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.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models.

BACKGROUND: A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE: We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS: Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS: The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 µg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 µg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 µg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION: In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.

[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.

Environmental factors and their impact on the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in numerous cases of illness and death worldwide. Research has shown that there are associations between transmission, as well as the severity of SARS-CoV­2 (severe acute respiratory syndrome coronavirus 2) infections, and various environmental factors. For example, air pollution with particulate matter is thought to play a crucial role, and both climatic and geographical aspects must be considered. Furthermore, environmental conditions such as industry and urban lifestyle have a significant impact on air quality and thus on health aspects of the population. In this regard, other factors such as chemicals, microplastics, and diet also critically impact health, including respiratory and cardiovascular diseases. Overall, the COVID-19 pandemic has highlighted how closely health and the environment are linked. This review discusses the impact of environmental factors on the COVID-19 pandemic.

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.

Long-term exposure to air pollution and COVID-19 severity: A cohort study in Greater Manchester, United Kingdom.

Exposure to outdoor air pollution may affect incidence and severity of coronavirus disease 2019 (COVID-19). In this retrospective cohort based on patient records from the Greater Manchester Care Records, all first COVID-19 cases diagnosed between March 1, 2020 and May 31, 2022 were followed until COVID-19 related hospitalization or death within 28 days. Long-term exposure was estimated using mean annual concentrations of particulate matter with diameter ≤2.5 µm (PM2.5), ≤10 µm (PM10), nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2) and benzene (C6H6) in 2019 using a validated air pollution model developed by the Department for Environment, Food and Rural Affairs (DEFRA). The association of long-term exposure to air pollution with COVID-19 hospitalization and mortality were estimated using multivariate logistic regression models after adjusting for potential individual, temporal and spatial confounders. Significant positive associations were observed between PM2.5, PM10, NO2, SO2, benzene and COVID-19 hospital admissions with odds ratios (95% Confidence Intervals [CI]) of 1.27 (1.25-1.30), 1.15 (1.13-1.17), 1.12 (1.10-1.14), 1.16 (1.14-1.18), and 1.39 (1.36-1.42), (per interquartile range [IQR]), respectively. Significant positive associations were also observed between PM2.5, PM10, SO2, or benzene and COVID-19 mortality with odds ratios (95% CI) of 1.39 (1.31-1.48), 1.23 (1.17-1.30), 1.18 (1.12-1.24), and 1.62 (1.52-1.72), per IQR, respectively. Individuals who were older, overweight or obese, current smokers, or had underlying comorbidities showed greater associations between all pollutants of interest and hospital admission, compared to the corresponding groups. Long-term exposure to air pollution is associated with developing severe COVID-19 after a positive SARS-CoV-2 infection, resulting in hospitalization or death.

Impact of ambient air pollution on physical activity and sedentary behavior in children.

BACKGROUND: Exposure to air pollution has become a serious environmental issue affecting children's health and health-related behavior in China. Previous studies have focused on the associations between air pollution and physical activity among adults; however, few have examined the relationship between air pollution and health-related behavior among children, which are particularly susceptible population subgroups. The present study aims to examine the impact of air pollution on daily physical activity (PA) and sedentary behavior (SB) among children in China. METHODS: PA and SB data were collected by actiGraph accelerometers for eight consecutive days. PA and SB data from 206 children were matched to daily air pollution obtained from the Ministry of Environmental Protection of the People's Republic of China, including the average daily air quality index (AQI), PM2.5 (µg/m³), and PM10 (µg/m³). Associations were estimated using linear individual fixed-effect regressions. RESULTS: A 10-unit increase in daily AQI was associated with a reduction in daily PA by 5.94 (95% confidence interval [CI] = -8.79, -3.08) minutes of moderate to vigorous physical activity (MVPA) and 229.82 (95% CI = -345.35, -114.28) walking steps and an increase in daily SB by 15.77 (95% CI = 9.01, 22.53) minutes. A 10 µg/m³ increase in air pollution concentration in daily PM2.5 was associated with a reduction in daily PA by 7.51 (95% CI = -11.04, -3.97) minutes of MVPA, 295.69 (95% CI = -438.46, -152.92) walking steps and an increase in daily SB by 21.12 (95% CI = 12.77, 29.47) minutes. A 10 µg/m³ increase in air pollution concentration in daily PM10 was associated with a reduction in daily PA by 13.18 (95% confidence interval [CI] = -15.98, -10.37) minutes of MVPA, 518.34 (95% CI = -631.77, -404.91) walking steps and an increase in daily SB by 19.87 (95% CI = 13.10, 26.64) minutes. CONCLUSION: Air pollution may discourage physical activity and increase sedentary behavior among children. Policy interventions are needed to reduce air pollution and develop strategies to decrease risks to children's health.

Discussion about the Latest Findings on the Possible Relation between Air Particulate Matter and COVID-19.

Since SARS-CoV-2 was identified, the scientific community has tried to understand the variables that can influence its spread. Several studies have already highlighted a possible link between particulate matter (PM) and COVID-19. This work is a brief discussion about the latest findings on this topic, highlighting the gaps in the current results and possible tips for future studies. Based on the literature outcomes, PM is suspected to play a double role in COVID-19: a chronic and an acute one. The chronic role is related to the possible influence of long-term and short-term exposure to high concentrations of PM in developing severe forms of COVID-19, including death. The acute role is linked to the possible carrier function of PM in SARS-CoV-2. The scientific community seems sure that the inflammatory effect on the respiratory system of short-term exposure to a high concentration of PM, and other additional negative effects on human health in cases of longer exposure, increases the risk of developing a more severe form of COVID-19 in cases of contagion. On the contrary, the results regarding PM acting as a carrier of SARS-CoV-2 are more conflicting, especially regarding the possible inactivation of the virus in the environment, and no final explanation on the possible acute role of PM in the spread of COVID-19 can be inferred.

New determinants of mental health: the role of noise pollution. A narrative review.

Urbanisation processes and anthropogenic actions led to a significant increase in pollution levels, with relevant consequences on global health. In particular, noise pollution demonstrated an association with cardiovascular, metabolic, and respiratory diseases. Furthermore, increasing evidence underlined the possible role of air and noise pollution in the development of psychiatric disorders. In this narrative review, evidence concerning the relationship between noise pollution and the emergence of psychiatric symptoms or psychiatric disorders is summarised. After the literature search process was completed, 40 papers were included in the present review. The exposure to road-, rail-, and air- traffic represented a risk factor for the emergence of affective disorders. This could also be mediated by the occurrence of circadian rhythms disturbances or by noise annoyance and noise sensitivity, both influencing psychological well-being and health-related quality of life. Fewer studies concentrated on special populations, particularly pregnant women and children, for whom noise pollution was confirmed as a risk factor for psychopathology. The better clarification of the complex interaction between noise pollution and mental health may help to identify subjects at risk and targeting specific prevention and intervention strategies in the urban environment.

A Literature Review of the Effects of Air Pollution on COVID-19 Health Outcomes Worldwide: Statistical Challenges and Data Visualization.

Several peer-reviewed papers and reviews have examined the relationship between exposure to air pollution and COVID-19 spread and severity. However, many of the existing reviews on this topic do not extensively present the statistical challenges associated with this field, do not provide comprehensive guidelines for future researchers, and review only the results of a relatively small number of papers. We reviewed 139 papers, 127 of which reported a statistically significant positive association between air pollution and adverse COVID-19 health outcomes. Here, we summarize the evidence, describe the statistical challenges, and make recommendations for future research. To summarize the 139 papers with data from geographical locations around the world, we also present anopen-source data visualization tool that summarizes these studies and allows the research community to contribute evidence as new research papers are published.

The effect of air pollution on COVID-19 severity in a sample of patients with multiple sclerosis.

BACKGROUND AND PURPOSE: Some studies have shown that air pollution, often assessed by thin particulate matter with diameter below 2.5 µg/m3 (PM2.5), may contribute to severe COVID-19 courses, as well as play a role in the onset and evolution of multiple sclerosis (MS). However, the impact of air pollution on COVID-19 has never been explored specifically amongst patients with MS (PwMS). This retrospective observational study aims to explore associations between PM2.5 and COVID-19 severity amongst PwMS. METHODS: Data were retrieved from an Italian web-based platform (MuSC-19) which includes PwMS with COVID-19. PM2.5 2016-2018 average concentrations were provided by the Copernicus Atmospheric Monitoring Service. Italian patients inserted in the platform from 15 January 2020 to 9 April 2021 with a COVID-19 positive test were included. Ordered logistic regression models were used to study associations between PM2.5 and COVID-19 severity. RESULTS: In all, 1087 patients, of whom 13% required hospitalization and 2% were admitted to an intensive care unit or died, were included. Based on the multivariate analysis, higher concentrations of PM2.5 increased the risk of worse COVID-19 course (odds ratio 1.90; p = 0.009). CONCLUSIONS: Even if several other factors explain the unfavourable course of COVID-19 in PwMS, the role of air pollutants must be considered and further investigated.

Impacts of Wildfire Smoke and Air Pollution on a Pediatric Population with Asthma: A Population-Based Study.

Wildfires are increasing yearly in number and severity as a part of the evolving climate crisis. These fires are a significant source of air pollution, a common driver of flares in cardiorespiratory disease, including asthma, which is the most common chronic disease of childhood. Poorly controlled asthma leads to significant societal costs through morbidity, mortality, lost school and work time and healthcare utilization. This retrospective cohort study set in Calgary, Canada evaluates the relationship between asthma exacerbations during wildfire smoke events and equivalent low-pollution periods in a pediatric asthma population. Air pollution was based on daily average levels of PM2.5. Wildfire smoke events were determined by combining information from provincial databases and local monitors. Exposures were assumed using postal codes in the health record at the time of emergency department visits. Provincial claims data identified 27,501 asthma exacerbations in 57,375 children with asthma between 2010 to 2021. Wildfire smoke days demonstrated an increase in asthma exacerbations over the baseline (incidence rate ratio: 1.13; 95% CI: 1.02-1.24); this was not seen with air pollution in general. Increased rates of asthma exacerbations were also noted yearly in September. Asthma exacerbations were significantly decreased during periods of COVID-19 healthcare precautions.

The Relationship between the Transmission of Different SARS-CoV-2 Strains and Air Quality: A Case Study in China.

Coronavirus Disease 2019 (COVID-19) has been a global public health concern for almost three years, and the transmission characteristics vary among different virus variants. Previous studies have investigated the relationship between air pollutants and COVID-19 infection caused by the original strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is unclear whether individuals might be more susceptible to COVID-19 due to exposure to air pollutants, with the SARS-CoV-2 mutating faster and faster. This study aimed to explore the relationship between air pollutants and COVID-19 infection caused by three major SARS-CoV-2 strains (the original strain, Delta variant, and Omicron variant) in China. A generalized additive model was applied to investigate the associations of COVID-19 infection with six air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3). A positive correlation might be indicated between air pollutants (PM2.5, PM10, and NO2) and confirmed cases of COVID-19 caused by different SARS-CoV-2 strains. It also suggested that the mutant variants appear to be more closely associated with air pollutants than the original strain. This study could provide valuable insight into control strategies that limit the concentration of air pollutants at lower levels and would better control the spread of COVID-19 even as the virus continues to mutate.

Impact of air pollution on ischemic heart disease: Evidence, mechanisms, clinical perspectives.

Ambient air pollution, and especially particulate matter (PM) air pollution <2.5 µm in diameter (PM2.5), has clearly emerged as an important yet often overlooked risk factor for atherosclerosis and ischemic heart disease (IHD). In this review, we examine the available evidence demonstrating how acute and chronic PM2.5 exposure clinically translates into a heightened coronary atherosclerotic burden and an increased risk of acute ischemic coronary events. Moreover, we provide insights into the pathophysiologic mechanisms underlying PM2.5-mediated atherosclerosis, focusing on the specific biological mechanism through which PM2.5 exerts its detrimental effects. Further, we discuss about the possible mechanisms that explain the recent findings reporting a strong association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, increased PM2.5 exposure, and morbidity and mortality from IHD. We also address the possible mitigation strategies that should be implemented to reduce the impact of PM2.5 on cardiovascular morbidity and mortality, and underscoring the strong need of clinical trials demonstrating the efficacy of specific interventions (including both PM2.5 reduction and/or specific drugs) in reducing the incidence of IHD. Finally, we introduce the emerging concept of the exposome, highlighting the close relationship between PM2.5 and other environmental exposures (i.e.: traffic noise and climate change) in terms of common underlying pathophysiologic mechanisms and possible mitigation strategies.

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.

Air pollution and respiratory infections: the past, present, and future.

Air pollution levels across the globe continue to rise despite government regulations. The increase in global air pollution levels drives detrimental human health effects, including 7 million premature deaths every year. Many of these deaths are attributable to increased incidence of respiratory infections. Considering the COVID-19 pandemic, an unprecedented public health crisis that has claimed the lives of over 6.5 million people globally, respiratory infections as a driver of human mortality is a pressing concern. Therefore, it is more important than ever to understand the relationship between air pollution and respiratory infections so that public health measures can be implemented to ameliorate further morbidity and mortality. This article aims to review the current epidemiologic and basic science research on interactions between air pollution exposure and respiratory infections. The first section will present epidemiologic studies organized by pathogen, followed by a review of basic science research investigating the mechanisms of infection, and then conclude with a discussion of areas that require future investigation.