The Health of Firefighters Deployed to the Fort McMurray Fire: Lessons Learnt

Introduction: Firefighters were working in exceptionally difficult conditions during the Fort McMurray/Horse River fire in May 2016.Methods: From mid-May, we recruited firefighters from 13 fire services as they returned from the fire. In October 2016 we extended recruitment to all Alberta-based firefighters deployed to the fire. In December 2017–May 2018 we sent a first online follow-up: this concentrated on mental health supports. The second follow-up, in October 2018–January 2019, included screening scales for respiratory ill-health and PTSD. All three contacts included visual analogue scales for chest symptoms and the Hospital Anxiety and Depression Scale. We estimated exposure to PM2.5, and calculated an exposure mitigation index from reports of respiratory protective equipment (RPE).Results: We recruited 1,234 firefighters and examined the relation of respiratory symptoms to estimated particulate exposure. The relation was strong immediately post fire but weakened over time. We found less chest tightness and cough in those whose RPE in the first week mitigated exposure by at least 10%. We examined the relation between particulate exposure and mental ill-health from screening questionnaires and found those with high exposure (reflecting the ferocity of the fire) had poorer mental health scores. Firefighters reporting their “worst moment during the fire” was life threatening were more anxious at second follow-up. Overall both anxiety and depression scores increased at successive contacts, more so in those with mental ill-health recorded in physician billing records before the fire.Discussion: The results from this study overall suggest on-going fire-related health effects in a substantial minority of firefighters, similar to those reported in the longitudinal follow-up of firefighters after the collapse of the World Trade Centre. Self-reports of both respiratory symptoms and mental ill-health were strongly related, soon after the fire, to estimated particulate exposures. Anxiety increased over time since the fire in those who felt their life or safety had been threatened, underlining the need for ongoing support. Our conclusions about the benefits of rapid research relate particularly to the collection of biomarkers of exposure as quickly and widely as possible, and the establishment of a nominal list of participants before they are too widely dispersed.

Open Application of Statistical and Machine Learning Models to Explore the Impact of Environmental Exposures on Health and Disease: An Asthma Use Case

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical approaches, such as bivariate chi-square tests. We recently developed a method for using ICEES to generate multivariate tables for subsequent application of machine learning and statistical models. The objective of the present study was to use this approach to identify predictors of asthma exacerbations through the application of three multivariate methods: conditional random forest, conditional tree, and generalized linear model. Among seven potential predictor variables, we found five to be of significant importance using both conditional random forest and conditional tree: prednisone, race, airborne particulate exposure, obesity, and sex. The conditional tree method additionally identified several significant two-way and three-way interactions among the same variables. When we applied a generalized linear model, we identified four significant predictor variables, namely prednisone, race, airborne particulate exposure, and obesity. When ranked in order by effect size, the results were in agreement with the results from the conditional random forest and conditional tree methods as well as the published literature. Our results suggest that the open multivariate analytic capabilities provided by ICEES are valid in the context of an asthma use case and likely will have broad value in advancing open research in environmental and public health.

Woodsmoke particulates alter expression of antiviral host response genes in human nasal epithelial cells infected with SARS-CoV-2 in a sex-dependent manner

We have previously shown that exposure to particulate air pollution, both from natural and anthropogenic sources, alters gene expression in the airways and increases susceptibility to respiratory viral infection. Additionally, we have shown that woodsmoke particulates (WSP) affect responses to influenza in a sex-dependent manner. In the present study, we used human nasal epithelial cells (hNECs) from both sexes to investigate how particulate exposure could modulate gene expression in the context of SARS-CoV-2 infection. We used diesel exhaust particulate (DEP) as well as WSP derived from eucalyptus or red oak wood. HNECs were exposed to particulates at a concentration of 22 μg/cm2 for 2 h then immediately infected with SARS-CoV-2 at a MOI (multiplicity of infection) of 0.5. Exposure to particulates had no significant effects on viral load recovered from infected cells. Without particulate exposure, hNECs from both sexes displayed a robust upregulation of antiviral host response genes, though the response was greater in males. However, WSP exposure before infection dampened expression of genes related to the antiviral host response by 72 h post infection. Specifically, red oak WSP downregulated IFIT1, IFITM3, IFNB1, MX1, CCL3, CCL5, CXCL11, CXCL10, and DDX58, among others. After sex stratification of these results, we found that exposure to WSP prior to SARS-CoV-2 infection downregulated anti-viral gene expression in hNECs from females more so than males. These data indicate that WSP, specifically from red oak, alter virus-induced gene expression in a sex-dependent manner and potentially suppress antiviral host defense responses following SARS-CoV-2 infection.

Integrated Evaluation of Indoor Particulate Exposure: The VIEPI Project

Despite the progress made in recent years, reliable modeling of indoor air quality is still far from being obtained. This requires better chemical characterization of the pollutants and airflow physics included in forecasting tools, for which field observations conducted simultaneously indoors and outdoors are essential. The project “Integrated Evaluation of Indoor Particulate Exposure” (VIEPI) aimed at evaluating indoor air quality and exposure to particulate matter (PM) of humans in workplaces. VIEPI ran from February 2016 to December 2019 and included both numerical simulations and field campaigns carried out in universities and research environments located in urban and non-urban sites in the metropolitan area of Rome (Italy). VIEPI focused on the role played by micrometeorology and indoor airflow characteristics in determining indoor PM concentration. Short- and long-term study periods captured diurnal, weekly, and seasonal variability of airflow and PM concentration. Chemical characterization of PM10, including the determination of elements, ions, elemental carbon, organic carbon, and bioaerosol, was also carried out. Large differences in the composition of PM10 were detected between inside and outside as well as between different periods of the day and year. Indoor PM composition was related to the presence of people, to the season, and to the ventilation regime.

Effects of Home Particulate Air Filtration on Blood Pressure

Air pollution is a major contributor to cardiovascular morbidity and mortality. Fine particulate matter <2.5 µm in diameter may be a modifiable risk factor for hypertension. The benefits of in-home air filtration on systolic blood pressure (BP) and diastolic BP are unclear. To examine the effects of in-home personal air cleaner use on fine particulate exposure and BP, we queried PubMed, Web of Science, Cochrane Central Register, Inspec, and EBSCO GreenFILE databases for relevant clinical trials. Included studies were limited to nonsmoking participants in smoke-free homes with active or sham filtration on indoor fine particulate concentrations and changes in systolic and diastolic BP. Of 330 articles identified, 10 trials enrolling 604 participants who met inclusion criteria were considered. Over a median 13.5 days, there was a significant reduction of mean systolic BP by ≈4 mm Hg (−3.94 mm Hg [95% CI, −7.00 to −0.89]; P =0.01) but a nonsignificant difference in mean diastolic BP (−0.95 mm Hg [95% CI, −2.81 to 0.91]; P =0.32). Subgroup analyses indicated no heterogeneity of effect by age, level of particulate exposure, or study duration. Given the variation in study design, additional study is warranted to confirm and better quantify the observed benefits in systolic BP found with personal air cleaner use.