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.

Advances of microfluidic lung chips for assessing atmospheric pollutants exposure.

Atmospheric pollutants, including particulate matters, nanoparticles, bioaerosols, and some chemicals, have posed serious threats to the environment and the human's health. The lungs are the responsible organs for providing the interface betweenthecirculatory system and the external environment, where pollutant particles can deposit or penetrate into bloodstream circulation. Conventional studies to decipher the mechanismunderlying air pollution and human health are quite limited, due to the lack of reliable models that can reproduce in vivo features of lung tissues after pollutants exposure. In the past decade, advanced near-to-native lung chips, combining cell biology with bioengineered technology, present a new strategy for atmospheric pollutants assessment and narrow the gap between 2D cell culture and in vivo animal models. In this review, the key features of artificial lung chips and the cutting-edge technologies of the lung chip manufacture are introduced. The recent progresses of lung chip technologies for atmospheric pollutants exposure assessment are summarized and highlighted. We further discuss the current challenges and the future opportunities of the development of advanced lung chips and their potential utilities in atmospheric pollutants associated toxicity testing and drug screening.

Long-term impacts of non-occupational wildfire exposure on human health: A systematic review.

The intensity and frequency of wildfires is increasing globally. The systematic review of the current evidence on long-term impacts of non-occupational wildfire exposure on human health has not been performed yet. To provide a systematic review and identify potential knowledge gaps in the current evidence of long-term impacts of non-occupational exposure to wildfire smoke and/or wildfire impacts on human health. We conducted a systematic search of the literature via MEDLINE, Embase and Scopus from the database inception to July 05, 2022. References from the included studies and relevant reviews were also considered. The Newcastle-Ottawa Scale (NOS) and a validated quality assessment framework were used to evaluate the quality of observational studies. Study results were synthesized descriptively. A total of 36 studies were included in our systematic review. Most studies were from developed countries (11 in Australia, 9 in Canada, 7 in the United States). Studies predominantly focused on mental health (21 studies, 58.33%), while evidence on long-term impacts of wildfire exposure on health outcomes other than mental health is limited. Current evidence indicated that long-term impacts of non-occupational wildfire exposure were associated with mortality (COVID-19 mortality, cardiovascular disease mortality and acute myocardial disease mortality), morbidity (mainly respiratory diseases), mental health disorders (mainly posttraumatic stress disorder), shorter height of children, reduced lung function and poorer general health status. However, no significant associations were observed for long-term impacts of wildfire exposure on child mortality and respiratory hospitalizations. The population-based high-quality evidence with quantitative analysis on this topic is still limited. Future well-designed studies considering extensive wildfire smoke air pollutants (e.g., particulate matter, ozone, nitrogen oxides) and estimating risk coefficient values for extensive health outcomes (e.g., mortality, morbidity) are warranted to fill current knowledge gaps.

Long-term air pollution exposure and COVID-19 case-severity: An analysis of individual-level data from Switzerland.

Several studies are pointing out that exposure to elevated air pollutants could contribute to increased COVID-19 mortality. However, literature on the associations between air pollution exposure and COVID-19 severe morbidity is rather sparse. In addition, the majority of the studies used an ecological study design and were applied in regions with rather high air pollution levels. Here, we study the differential effects of long-term exposure to air pollution on severe morbidity and mortality risks from COVID-19 in various population subgroups in Switzerland, a country known for clean air. We perform individual-level analyses using data covering the first two major waves of COVID-19 between February 2020 and May 2021. High-resolution maps of particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations were produced for the 6 years preceding the pandemic using Bayesian geostatistical models. Air pollution exposure for each patient was measured by the long-term average concentration across the municipality of residence. The models were adjusted for the effects of individual characteristics, socio-economic, health-system, and climatic factors. The variables with an important association to COVID-19 case-severity were identified using Bayesian spatial variable selection. The results have shown that the individual-level characteristics are important factors related to COVID-19 morbidity and mortality in all the models. Long-term exposure to air pollution appears to influence the severity of the disease only when analyzing data during the first wave; this effect is attenuated upon adjustment for health-system related factors during the entire study period. Our findings suggest that the burden of air pollution increased the risks of COVID-19 in Switzerland during the first wave of the pandemic, but not during the second wave, when the national health system was better prepared.

The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America.

BACKGROUND: Air pollution is speculated to increase the risks of COVID-19 spread, severity, and mortality. OBJECTIVES: We systematically reviewed studies investigating the relationship between air pollution and COVID-19 cases, non-fatal severity, and mortality in North America and Europe. METHODS: We searched PubMed, Web of Science, and Scopus for studies investigating the effects of harmful pollutants, including particulate matter with diameter ≤2.5 or 10 µm (PM2.5 or PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO), on COVID-19 cases, severity, and deaths in Europe and North America through to June 19, 2021. Articles were included if they quantitatively measured the relationship between exposure to air pollution and COVID-19 health outcomes. RESULTS: From 2,482 articles screened, we included 116 studies reporting 355 separate pollutant-COVID-19 estimates. Approximately half of all evaluations on incidence were positive and significant associations (52.7%); for mortality the corresponding figure was similar (48.1%), while for non-fatal severity this figure was lower (41.2%). Longer-term exposure to pollutants appeared more likely to be positively associated with COVID-19 incidence (63.8%). PM2.5, PM10, O3, NO2, and CO were most strongly positively associated with COVID-19 incidence, while PM2.5 and NO2 with COVID-19 deaths. All studies were observational and most exhibited high risk of confounding and outcome measurement bias. DISCUSSION: Air pollution may be associated with worse COVID-19 outcomes. Future research is needed to better test the air pollution-COVID-19 hypothesis, particularly using more robust study designs and COVID-19 measures that are less prone to measurement error and by considering co-pollutant interactions.

Towards understanding respiratory particle transport and deposition in the human respiratory system: Effects of physiological conditions and particle properties.

Fly ash is a common solid residue of incineration plants and poses a great environmental concern because of its toxicity upon inhalation exposure. The inhalation health impacts of fly ash is closely related to its transport and deposition in the human respiratory system which warrants significant research for health guideline setting and inhalation exposure protection. In this study, a series of fly ash transport and deposition experiments have been carried out in a bifurcation airway model by optical aerosol sampling analysis. Three types of fly ash samples of different morphologies were tested and their respiratory deposition and transport processes were compared. The deposition efficiencies were calculated and relevant transport dynamics mechanisms were discussed. The influences of physiological conditions such as breathing rate, duration, and fly ash physical properties (size, morphology, and specific surface area) were investigated. The deposition characteristics of respiratory particles containing SARS-CoV-2 has also been analyzed, which could further provide some guidance on COVID-19 prevention. The results could potentially serve as a basis for setting health guidelines and recommending personal respiratory protective equipment for fly ash handlers and people who are in the high exposure risk environment for COVID-19 transmission.

Air quality in Germany as a contributing factor to morbidity from COVID-19.

BACKGROUND: The SARS-CoV-2 virus has been spreading in Germany since January 2020, with regional differences in incidence, morbidity, and mortality. Long-term exposure to air pollutants as nitrogen dioxide (NO2), nitrogen monoxide (NO), ozone (O3), and particulate matter (<10 µm PM10, <2.5 µm PM2.5) has a negative impact on respiratory functions. We analyze the association between long-term air pollution and the outcome of SARS-CoV-2 infections in Germany. METHODS: We conducted an observational study in Germany on county-level, investigating the association between long-term (2010-2019) air pollutant exposure (European Environment Agency, AirBase data set) and COVID-19 incidence, morbidity, and mortality rate during the first outbreak of SARS-CoV-2 (open source data Robert Koch Institute). We used negative binominal models, including adjustment for risk factors (age, sex, days since first COVID-19 case, population density, socio-economic and health parameters). RESULTS: After adjustment for risk factors in the tri-pollutant model (NO2, O3, PM2.5) an increase of 1 µg/m³ NO2 was associated with an increase of the need for intensive care due to COVID-19 by 4.2% (95% CI 1.011-1.074), and mechanical ventilation by 4.6% (95% CI 1.010-1.084). A tendency towards an association of NO2 with COVID-19 incidence was indicated, as the results were just outside of the defined statistical significance (+1.6% (95% CI 1.000-1.032)). Long-term annual mean NO2 level ranged from 4.6 µg/m³ to 32 µg/m³. CONCLUSIONS: Our results indicate that long-term NO2 exposure may have increased susceptibility for COVID-19 morbidity in Germany. The results demonstrate the need to reduce ambient air pollution to improve public health.

Variation of pollution sources and health effects on air pollution before and during COVID-19 pandemic in Linfen, Fenwei Plain.

Stringent pollution control measures are generally applied to improve air quality, especially in the Spring Festival in China. Meanwhile, human activities are reduced significantly due to nationwide lockdown measures to curtail the COVID-19 spreading in 2020. Herein, to better understand the influence of control measures and meteorology on air pollution, this study compared the variation of pollution source and their health risk during the 2019 and 2020 Spring Festival in Linfen, China. Results revealed that the average concentration of PM2.5 in 2020 decreased by 39.0% when compared to the 2019 Spring Festival. Organic carbon (OC) and SO42- were the primary contributor to PM2.5 with the value of 19.5% (21.1%) and 23.5% (25.5%) in 2019 (2020) Spring Festival, respectively. Based on the positive matrix factorization (PMF) model, six pollution sources of PM2.5 were indicated. Vehicle emissions (VE) had the maximum reduction in pollution source concentration (28.39 µg· m-3), followed by dust fall (DF) (11.47 µg· m-3), firework burning (FB) (10.39 µg· m-3), coal combustion (CC) (8.54 µg· m-3), and secondary inorganic aerosol (SIA) (3.95 µg· m-3). However, the apportionment concentration of biomass burning (BB) increased by 78.7%, indicating a significant increase in biomass combustion under control measures. PAHs-lifetime lung cancer risk (ILCR) of VE, CC, FB, BB, and DF, decreased by 44.6%, 43.2%, 34.1%, 21.3%, and 2.0%, respectively. Additionally, the average contribution of meteorological conditions on PM2.5 in 2020 increased by 20.21% compared to 2019 Spring Festival, demonstrating that meteorological conditions played a crucial role in located air pollution. This study revealed that the existing control measures in Linfen were efficient to reduce air pollution and health risk, whereas more BB emissions were worthy of further attention. Furthermore, the result was conducive to developing more effective control measures and putting more attention into unfavorable meteorological conditions in Linfen.

Gastrointestinal tissue as a "new" target of pollution exposure.

Airborne pollution has become a leading cause of global death in industrialized cities and the exposure to environmental pollutants has been demonstrated to have adverse effects on human health. Among the pollutants, particulate matter (PM) is one of the most toxic and although its exposure has been more commonly correlated with respiratory diseases, gastrointestinal (GI) complications have also been reported as a consequence to PM exposure. Due to its composition, PM is able to exert on intestinal mucosa both direct damaging effects, (by reaching it either via direct ingestion of contaminated food and water or indirect inhalation and consequent macrophagic mucociliary clearance) and indirect ones via generation of systemic inflammation. The relationship between respiratory and GI conditions is well described by the lung-gut axis and more recently, has become even clearer during coronavirus disease 2019 (COVID-19) pandemic, when respiratory symptoms were associated with gastrointestinal conditions. This review aims at pointing out the mechanisms and the models used to evaluate PM induced GI tract damage.

Effects of meteorological factors and air pollutants on the incidence of COVID-19 in South Korea.

Air pollution and meteorological factors can exacerbate susceptibility to respiratory viral infections. To establish appropriate prevention and intervention strategies, it is important to determine whether these factors affect the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, this study examined the effects of sunshine, temperature, wind, and air pollutants including sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), particulate matter ≤2.5 µm (PM2.5), and particulate matter ≤10 µm (PM10) on the age-standardized incidence ratio of coronavirus disease (COVID-19) in South Korea between January 2020 and April 2020. Propensity score weighting was used to randomly select observations into groups according to whether the case was cluster-related, to reduce selection bias. Multivariable logistic regression analyses were used to identify factors associated with COVID-19 incidence. Age 60 years or over (odds ratio [OR], 1.29; 95% CI, 1.24-1.35), exposure to ambient air pollutants, especially SO2 (OR, 5.19; 95% CI, 1.13-23.9) and CO (OR, 1.17; 95% CI, 1.07-1.27), and non-cluster infection (OR, 1.28; 95% CI, 1.24-1.32) were associated with SARS-CoV-2 infection. To manage and control COVID-19 effectively, further studies are warranted to confirm these findings and to develop appropriate guidelines to minimize SARS-CoV-2 transmission.

Role of air pollutants mediated oxidative stress in respiratory diseases.

Airborne particulate (PM) components from fossil fuel combustion can induce oxidative stress initiated by reactive oxygen species (ROS) that are strongly correlated with airway inflammation and asthma. A valid biomarker of airway inflammation is fractionated exhaled nitric oxide (FENO). The oxidative potential of PM2.5 can be evaluated with the dithiothreitol (DTT) dosage, which represents both ROS chemically produced and intracellular ROS of macrophages. This correlates with quality indicators of the internal environment and ventilation strategies such as dilution and removal of airborne contaminants.

Exposure to particulate matter: Direct and indirect role in the COVID-19 pandemic.

Knowing the transmission factors and the natural environment that favor the spread of a viral infection is crucial to stop outbreaks and develop effective preventive strategies. This work aims to evaluate the role of Particulate Matter (PM) in the COVID-19 pandemic, focusing especially on that of PM as a vector for SARS-CoV-2. Exposure to PM has been related to new cases and to the clinical severity of people infected by SARS-CoV-2, which can be explained by the oxidative stress and the inflammatory response generated by these particles when entering the respiratory system, as well as by the role of PM in the expression of ACE-2 in respiratory cells in human hosts. In addition, different authors have detected SARS-CoV-2 RNA in PM sampled both in outdoor and indoor environments. The results of various studies lead to the hypothesis that the aerosols emitted by an infected person could be deposited in other suspended particles, sometimes of natural but especially of anthropogenic origin, that form the basal PM. However, the viability of the virus in PM has not yet been demonstrated. Should PM be confirmed as a vector of transmission, prevention strategies ought to be adapted, and PM sampling in outdoor environments could become an indicator of viral load in a specific area.

Role of angiotensin-converting enzyme 2 in fine particulate matter-induced acute lung injury.

Fine particulate matter (PM2.5) pollution poses significant health concerns worldwide and can cause respiratory diseases. However, how it causes health problems is still poorly understood. Angiotensin-converting enzyme (ACE)2 is a terminal carboxypeptidase implicated in the functions of renin-angiotensin system (RAS) and plays a crucial role in the control of lung inflammation. To investigate whether ACE2 functions in PM2.5-induced lung inflammation, wild-type (WT) C57BL/6J mice and ACE2 knock-out (KO) mice were intratracheally instilled with PBS or PM2.5 suspension for 3 consecutive days, respectively. The concentrations of cytokines in bronchoalveolar lavage fluid (BALF) were determined by ELISA. The expression of ACE2 and ACE and activation of inflammatory signaling pathways in lung tissues were evaluated by immunofluorescence staining and Western blotting. We found that PM2.5 exposure increased ACE2 expression. Loss of ACE2 significantly elevated the levels of total proteins, total cells, and the concentrations of MCP-1, IL-1ß in BALF after PM2.5 challenge. Additionally, loss of ACE2 enhanced lung pathologies, airway resistance, and inflammatory signaling activation. Collectively, loss of ACE2 exacerbates PM2.5-induced acute lung injury in mice.

Exposure to air pollution is associated with congenital anomalies in the population born by in vitro fertilization.

BACKGROUND: Congenital anomalies (CAs) are the leading causes for children's disabilities and mortalities worldwide. The associations between air pollution and CAs are not fully characterized in fetuses born by in vitro fertilization (IVF) who are at high risk of congenital anomalies. METHODS: We conducted a cross-sectional study including 16,971 IVF cycles from three hospitals in Hebei Province, China, 2014-2019. Air quality data was obtained from 149 air monitoring stations. Individual average daily concentrations of PM2.5, PM10, NO2, SO2, CO, and O3 were estimated by spatiotemporal kriging method. Exposure windows were divided into 5: preantral follicle period, antral follicle period, germinal period, embryonic period and early fetal period. Logistic generalized estimating equations were used to estimate the associations between air pollutants and overall or organ-system specific congenital anomalies. Negative control exposure method was used to detect and reduce bias of estimation. RESULTS: We found increasing levels of PM2.5 and PM10 were associated with higher risk of overall congenital anomalies during early fetal period, equating gestation 10-12 weeks (OR: 1.05, 95% CI: 1.02-1.09, p = 0.013 for a 10 µg/m3 increase of PM2.5; OR: 1.03, 95% CI: 1.01-1.06, p = 0.021 for a 10 µg/m3 increase of PM10). Cleft lip and cleft palate were associated with PM10 in germinal period and early fetal period. The CAs of eye, ear, face and neck were related to CO in preantral follicle stage. We did not find an association between chromosome abnormalities and air pollution exposure. CONCLUSIONS: We concluded that ambient air pollution was a risk factor for congenital anomalies in the fetuses conceived through IVF, especially exposure in early fetal period.

The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model.

The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM2.5) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India. This study aims to address this knowledge gap by investigating the nexus between air pollution and COVID-19 in the ten most affected Indian states using daily observations from 9th March to September 20, 2020. The study has used the newly developed Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag (NPARDL) model for asymmetric analysis. Empirical results illustrate an asymmetric relationship between PM2.5 and COVID-19 cases. More precisely, a 1% change in the positive shocks of PM2.5 increases the COVID-19 cases by 0.439%. Besides, the estimates of individual states expose the heterogeneous effects of PM2.5 on COVID-19. The asymmetric causality test of Hatemi-J's (2011) also suggests that the positive shocks on PM2.5 Granger-cause positive shocks on COVID19 cases. Research findings indicate that air pollution is the root cause of this outbreak; thus, the government should recognize this channel and implement robust policy guidelines to control the spread of environmental pollution.

Ambient air pollution and COVID-19 incidence during four 2020-2021 case surges.

BACKGROUND: Air pollution exposure may make people more vulnerable to COVID-19 infection. However, previous studies in this area mostly focused on infection before May 2020 and long-term exposure. OBJECTIVE: To assess both long-term and short-term exposure to air pollution and COVID-19 incidence across four case surges from 03/1/2020 to 02/28/2021. METHODS: The cohort included 4.6 million members from a large integrated health care system in southern California with comprehensive electronic medical records (EMR). COVID-19 cases were identified from EMR. Incidence of COVID-19 was computed at the census tract-level among members. Prior 1-month and 1-year averaged air pollutant levels (PM2.5, NO2, and O3) at the census tract-level were estimated based on hourly and daily air quality data. Data analyses were conducted by each wave: 3/1/2020-5/31/2020, 6/1/202-9/30/2020, 10/1/2020-12/31/2020, and 1/1/2021-2/28/2021 and pooled across waves using meta-analysis. Generalized linear mixed effects models with Poisson distribution and spatial autocorrelation were used with adjustment for meteorological factors and census tract-level social and health characteristics. Results were expressed as relative risk (RR) per 1 standard deviation. RESULTS: The cohort included 446,440 COVID-19 cases covering 4609 census tracts. The pooled RRs (95% CI) of COVID-19 incidence associated with 1-year exposures to PM2.5, NO2, and O3 were 1.11 (1.04, 1.18) per 2.3 µg/m3,1.09 (1.02, 1.17) per 3.2 ppb, and 1.06 (1.00, 1.12) per 5.5 ppb respectively. The corresponding RRs (95% CI) associated with prior 1-month exposures were 1.11 (1.03, 1.20) per 5.2 µg/m3 for PM2.5, 1.09 (1.01, 1.17) per 6.0 ppb for NO2 and 0.96 (0.85, 1.08) per 12.0 ppb for O3. CONCLUSION: Long-term PM2.5 and NO2 exposures were associated with increased risk of COVID-19 incidence across all case surges before February 2021. Short-term PM2.5 and NO2 exposures were also associated. Our findings suggest that air pollution may play a role in increasing the risk of COVID-19 infection.

Air Pollution in Poland: A 2022 Narrative Review with Focus on Respiratory Diseases.

According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland. Thus, ambient air pollution and its detrimental health effects are a matter of immense importance in Poland. This narrative review aims to analyse current findings on air pollution and health in Poland, with a focus on respiratory diseases, including COVID-19, as well as the Poles' awareness of air pollution. PubMed, Scopus and Google Scholar databases were searched. In total, results from 71 research papers were summarized qualitatively. In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality rates, higher prevalence of respiratory diseases, including asthma, lung cancer and COVID-19 infections, reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The proximity of high traffic areas exacerbates respiratory health problems. People living in more polluted regions (south of Poland) and in the winter season have a higher level of air pollution awareness. There is an urgent need to reduce air pollution levels and increase public awareness of this threat. A larger number of multi-city studies are needed in Poland to consistently track the burden of diseases attributable to air pollution.

Association of Acute Respiratory Infections with Indoor Air Pollution from Biomass Fuel Exposure among Under-Five Children in Jimma Town, Southwestern Ethiopia.

Background: Most of the households in developing countries burn biomass fuel in traditional stoves with incomplete combustion that leads to high indoor air pollution and acute respiratory infections. Acute respiratory infection is the most common cause of under-five morbidity and mortality accounting for 2 million deaths worldwide and responsible for 18% of deaths among under-five children in Ethiopia. Although studies were done on acute respiratory infections, the majority of studies neither clinically diagnose respiratory infections nor use instant measurement of particulate matter. Methods: The community-based cross-sectional study design was employed among under-five children in Jimma town from May 21 to June 7, 2020. A total of 265 children through systematic random sampling were included in the study. The data were collected using a pretested semistructured questionnaire and laser pm 2.5 meter for indoor particulate matter concentration. Associations among factors were assessed through correlation analysis, and binary logistic regression was done to predict childhood acute respiratory infections. Variables with p-value less than 0.25 in bivariate regression were the candidate for the final multivariate logistic regression. Two independent sample t-tests were done to compare significant mean difference between concentrations of particulate matter. Results: Among 265 under-five children who were involved in the study, 179 (67.5%) were living in households that predominantly use biomass fuel. Prevalence of acute respiratory infections in the study area was 16%. Children living in households that use biomass fuel were four times more likely to develop acute respiratory infections than their counterparts (AOR: 4.348; 95% CI: 1.632, 11.580). The size of household was significantly associated with the prevalence of acute respiratory infections. Under-five children living in households that have a family size of six and greater had odds of 1.7 increased risk of developing acute respiratory infections than their counterparts (AOR: 1.7; 95% CI: 1.299, 2.212). The other factor associated with acute respiratory infection was separate kitchen; children living in households in which there were no separate kitchen were four times at increased risk of developing acute respiratory infection than children living in households which have separate kitchen (AOR: 4.591; 95% CI: 1.849, 11.402). The concentration of indoor particulate matter was higher in households using biomass fuel than clean fuel. There was statistically higher particulate matter concentration in the kitchen than living rooms (t = 4.509, p ≤ 0.001). Particulate matter 2.5 concentrations (µg/m3) of the households that had parental smoking were significantly higher than their counterparts (AOR: 20.224; 95% CI: 1.72, 12.58). Conclusion: There is an association between acute respiratory infections and biomass fuel usage among under-five children. Focusing on improved energy sources is essential to reduce the burden and assure the safety of children.

COVID-19 and Air Pollution: A Spatial Analysis of Particulate Matter Concentration and Pandemic-Associated Mortality in the US.

In 2019, a novel coronavirus, SARS-CoV-2, was first reported in Wuhan, China. The virus causes the disease commonly known as COVID-19, and, since its emergence, it has infected over 252 million individuals globally and taken the lives of over 5 million in the same time span. Primary research on SARS-CoV-2 and COVID-19 focused on understanding the biomolecular composition of the virus. This research has led to the development of multiple vaccines with great efficacy and antiviral treatments for the disease. The development of biomedical interventions has been crucial to combating this pandemic; additionally, environmental confounding variables that could have exacerbated the pandemic need further assessment. In this research study, we conducted a spatial analysis of particulate matter (PM) concentration and its association with COVID-19 mortality in the United States. Results of this study demonstrate a significant positive correlation between PM concentration levels and COVID-19 mortality; however, this does not necessarily imply a causal relationship. These results are consistent with similar studies in Italy and China, where significant COVID-19 cases and corresponding deaths were exhibited. Furthermore, maps of the data demonstrate clustering of COVID-19 mortality which suggest further investigation into the social determinants of health impacting the pandemic.

Negative-Binomial and quasi-poisson regressions between COVID-19, mobility and environment in São Paulo, Brazil.

Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to monitor quarantines and prevent the transmissions of SARS-CoV-2. In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in São Paulo, Brazil. We applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between RMI and COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 4 and 21 days, and 2) the association between COVID-19 and exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility. We found that an RMI of 45.28% results in 1212 cases (95% CI: 1189 to 1235) and 44 deaths (95% CI: 40 to 47). Increasing the isolation from 45.28% to 50% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 µg⋅m-³ of PM2.5 results in a risk of 1.140 (95% CI: 1.021 to 1.274) for cases and 1.086 (95% CI: 1.008 to 1.170) for deaths, while O3 produces a relative risk of 1.075 (95% CI: 1.006 to 1.150) for cases and 1.063 (95% CI: 1.006 to 1.124) for deaths, respectively. We compared our results with observations and literature review, finding well agreement. Policymakers can use such mobility indices as tools to control social distance activities. Spatial distancing is an important factor to control COVID-19, however, measuring face-mask usage would enhance the understanding the pandemic dynamic. Small increments of air pollution result in an increased number of COVID-19 cases and deaths.