Long-term exposure to air pollution and severe COVID-19 in Catalonia: a population-based cohort study.

The association between long-term exposure to ambient air pollutants and severe COVID-19 is uncertain. We followed 4,660,502 adults from the general population in 2020 in Catalonia, Spain. Cox proportional models were fit to evaluate the association between annual averages of PM2.5, NO2, BC, and O3 at each participant's residential address and severe COVID-19. Higher exposure to PM2.5, NO2, and BC was associated with an increased risk of COVID-19 hospitalization, ICU admission, death, and hospital length of stay. An increase of 3.2 µg/m3 of PM2.5 was associated with a 19% (95% CI, 16-21) increase in hospitalizations. An increase of 16.1 µg/m3 of NO2 was associated with a 42% (95% CI, 30-55) increase in ICU admissions. An increase of 0.7 µg/m3 of BC was associated with a 6% (95% CI, 0-13) increase in deaths. O3 was positively associated with severe outcomes when adjusted by NO2. Our study contributes robust evidence that long-term exposure to air pollutants is associated with severe COVID-19.

Critical air pollutant assessments and health effects attributed to PM2.5 during and after COVID-19 lockdowns in Iran: application of AirQ+ models.

Objectives: The aim of this study was to evaluate changes in air quality index (AQI) values before, during, and after lockdown, as well as to evaluate the number of hospitalizations due to respiratory and cardiovascular diseases attributed to atmospheric PM2.5 pollution in Semnan, Iran in the period from 2019 to 2021 during the COVID-19 pandemic. Methods: Daily air quality records were obtained from the global air quality index project and the US Environmental Protection Administration (EPA). In this research, the AirQ+ model was used to quantify health consequences attributed to particulate matter with an aerodynamic diameter of <2.5 µm (PM2.5). Results: The results of this study showed positive correlations between air pollution levels and reductions in pollutant levels during and after the lockdown. PM2.5 was the critical pollutant for most days of the year, as its AQI was the highest among the four investigated pollutants on most days. Mortality rates from chronic obstructive pulmonary disease (COPD) attributed to PM2.5 in 2019-2021 were 25.18% in 2019, 22.55% in 2020, and 22.12% in 2021. Mortality rates and hospital admissions due to cardiovascular and respiratory diseases decreased during the lockdown. The results showed a significant decrease in the percentage of days with unhealthy air quality in short-term lockdowns in Semnan, Iran with moderate air pollution. Natural mortality (due to all-natural causes) and other mortalities related to COPD, ischemic heart disease (IHD), lung cancer (LC), and stroke attributed to PM2.5 in 2019-2021 decreased. Conclusion: Our results support the general finding that anthropogenic activities cause significant health threats, which were paradoxically revealed during a global health crisis/challenge.

Prognostic Factors for Covid-19 on Admission Profile and Air Pollutants.

It has been reported that the severity and lethality of Covid-19 are associated with coexisting underlying diseases (hypertension, diabetes, etc.) and cardiovascular diseases (coronary artery disease, atrial fibrillation, heart failure, etc.) that increase with age, but environmental exposure such as air pollutants may also be a risk factor for mortality. In this study, we investigated patient characteristics at admission and prognostic factors of air pollutants in Covid-19 patients using a machine learning (random forest) prediction model. Age, Photochemical oxidant concentration one month prior to admission, and level of care required were shown to be highly important for the characteristics, while the cumulative concentrations of air pollutants SPM, NO2, and PM2.5 one year prior to admission were the most important characteristics for patients aged 65 years and older, suggesting the influence of long-term exposure.

[Long-term exposure to ambient air pollution and the incidence of SARS-CoV-2 infections in Italy: The EpiCovAir study]. / Esposizione a lungo termine a inquinamento dell'aria ambiente e incidenza di infezioni di SARS-CoV-2 in Italia: lo studio EpiCovAir.

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.

Indoor air quality in a training centre used for sports practice.

Background: One of the measures for controlling the coronavirus disease 2019 (COVID-19) pandemic was the mass closure of gyms. This measure leads us to determine the differences between indoor and outdoor air quality. That is why the objective of this study was to analyse the indoor air quality of a sports centre catering to small groups and rehabilitation. Methods: The study was conducted in a single training centre, where 26 measurements were taken in two spaces (indoors and outdoors). The air quality index, temperature, relative humidity, total volatile compounds, carbon monoxide, ozone, formaldehyde, carbon dioxide, and particulate matter were measured indoors and outdoors using the same protocol and equipment. These measurements were taken twice, once in the morning and once in the afternoon, with all measurements made at the same time, 10 am and 6 pm, respectively. Additionally, four determinations of each variable were collected during each shift, and the number of people who had trained in the room and the number of trainers were counted. Results: In the different variables analysed, the results show that CO2 and RH levels are higher indoors than outdoors in both measurement shifts. Temperatures are higher outside than inside and, in the evening, than in the morning. TVOC, AQI and PM show less variation, although they are higher outdoors in the morning. CO is highest indoors. HCHO levels are almost negligible and do not vary significantly, except for a slight increase in the afternoon outside. Ozone levels are not significant. All the variables showed practically perfect reliability in all the measurements, except for ozone measured outside in the morning. On the other hand, the variables exhibit variations between indoors and outdoors during the morning and afternoon, except for the three types of PM. Also, the data show that all the main variables measured inside the sports training centre are similar between morning and afternoon. However, outside, temperature, relative humidity and HCHO levels show significant differences between morning and afternoon while no differences are observed for the other variables. Conclusion: The indoor air quality of the training centre assessed was good and met current regulations; some of its components even exhibited better levels than fresh air. This article is the first to measure indoor air quality in a sports training centre catering to rehabilitation and small groups.

Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review and meta-analysis.

Ecological evidence links ambient particulate matter ≤2.5 mm (PM2.5) and the rate of COVID-19 infections, severity, and deaths. However, such studies are unable to account for individual-level differences in major confounders like socioeconomic status and often rely on imprecise measures of PM2.5. We conducted a systematic review of case-control and cohort studies, which rely on individual-level data, searching Medline, Embase, and the WHO COVID-19 database up to 30 June 2022. Study quality was evaluated using the Newcastle-Ottawa Scale. Results were pooled with a random effects meta-analysis, with Egger's regression, funnel plots, and leave-one-out/trim-and-fill sensitivity analyses to account for publication bias. N = 18 studies met inclusion criteria. A 10 µg/m3 increase in PM2.5 was associated with 66 % (95 % CI: 1.31-2.11) greater odds of COVID-19 infection (N = 7) and 127 % (95 % CI: 1.41-3.66) odds of severe illness (hospitalisation, ICU admission, or requiring respiratory support) (N = 6). Pooled mortality results (N = 5) indicated increased deaths due to PM2.5 but were non-significant (OR 1.40; 0.94 to 2.10). Most studies were rated "good" quality (14/18 studies), though there were numerous methodological issues; few used individual-level data to adjust for socioeconomic status (4/18 studies), instead using area-based indicators (11/18 studies) or no such adjustments (3/18 studies). Most severity (9/10 studies) and mortality studies (5/6 studies) were based on people already diagnosed COVID-19, potentially introducing collider bias. There was evidence of publication bias in studies of infection (p = 0.012) but not severity (p = 0.132) or mortality (p = 0.100). While methodological limits and evidence of bias require cautious interpretation of the findings, we found compelling evidence that PM2.5 increases the risk of COVID-19 infection and severe disease, and weaker evidence of an increase in mortality risk.

Avoidable mortality due to long-term exposure to PM2.5 in Colombia 2014-2019.

OBJECTIVE: To compare estimates of spatiotemporal variations of surface PM2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM2.5 annual mean at municipality level. METHODS: We retrieved PM2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM2.5 concentration over the current mean annual national standard of 25 µg/m3 and projected standard of 15 µg/m3. RESULTS: Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m3 compared to a mean bias of 4,7 µg/m3 from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM2.5 exposure over 25 and 15 µg/m3 were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m3 were 2,381 years. CONCLUSION: Comparison of two global air quality models for estimating surface PM2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

Temperature and particulate matter as environmental factors associated with seasonality of influenza incidence - an approach using Earth observation-based modeling in a health insurance cohort study from Baden-Württemberg (Germany).

BACKGROUND: Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. OBJECTIVES: We examined influences of medium-term residential exposure to fine particulate matter (PM2.5), NO2, SO2, air temperature and precipitation on influenza incidence. METHODS: To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. RESULTS: In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM2.5 and NO2. Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 µg/m3 to 15.98 µg/m3. CONCLUSIONS: Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.

Exposure to air pollution and hospitalization due to COVID-19 in São José dos Campos, Brazil.

The association between exposure to air pollutants and respiratory diseases is well known. This study aimed to identify the association between this exposure and hospitalizations for COVID-19 in São José dos Campos, SP, a medium-sized city, between April 2020 and April 2021. Hospitalization data, concerning code B34.2, was supplied by DATASUS, and data concerning pollutants and climate variables were supplied by CETESB. Cases were quantified by sex, age, length of hospital stay in days, and type of discharge, whether hospital discharge or death. The negative binomial regression model was chosen. Estimates were produced for the relative risk (RR) of significant exposure to pollutants (P≤0.05) with a 10 µg/m3 increase of pollutant, as well as for excess hospitalizations. There were 1873 hospitalizations, with a daily average of 4.7 (±3.8), ranging from zero to 21: 716 deaths (38.2%) were recorded, 1065 admissions were men, and women were less susceptible (OR=0.82). The average age of women was higher than that of men; in cases of death, men were older than women; discharged patients were younger. All the above variables were significant. The risk of ozone exposure was higher and more significant in Lag 2, and the risk of nitrogen dioxide exposure was high in Lag 3, which was the period of the highest increase in hospitalizations, at 11.3%. The findings of this study, the first conducted in Brazil, corroborate the results of studies conducted in other centers.

Association between long-term air pollution exposure and COVID-19 mortality in Latin America.

Recent studies have shown a relationship between air pollution and increased vulnerability and mortality due to COVID-19. Most of these studies have looked at developed countries. This study examines the relationship between long-term exposure to air pollution and COVID-19-related deaths in four countries of Latin America that have been highly affected by the pandemic: Brazil, Chile, Colombia, and Mexico. Our results suggest that an increase in long-term exposure of 1 µg/m3 of fine particles is associated with a 2.7 percent increase in the COVID-19 mortality rate. This relationship is found primarily in municipalities of metropolitan areas, where urban air pollution sources dominate, and air quality guidelines are usually exceeded. By focusing the analysis on Latin America, we provide a first glimpse on the role of air pollution as a risk factor for COVID-19 mortality within a context characterized by weak environmental institutions, limited health care capacity and high levels of inequality.

Public health in Global South: effect of environmental pollutant PM2.5 on the incidence and mortality of SARS-CoV-2 in Karachi, Lahore, and Islamabad.

OBJECTIVE: Environmental pollution has undoubtedly been established as a planetary, intergenerational, and existential threat to global human health and safety. Environmental pollution is adversely affecting the world, mainly the countries where human health is not a priority aspect, and this has been exacerbated due to the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), and pandemic is known as "COVID pandemic". This study investigates the association of environmental pollutants, particulate matter (PM2.5), with SARS-CoV-2 daily cases and deaths in Karachi, Lahore, and Islamabad, Pakistan, presenting the perspectives from the Global South. MATERIALS AND METHODS: The day-to-day PM2.5 levels were recorded from the metrological website, Real-Time Air Quality Index-AQI. The corresponding data on the COVID cases and deaths in Karachi, Lahore, and Islamabad were obtained from August 1, 2020, to September 30, 2021, from the Health Ministry and National Command Operations Centre Pakistan. RESULTS: The mean values for PM2.5 in Karachi were 110.4±46.2; in Lahore 174.0±83.2; and in Islamabad 107.1±40.0. The COVID-19 mean daily cases in Karachi were 538.9±446.6; Lahore 398.3±403.1; and Islamabad 212.2±187.6; and mean daily deaths in Karachi were 9.2±8.3; Lahore 9.3±9.7; and Islamabad 1.8±1.8. The results further depicted that the SARS-CoV-2 cases were 2.86 times higher in Karachi and 1.4 times higher in Lahore than in Islamabad. Similarly, the SARS-CoV-2 deaths were 3.6 and 2.8 times higher in Karachi and Lahore, respectively, compared to Islamabad. CONCLUSIONS: The findings claim that cases and deaths augmented significantly along with PM2.5 levels. These empirical estimates demonstrate an association between PM2.5 and SARS-CoV-2 daily cases and deaths in the cities of the Global South. These findings can contribute to policy-making decisions about addressing air pollutants and climate concerns in developing countries and create an urgency to develop a strategy for minimizing environmental pollution. This study can also steer the actions needed to address the environmental problems in developing countries to improve public health and safety.

Substantial changes in Gaseous pollutants and health effects during COVID-19 in Delhi, India.

Background: Coronavirus disease has affected the entire population worldwide in terms of physical and environmental consequences. Therefore, the current study demonstrates the changes in the concentration of gaseous pollutants and their health effects during the COVID-19 pandemic in Delhi, the national capital city of India. Methodology: In the present study, secondary data on gaseous pollutants such as nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ammonia (NH3), and ozone (O3) were collected from the Central Pollution Control Board (CPCB) on a daily basis. Data were collected from January 1, 2020, to September 30, 2020, to determine the relative changes (%) in gaseous pollutants for pre-lockdown, lockdown, and unlockdown stages of COVID-19. Results: The current findings for gaseous pollutants reveal that concentration declined in the range of 51%-83% (NO), 40%-69% (NOx), 31%-60% (NO2), and 25%-40% (NH3) during the lockdown compared to pre-lockdown period, respectively. The drastic decrease in gaseous pollutants was observed due to restricted measures during lockdown periods. The level of ozone was observed to be higher during the lockdown periods as compared to the pre-lockdown period. These gaseous pollutants are linked between the health risk assessment and hazard identification for non-carcinogenic. However, in infants (0-1 yr), Health Quotient (HQ) for daily and annual groups was found to be higher than the rest of the exposed group (toddlers, children, and adults) in all the periods. Conclusion: The air quality values for pre-lockdown were calculated to be "poor category to "very poor" category in all zones of Delhi, whereas, during the lockdown period, the air quality levels for all zones were calculated as "satisfactory," except for Northeast Delhi, which displayed the "moderate" category. The computed HQ for daily chronic exposure for each pollutant across the child and adult groups was more than 1 (HQ > 1), which indicated a high probability to induce adverse health outcomes.

Environmental Impacts on Infectious Disease: A Literature View of Epidemiological Evidence.

Background: This article summarises a session from the recent Pacific Basin Consortium for Environment and Health Focus meeting on Environmental Impacts on Infectious Disease. Objective: To provide an overview of the literature underpinning the presentations from this session. Methods: References used in developing the presentations were obtained from the presenters. Additional references were obtained from PubMed using key words from the presentations. Findings and Conclusions: The Hokkaido longitudinal children's study has found that exposure to chemicals in early life, such as persistent organic pollutants and per/polyfluorinated compounds, is associated with a range of immunological outcomes such as decreased cord blood IgE, otitis media, wheeze, increased risk of infections and higher risk of food allergy.Epidemiological evidence links exposure to poor air quality to increased severity and mortality of Covid-19 in many parts of the world. Most studies suggest that long-term exposure has a more marked effect than acute exposure.Components of air pollution, such as a newly described combustion product known as environmentally persistent free radicals, induce oxidative stress in exposed individuals. Individuals with genetic variations predisposing them to oxidative stress are at increased risk of adverse health effects from poor air quality.

Effects of Air Pollution on Chemosensory Dysfunction in COVID-19 Patients.

BACKGROUND: In some patients, coronavirus disease 2019 (COVID-19) is accompanied by loss of smell and taste, and this has been reportedly associated with exposure to air pollutants. This study investigated the relationship between the occurrence of chemosensory dysfunction in COVID-19 patients and air pollutant concentrations in Korea. METHODS: Information on the clinical symptom of chemosensory dysfunction, the date of diagnosis, residential area, age, and sex of 60,194 confirmed COVID-19 cases reported to the Korea Disease Control and Prevention Agency from January 20 to December 31, 2020 was collected. In addition, the daily average concentration of air pollutants for a week in the patients' residential area was collected from the Ministry of Environment based on the date of diagnosis of COVID-19. A binomial logistic regression model, using age and gender, standardized smoking rate, number of outpatient visits, 24-hour mean temperature and relative humidity at the regional level as covariates, was used to determine the effect of air pollution on chemosensory dysfunction. RESULTS: Symptoms of chemosensory dysfunction were most frequent among patients in their 20s and 30s, and occurred more frequently in large cities. The logistic analysis showed that the concentration of particulate matter 10 (PM10) and 2.5 (PM2.5) up to 2 days before the diagnosis of COVID-19 and the concentration of sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) at least 7 days before the diagnosis of COVID-19 affected the development of chemosensory dysfunction. In the logistic regression model adjusted for age, sex, standardized smoking rate, number of outpatient visits, and daily average temperature and relative humidity, it was found that an increase in the interquartile range of PM10, PM2.5, SO2, NO2, and CO on the day of diagnosis increased the incidence of chemosensory dysfunction 1.10, 1.10, 1.17, 1.31, and 1.19-fold, respectively. In contrast, the O3 concentration had a negative association with chemosensory dysfunction. CONCLUSION: High concentrations of air pollutants such as PM10, PM2.5, SO2, NO2, and CO on the day of diagnosis increased the risk of developing chemosensory dysfunction from COVID-19 infection. This result underscores the need to actively prevent exposure to air pollution and prevent COVID-19 infection. In addition, policies that regulate activities and products that create high amounts of harmful environmental wastes may help in promoting better health for all during COVID-19 pandemic.