasons why the new coronavirus differently impacted on Italian regional and provincial populations. With the help of artificial intelligence, we studied the importance of air pollution for mortality and positivity rates of the SARS-CoV-2 outbreak in Italy. We discovered that among several environmental, health, and socio-economic factors, air pollution and fine particulate matter (PM2.5), as its main component, resulted as the most important predictors of SARS-CoV-2 effects. We also found that the emissions from industries, farms, and road traffic - in order of importance - might be responsible for more than 70% of the deaths associated with SARS-CoV-2 nationwide. Given the major contribution played by air pollution (much more important than other health and socio-economic factors, as we discovered), we projected that, with an increase of 5-10% in air pollution, similar future pathogens may inflate the epidemic toll of Italy by 21-32% additional cases, whose 19-28% more positives and 4-14% more deaths. Our findings, demonstrating that fine-particulate (PM2.5) pollutant level is the most important factor to predict SARS-CoV-2 effects that would worsen even with a slight decrease of air quality, highlight that the imperative of productivity before health and environmental protection is, indeed, a short-term/small-minded resolution.

SUBMITTER: Cazzolla Gatti R

PROVIDER: S-EPMC7442434 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Machine learning reveals that prolonged exposure to air pollution is associated with SARS-CoV-2 mortality and infectivity in Italy.

Cazzolla Gatti Roberto R Velichevskaya Alena A Tateo Andrea A Amoroso Nicola N Monaco Alfonso A

Environmental pollution (Barking, Essex : 1987) 20200821

Air pollution can increase the risk of respiratory diseases, enhancing the susceptibility to viral and bacterial infections. Some studies suggest that small air particles facilitate the spread of viruses and also of the new coronavirus, besides the direct person-to-person contagion. However, the effects of the exposure to particulate matter and other contaminants on SARS-CoV-2 has been poorly explored. Here we examined the possible reasons why the new coronavirus differently impacted on Italian ...[more]

PMID: 32882464

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Project description:Data-driven machine learning methods present an opportunity to simultaneously assess the impact of multiple air pollutants on health outcomes. The goal of this study was to apply a two-stage, data-driven approach to identify associations between air pollutant exposure profiles and children's cognitive skills. Data from 6900 children enrolled in the Early Childhood Longitudinal Study, Birth Cohort, a national study of children born in 2001 and followed through kindergarten, were linked to estimated concentrations of 104 ambient air toxics in the 2002 National Air Toxics Assessment using ZIP code of residence at age 9 months. In the first-stage, 100 regression trees were learned to identify ambient air pollutant exposure profiles most closely associated with scores on a standardized mathematics test administered to children in kindergarten. In the second-stage, the exposure profiles frequently predicting lower math scores were included within linear regression models and adjusted for confounders in order to estimate the magnitude of their effect on math scores. This approach was applied to the full population, and then to the populations living in urban and highly-populated urban areas. Our first-stage results in the full population suggested children with low trichloroethylene exposure had significantly lower math scores. This association was not observed for children living in urban communities, suggesting that confounding related to urbanicity needs to be considered within the first-stage. When restricting our analysis to populations living in urban and highly-populated urban areas, high isophorone levels were found to predict lower math scores. Within adjusted regression models of children in highly-populated urban areas, the estimated effect of higher isophorone exposure on math scores was -1.19 points (95% CI -1.94, -0.44). Similar results were observed for the overall population of urban children. This data-driven, two-stage approach can be applied to other populations, exposures and outcomes to generate hypotheses within high-dimensional exposure data.

Project description:BackgroundThe role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear.ObjectivesThe study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy.MethodsWe obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10μm (PM10), PM with aerodynamic diameter ≤2.5μm (PM2.5), and nitrogen dioxide (NO2) to each municipality (n=7,800) as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units.ResultsWe analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per 1 μg/m3 increment in PM2.5, PM10, and NO2, respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated ∼8% COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines.DiscussionWe found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.

Project description:Zinc (Zn) is a major elemental component of respirable ambient particulate matter (PM) detected often at alarming levels in urban air. Exposure to PM has been widely associated with increased cardiovascular morbidity and mortality, however, it is not known what components or sources of PM are causative. We recently demonstrated that long-term episodic inhalation of combustion PM, having similar amount of Zn found in urban PM, caused myocardial lesions in rats. We further demonstrated that a single pulmonary exposure to Zn at high concentration is associated with disturbances in cardiac mitochondrial function, ion channel regulation, calcium homeostasis, and cell signaling. Therefore, in this study we investigated the role of PM-associated Zn in cardiac injury using multiple exposure scenarios. Male Wistar-Kyoto (WKY) rats of 12-14 wks age were intratracheally exposed (once per wk x 8 or16 wks) to either (1) saline (control); (2) PM having no soluble Zn; (3) combustion PM suspension containing 14.5 ug/mg water-soluble Zn at high and (4) low dose levels, (5) the aqueous fraction of this suspension devoid of solid insoluble particulate fraction (14.5 ug/mg soluble Zn), or (6) Zn sulfate. Zn concentrations were identical in groups 3, 5 and 6. Pulmonary toxicity was apparent in all exposure groups when compared to saline as determined by recovery of cells in bronchoalveolar lavage fluid. Long-term exposure to PM with or without soluble Zn, or Zn sulfate caused distinct myocardial lesions characterized by subepicardial and randomly distributed myocardial inflammation, degeneration, and fibrosis. The lesion severity was higher in those groups receiving Zn PM. Because cardiac mitochondria are likely the primary target of inhaled metal or other absorbed PM components, we analyzed mitochondrial DNA damage using QPCR and found that all exposure groups except those exposed to PM without Zn caused variable degree of damage. Aconitase activity, sensitive to inhibition by oxidative stress was inhibited slightly but significantly in rats receiving zinc sulfate. Although modest, microarray (Affymetrix) analysis revealed expression changes in the heart reflective of effects on cell signaling, inflammation/oxidative stress, mitochondrial fatty acid metabolisms and cell cycle regulation in rats exposed to zinc sulfate. However, these changes were minimal following exposure to PM devoid of soluble metals. We demonstrate that episodic subchronic pulmonary exposure to zinc sulfate causes cardiac injury and mitochondrial DNA damage. Thus, water-soluble PM-associated zinc may be one of the PM components responsible for cardiovascular morbidity. Experiment Overall Design: Group 1 received Saline to serve as a control. Group 2 received Mount St. Helenâs ash, which does not contain any water-soluble zinc or other metals such that we can delineate any cardiac effect secondary to pulmonary deposition of these particles as these fine mode particles themselves are not likely to translocate to the heart. Group 3 received whole saline suspension of the same fugitive oil combustion particle sample used in the previous study, which contained insoluble components plus water-soluble zinc (Kodavanti et al., 2003; 14.5 ug/mg zinc) and also a small amount of water-soluble nickel (3.0 Âµg/mg). Elemental composition of this PM is comparable to Ottawa urban PM (Kodavanti et al., 2003). Group 4 also received same particle sample but at half the dose than group 3. Group 5 received saline-soluble or leachable fraction of PM-HD devoid of any solid material but contained soluble components including zinc and nickel. And, group 6 received zinc sulfate at concentration that was present in groups 3 or 5. This design allowed us to test if cardiac injury in rats was due to leached of zinc or solid particles. There were 4 replicates per treatment group.

Project description:The US Environmental Protection Agency is required to reexamine its National Ambient Air Quality Standards (NAAQS) every 5 years, but evidence of mortality risk is lacking at air pollution levels below the current daily NAAQS in unmonitored areas and for sensitive subgroups.To estimate the association between short-term exposures to ambient fine particulate matter (PM2.5) and ozone, and at levels below the current daily NAAQS, and mortality in the continental United States.Case-crossover design and conditional logistic regression to estimate the association between short-term exposures to PM2.5 and ozone (mean of daily exposure on the same day of death and 1 day prior) and mortality in 2-pollutant models. The study included the entire Medicare population from January 1, 2000, to December 31, 2012, residing in 39?182 zip codes.Daily PM2.5 and ozone levels in a 1-km × 1-km grid were estimated using published and validated air pollution prediction models based on land use, chemical transport modeling, and satellite remote sensing data. From these gridded exposures, daily exposures were calculated for every zip code in the United States. Warm-season ozone was defined as ozone levels for the months April to September of each year.All-cause mortality in the entire Medicare population from 2000 to 2012.During the study period, there were 22?433?862 million case days and 76?143?209 control days. Of all case and control days, 93.6% had PM2.5 levels below 25 ?g/m3, during which 95.2% of deaths occurred (21?353?817 of 22?433?862), and 91.1% of days had ozone levels below 60 parts per billion, during which 93.4% of deaths occurred (20?955?387 of 22?433?862). The baseline daily mortality rates were 137.33 and 129.44 (per 1 million persons at risk per day) for the entire year and for the warm season, respectively. Each short-term increase of 10 ?g/m3 in PM2.5 (adjusted by ozone) and 10 parts per billion (10-9) in warm-season ozone (adjusted by PM2.5) were statistically significantly associated with a relative increase of 1.05% (95% CI, 0.95%-1.15%) and 0.51% (95% CI, 0.41%-0.61%) in daily mortality rate, respectively. Absolute risk differences in daily mortality rate were 1.42 (95% CI, 1.29-1.56) and 0.66 (95% CI, 0.53-0.78) per 1 million persons at risk per day. There was no evidence of a threshold in the exposure-response relationship.In the US Medicare population from 2000 to 2012, short-term exposures to PM2.5 and warm-season ozone were significantly associated with increased risk of mortality. This risk occurred at levels below current national air quality standards, suggesting that these standards may need to be reevaluated.

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Machine learning reveals that prolonged exposure to air pollution is associated with SARS-CoV-2 mortality and infectivity in Italy.

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Machine learning reveals that prolonged exposure to air pollution is associated with SARS-CoV-2 mortality and infectivity in Italy.

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