Time series analysis of fine particulate matter and asthma reliever dispensations in populations affected by forest fires

Fine Particulate Matter, Its Constituents, and Spontaneous Preterm Birth

Importance

The associations of exposure to fine particulate matter (PM2.5) and its constituents with spontaneous preterm birth (sPTB) remain understudied. Identifying subpopulations at increased risk characterized by socioeconomic status and other environmental factors is critical for targeted interventions.

Objective

To examine associations of PM2.5 and its constituents with sPTB.

Design, Setting, and Participants

This population-based retrospective cohort study was conducted from 2008 to 2018 within a large integrated health care system, Kaiser Permanente Southern California. Singleton live births with recorded residential information of pregnant individuals during pregnancy were included. Data were analyzed from December 2023 to March 2024.

Exposures

Daily total PM2.5 concentrations and monthly data on 5 PM2.5 constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) in California were assessed, and mean exposures to these pollutants during pregnancy and by trimester were calculated. Exposures to total green space, trees, low-lying vegetation, and grass were estimated using street view images. Wildfire-related exposure was measured by the mean concentration of wildfire-specific PM2.5 during pregnancy. Additionally, the mean exposure to daily maximum temperature during pregnancy was calculated.

Main Outcomes and Measures

The primary outcome was sPTB identified through a natural language processing algorithm. Discrete-time survival models were used to estimate associations of total PM2.5 concentration and its 5 constituents with sPTB. Interaction terms were used to examine the effect modification by race and ethnicity, educational attainment, household income, and exposures to green space, wildfire smoke, and temperature.

Results

Among 409 037 births (mean [SD] age of mothers at delivery, 30.3 [5.8] years), there were positive associations of PM2.5, black carbon, nitrate, and sulfate with sPTB. Adjusted odds ratios (aORs) per IQR increase were 1.15 (95% CI, 1.12-1.18; P < .001) for PM2.5 (IQR, 2.76 μg/m3), 1.15 (95% CI, 1.11-1.20; P < .001) for black carbon (IQR, 1.05 μg/m3), 1.09 (95% CI, 1.06-1.13; P < .001) for nitrate (IQR, 0.93 μg/m3), and 1.06 (95% CI, 1.03-1.09; P < .001) for sulfate (IQR, 0.40 μg/m3) over the entire pregnancy. The second trimester was the most susceptible window; for example, aORs for total PM2.5 concentration were 1.07 (95% CI, 1.05-1.09; P < .001) in the first, 1.10 (95% CI, 1.08-1.12; P < .001) in the second, and 1.09 (95% CI, 1.07-1.11; P < .001) in the third trimester. Significantly higher aORs were observed among individuals with lower educational attainment (eg, less than college: aOR, 1.16; 95% CI, 1.12-1.21 vs college [≥4 years]: aOR, 1.10; 95% CI, 1.06-1.14; P = .03) or income (<50th percentile: aOR, 1.17; 95% CI, 1.14-1.21 vs ≥50th percentile: aOR, 1.12; 95% CI, 1.09-1.16; P = .02) or who were exposed to limited green space (<50th percentile: aOR, 1.19; 95% CI, 1.15-1.23 vs ≥50th percentile: aOR, 1.12; 95% CI, 1.09-1.15; P = .003), more wildfire smoke (≥50th percentile: aOR, 1.19; 95% CI, 1.16-1.23 vs <50th percentile: aOR, 1.13; 95% CI, 1.09-1.16; P = .009), or extreme heat (aOR, 1.51; 95% CI, 1.42-1.59 vs mild temperature: aOR, 1.11; 95% CI, 1.09-1.14; P < .001).

Conclusions and Relevance

In this study, exposures to PM2.5 and specific PM2.5 constituents during pregnancy were associated with increased odds of sPTB. Socioeconomic status and other environmental exposures modified this association.

Respiratory Diseases Associated With Wildfire Exposure in Outdoor Workers

Wildfires, including forest fires, bushfires, and landscape fires, have become increasingly prevalent, fueled by climate change and environmental factors and posing significant challenges to both ecosystems and public health. This review article examines the relationship between wildfires and respiratory diseases in outdoor workers, with a main focus on airway disease. In addition to the expected effects of direct thermal respiratory injuries and possible carbon monoxide poisoning, there are associations between wildfires and upper and lower respiratory effects, including infections as well as exacerbations of asthma and chronic obstructive pulmonary disease. A few studies have also shown an increased risk of new-onset asthma among wildfire firefighters. Outdoor workers are likely to have greater exposure to wildfire smoke with associated increased risks of adverse effects. As wildfires become increasingly prevalent globally, it is crucial to understand the various dimensions of this association. Furthermore, this review addresses preventive measures and potential interventions to alleviate the airway burden on individuals during and after work with wildfires events.

Data Linkages for Wildfire Exposures and Human Health Studies: A Scoping Review

Wildfires are increasing in frequency and intensity, with significant consequences that impact human health. A scoping review was conducted to: (a) understand wildfire-related health effects, (b) identify and describe environmental exposure and health outcome data sources used to research the impacts of wildfire exposures on health, and (c) identify gaps and opportunities to leverage exposure and health data to advance research. A literature search was conducted in PubMed and a sample of 83 articles met inclusion criteria. A majority of studies focused on respiratory and cardiovascular outcomes. Hospital administrative data was the most common health data source, followed by government data sources and health surveys. Wildfire smoke, specifically fine particulate matter (PM2.5), was the most common exposure measure and was predominantly estimated from monitoring networks and satellite data. Health data were not available in real-time, and they lacked spatial and temporal coverage to study health outcomes with longer latency periods. Exposure data were often available in real-time and provided better temporal and spatial coverage but did not capture the complex mixture of hazardous wildfire smoke pollutants nor exposures associated with non-air pathways such as soil, household dust, food, and water. This scoping review of the specific health and exposure data sources used to underpin these studies provides a framework for the research community to understand: (a) the use and value of various environmental and health data sources, and (b) the opportunities for improving data collection, integration, and accessibility to help inform our understanding of wildfires and other environmental exposures.

Associations between short-term exposure to wildfire particulate matter and respiratory outcomes: A systematic review

BACKGROUND

The frequency and severity of wildfires have been sharply increasing due to climate change, which largely contributes to ambient particulate matter (PM) pollution. We conducted a systematic review focusing on the short-term relationships between PM attributable to wildfires (wildfire-specific PM) and diverse respiratory endpoints, with a comparison between the effects of wildfire-specific PM vs. all-source/non-wildfire PM.

METHODS

A comprehensive online search for the literature published from 2000 to 2022 was conducted through PubMed, Web of Sciences, Scopus, and EMBASE. We applied search terms related to wildfire smoke and respiratory health outcomes.

RESULTS

In total, 3196 articles were retrieved, and 35 articles were included in this review. Most studies focused on the associations of wildfire-specific PM with an aerodynamic diameter of <2.5 μm (PM2.5) with respiratory emergency department visits or hospitalizations, with a time-series or case-crossover study design. Studies were mostly conducted in the United States, Canada, and Australia. Positive associations of wildfire-specific PM with respiratory morbidity were observed in most studies. Studies that focused on respiratory mortality were limited. Females can be more vulnerable to the respiratory impacts of wildfire PM, while the evidence of vulnerable subpopulations among different age groups was inconclusive. Few studies compared the effects of wildfire-specific vs. all-source/non-wildfire PM, and some reported higher levels of toxicity of wildfire-specific PM, potentially due to its distinct chemical and physical compositions. Asthma and chronic obstructive pulmonary disease were the most studied diseases, and both were adversely affected by wildfire-specific PM.

CONCLUSION

To our knowledge, this is the first review that systematically summarized the associations of wildfire-specific PM exposure with adverse respiratory outcomes and compared associations of wildfire-specific vs. all-source/non-wildfire PM. Further investigations may add to the literature by examining the impacts on respiratory mortality and the effects of specific PM components from different types of wildfires.

Designing a conceptual framework for strategic selection of Bushfire mitigation approaches

Fires are an important aspect of environmental ecology; however, they are also one of the most widespread destructive forces impacting natural ecosystems as well as property, human health, water and other resources. Urban sprawl is driving the construction of new homes and facilities into fire-vulnerable areas. This growth, combined with a warmer climate, is likely to make the consequences of wildfires more severe. To reduce wildfires and associated risks, a variety of hazard reduction practices are implemented, such as prescribed burning (PB) and mechanical fuel load reduction (MFLR). PB can reduce forest fuel load; however, it has adverse effects on air quality and human health, and should not be applied close to residential areas due to risks of fire escape. On the other hand, MFLR releases less greenhouse gasses and does not impose risks to residential areas. However, it is more expensive to implement. We suggest that environmental, economic and social costs of various mitigation tools should be taken into account when choosing the most appropriate fire mitigation approach and propose a conceptual framework, which can do it. We show that applying GIS methods and life cycle assessment we can produce a more reasonable comparison that can, for example, include the benefits that can be generated by using collected biomass for bioenergy or in timber industries. This framework can assist decision makers to find the optimal combinations of hazard reduction practices for various specific conditions and locations.

Increase in daily asthma medication sales in association with air pollution levels in Greater Stockholm

Daily air pollution levels are known to influence the number of patients with acute asthma. We investigated the short-term effects of air pollution exposure on the daily number of asthma medication purchases in the Greater Stockholm area, Sweden.

Methods

We conducted a time-series study with data on asthma medication purchases and daily mean values of particulate matter ≤10 µm (PM10), nitrogen oxides (NOx), and ozone during 2018-2019. We used nonlinear distributed lag quasi-Poisson regression models to estimate the associations between air pollution levels and medication purchases, adjusting for meteorological variables, pollen levels, day of the week, and long-term trends. The models established linear relationships between air pollutants and the outcome, and potential delayed effects were smoothed with a spline across a lag period of 2 weeks. We applied separate models for each municipality (n = 21) in Greater Stockholm, and calculated pooled estimates to achieve combined results for the whole region.

Results

We observed associations between daily levels of air pollution and purchases of asthma medications, most clearly for PM10. The pooled estimates of the relative risks for asthma medication purchases across all 21 municipalities associated with a 10 μg m-3 increase in PM10 the same day (lag 0) was 1.7% [95% confidence interval (CI): 1.2%, 2.1%], a cumulative increase of 4.6% (95% CI: 3.7%, 5.6%) over one week (lag 0-6), and a 6.5% (95% CI: 5%, 8%) increase over 2 weeks (lag 0-13). The corresponding pooled effect per 10 μg m-3 increase in NOx and ozone were 2.8% (95% CI: 1.6%, 4.1%) and 0.7% (95% CI: 0%, 1.4%) over 2 weeks (lag 0-13), respectively.

Conclusions

Our study revealed short-term associations between air pollution, especially PM10, and purchases of asthma medications.

Effect modification of the association between fine particulate air pollution during a wildfire event and respiratory health by area-level measures of socio-economic status, race/ethnicity, and smoking prevalence

Fine particulate air pollution (PM2.5) is decreasing in most areas of the United States, except for areas most affected by wildfires, where increasing trends in PM2.5 can be attributed to wildfire smoke. The frequency and duration of large wildfires and the length of the wildfire season have all increased in recent decades, partially due to climate change, and wildfire risk is projected to increase further in many regions including the western United States. Increasingly, empirical evidence suggests differential health effects from air pollution by class and race; however, few studies have investigated such differential health impacts from air pollution during a wildfire event. We investigated differential risk of respiratory health impacts during the 2008 northern California wildfires by a comprehensive list of socio-economic status (SES), race/ethnicity, and smoking prevalence variables. Regardless of SES level across nine measures of SES, we found significant associations between PM2.5 and asthma hospitalizations and emergency department (ED) visits during these wildfires. Differential respiratory health risk was found by SES for ED visits for chronic obstructive pulmonary disease where the highest risks were in ZIP codes with the lowest SES levels. Findings for differential effects by race/ethnicity were less consistent across health outcomes. We found that ZIP codes with higher prevalence of smokers had greater risk of ED visits for asthma and pneumonia. Our study suggests that public health efforts to decrease exposures to high levels of air pollution during wildfires should focus on lower SES communities.

The Effects of Trash, Residential Biofuel, and Open Biomass Burning Emissions on Local and Transported PM2.5 and Its Attributed Mortality in Africa

Long-term exposure to ambient fine particulate matter (PM2.5) is the second leading risk factor of premature death in Sub-Saharan Africa. We use GEOS-Chem to quantify the effects of (a) trash burning, (b) residential solid-fuel burning, and (c) open biomass burning (BB) (i.e., landscape fires) on ambient PM2.5 and PM2.5-attributable mortality in Africa. Using a series of sensitivity simulations, we excluded each of the three combustion sources in each of five African regions. We estimate that in 2017 emissions from these three combustion sources within Africa increased global ambient PM2.5 by 2%, leading to 203,000 (95% confidence interval: 133,000-259,000) premature mortalities yr-1 globally and 167,000 premature mortalities yr-1 in Africa. BB contributes more ambient PM2.5-related premature mortalities per year (63%) than residential solid-fuel burning (29%) and trash burning (8%). Open BB in Central Africa leads to the largest number of PM2.5-attributed mortalities inside the region, while trash burning in North Africa and residential solid-fuel burning in West Africa contribute the most regional mortalities for each source. Overall, Africa has a unique ambient air pollution profile because natural sources, such as windblown dust and BB, contribute strongly to ambient PM2.5 levels and PM2.5-related mortality. Air pollution policies may need to focus on taking preventative measures to avoid exposure to ambient PM2.5 from these less-controllable sources.

Health Outcomes in Children Associated with Prenatal and Early-Life Exposures to Air Pollution: A Narrative Review

(1) Background: The developmental origins of health and disease (DOHaD) hypothesis links adverse fetal exposures with developmental mal-adaptations and morbidity later in life. Short- and long-term exposures to air pollutants are known contributors to health outcomes; however, the potential for developmental health effects of air pollution exposures during gestation or early-childhood have yet to be reviewed and synthesized from a DOHaD lens. The objective of this study is to summarize the literature on cardiovascular and metabolic, respiratory, allergic, and neuropsychological health outcomes, from prenatal development through early childhood, associated with early-life exposures to outdoor air pollutants, including traffic-related and wildfire-generated air pollutants. (2) Methods: We conducted a search using PubMed and the references of articles previously known to the authors. We selected papers that investigated health outcomes during fetal or childhood development in association with early-life ambient or source-specific air pollution exposure. (3) Results: The current literature reports that prenatal and early-childhood exposures to ambient and traffic-related air pollutants are associated with a range of adverse outcomes in early life, including cardiovascular and metabolic, respiratory and allergic, and neurodevelopmental outcomes. Very few studies have investigated associations between wildfire-related air pollution exposure and health outcomes during prenatal, postnatal, or childhood development. (4) Conclusion: Evidence from January 2000 to January 2022 supports a role for prenatal and early-childhood air pollution exposures adversely affecting health outcomes during development. Future studies are needed to identify both detrimental air pollutants from the exposure mixture and critical exposure time periods, investigate emerging exposure sources such as wildfire, and develop feasible interventional tools.

Impact of Wildfire Smoke Exposure on Health in Korea

PURPOSE

The characteristic topography and climate often affect the occurrence of large-scale wildfires in the Eastern Gangwon-do region of Korea. However, there are no studies on the health effects of these wildfires in Korea. This study aimed to analyze the differences in medical use between a wildfire-affected area and an adjacent non-affected area before and after a wildfire in 2019 in Gangwon-do, Korea.

MATERIALS AND METHODS

We used medical usage data from the Korean National Health Insurance Corporation. Rates of medical use were determined for citizens of a wildfire-affected area in the Eastern Yeongdong region and a non-affected area in the Western Yeongseo region. Logistic regression analysis was performed considering an increase in medical use per individual as a dependent variable; age, sex, income, smoking, drinking, and exercise were included as confounding variables.

RESULTS

The odds ratio for medical use in Yeongdong region increased significantly after 3 days, 3 months, and 1 year after a fire occurred, compared with Yeongseo region.

CONCLUSION

The results of this study confirmed that the use of medical care increased for residents of a wildfire-affected area, compared with those of an adjacent non-affected area. This is the first study on the relationship between wildfires and inpatient medical use in Korea.

Exposure to fine particulate matter (PM2.5) during landscape fire events and the risk of cardiorespiratory emergency department attendances: a time-series study in Perth, Western Australia

BACKGROUND

Landscape fires (LFs) are the main source of elevated particulate matter (PM2.5) in Australian cities and towns. This study examined the associations between daily exposure to fine PM2.5 during LF events and daily emergency department attendances (EDA) for all causes, respiratory and cardiovascular outcomes.

METHODS

Daily PM2.5 was estimated using a model that included PM2.5 measurements on the previous day, remotely sensed aerosols and fires, hand-drawn tracing of smoke plumes from satellite images, fire danger ratings and the atmosphere venting index. Daily PM2.5 was then categorised as high (≥99th percentile), medium (96th-98th percentile) and low (≤95th percentile). Daily EDA for all-cause and cardiorespiratory conditions were obtained from the Western Australian Emergency Department Data Collection. We used population-based cohort time-series multivariate regressions with 95% CIs to assess modelled daily PM2.5 and EDA associations from 2015 to 2017. We estimated the lag-specific associations and cumulative risk ratios (RR) at lags of 0-3 days, adjusted for sociodemographic factors, weather and time.

RESULTS

All-cause EDA and overall cardiovascular presentations increased on all lagged days and up to 5% (RR 1.05, 95% CI 1.03 to 1.06) and 7% (RR 1.07, 95% CI 1.01 to 1.12), respectively, at the high level. High-level exposure was also associated with increased acute lower respiratory tract infections at 1 (RR 1.19, 95% CI 1.10 to 1.29) and 3 (RR 1.17, 95% CI 1.10 to 1.23) days lags and transient ischaemic attacks at 1 day (RR 1.25, 95% CI 1.02 to 1.53) and 2 (RR 1.20, 95% CI 1.01 to 1.42) days lag.

CONCLUSIONS

Exposure to PM2.5 concentrations during LFs was associated with an increased risk of all-cause EDA, overall EDA cardiovascular diseases, acute respiratory tract infections and transient ischaemic attacks.

Medication use in populations exposed to the 2010 Eyjafjallajökull eruption: an interrupted time series analysis

OBJECTIVES

To assess the trends in medication use indicative of physical and psychological morbidity following the 2010 volcanic eruption in Eyjafjallajökull immediately after and during a 3-year period following the eruption.

DESIGN

Population-based register study.

SETTING

Eyjafjallajökull eruption in Iceland, 2007-2013.

PARTICIPANTS

All residents in Iceland who received at least one medication dispensing were identified. Residents of exposed areas were classified into exposure groups (individual-level data) and residents in other parts of Iceland were included as a non-exposed group (aggregated data).

INTERVENTION/EXPOSURE

Eyjafjallajökull erupted on 14 April 2010 and continued for 39 days, producing heavy ash fall in South Iceland.

MAIN OUTCOME MEASURES

Using interrupted time series analysis, we examined annual and quarterly changes in medicine use, measured as number of dispensed defined daily dose (DDD) per 1000 individuals. We calculated the level shift (immediate change) and change in slope from pre-eruption to post-eruption (long-term change) in medication dispensing.

RESULTS

Among exposed residents, there was a 6% decrease (95% CI -7% to -4%) in the annual number of dispensed DDDs 1-year post-eruption in the overall medication class, including analgesics (-5%, 95% CI -6% to -3%), hypnotics and sedatives (-9%, 95% CI -11% to -7%) and respiratory medications (-7%, 95% CI -9% to -5%; -8%, 95% CI -11% to -4%). Simultaneously, there was a 9% decrease (95% CI -14% to -4%) in the overall medication class among non-exposed residents. Moreover, among exposed residents, we observed change in slope of -4% (95% CI -7% to -1%) in the overall medication class, including for analgesics (-6%, 95% CI -8% to -3%) and other respiratory drugs (-10%, 95% CI -16% to -4%).

CONCLUSION

Our findings indicate that the eruption did not lead to increases in medication dispensing among residents of exposed areas, rather decreases for some medicine classes. The results should be interpreted with caution since the content of each eruption differs.

Evaluation of a national smoke-free prisons policy using medication dispensing: an interrupted time-series analysis

BACKGROUND

Internationally, smoking prevalence among people in prison custody (ie, people on remand awaiting trial, awaiting sentencing, or serving a custodial sentence) is high. In Scotland, all prisons implemented a comprehensive smoke-free policy in 2018 after a 16-month anticipatory period. In this study, we aimed to use data on medication dispensing to assess the impact of this policy on cessation support, health outcomes, and potential unintended consequences among people in prison custody.

METHODS

We did an interrupted time-series analysis using dispensing data for 44 660 individuals incarcerated in 14 closed prisons in Scotland between March 30, 2014, and Nov 30, 2019. We estimated changes in dispensing rates associated with the policy announcement (July 17, 2017) and full implementation (Nov 30, 2018) using seasonal autoregressive integrated moving average models. Medication categories of primary interest were treatments for nicotine dependence (as an indicator of smoking cessation or abstinence attempts), acute smoking-associated illnesses, and mental health (antidepressants). We included antiepileptic medications as a negative control.

FINDINGS

A 44% step increase in dispensing of treatments for nicotine dependence was observed at implementation (2250 items per 1000 people in custody per fortnight, 95% CI 1875 to 2624) due primarily to a 42% increase in dispensing of nicotine replacement therapy (2109 items per 1000 people in custody per fortnight, 1701 to 2516). A 9% step decrease in dispensing for smoking-related illnesses was observed at implementation, largely accounted for by respiratory medications (-646 items per 1000 people in custody per fortnight, -1111 to -181). No changes associated with announcement or implementation were observed for mental health dispensing or antiepileptic medications (control).

INTERPRETATION

Smoke-free prison policies might improve respiratory health among people in custody and encourage smoking abstinence or cessation without apparent short-term adverse effects on mental health dispensing.

FUNDING

National Institute of Health Research Public Health Research programme, Scottish Government Chief Scientist Office, and UK Medical Research Council.

Chronic Obstructive Pulmonary Disease in Adults Exposed to Fine Particles from a Coal Mine Fire

RATIONALE

In 2014 the Hazelwood open cut coal mine in south eastern Australia burned for six weeks, exposing nearby residents to high concentrations of fine particulate matter (PM_2.5). The long-term health consequences are unknown, and are being evaluated as part of the Hazelwood Health Study.

OBJECTIVES

To explore the association between PM_2.5 exposure and chronic obstructive pulmonary disease (COPD).

METHODS

A sample of 346 exposed, and 173 unexposed, adults participated in the longitudinal Respiratory Stream of the Hazelwood Health Study. Participants underwent spirometry and gas transfer measurements, and answered validated respiratory questionnaires 3.5-4 years after the fire. Individual-level mine fire-related PM_2.5 exposure was modelled. Multivariate linear regression and logistic models were fitted to analyse associations between mean and peak PM_2.5 exposure and clinical outcomes, stratified by smoking status.

RESULTS

A 10 μg/m³ increase in mean PM_2.5 exposure was associated with a 69% (95%CI: 11% to 158%) increase in odds of spirometry consistent with COPD amongst non-smokers and increased odds of chest tightness (odds ratio; OR 1.30, 95%CI 1.03 to 1.64) and chronic cough (OR 1.24, 95%CI 1.02 to 1.51) in the previous 12 months in all participants. For current smokers, increments in mean PM_2.5 exposure were associated with higher odds of chronic cough in the preceding 12 months (OR 2.13, 95%CI 1.24 to 3.65).

CONCLUSIONS

Almost four years after a six-week period of coal fire PM_2.5 exposure, we identified a dose-response association between exposure and COPD in non-smokers. With climate change a likely contributor to increased risk of landscape fires, the findings will inform policy decisions during future sustained smoke events.

Extreme Weather and Climate Change: Population Health and Health System Implications

Extreme weather and climate events, such as heat waves, cyclones, and floods, are an expression of climate variability. These events and events influenced by climate change, such as wildfires, continue to cause significant human morbidity and mortality and adversely affect mental health and well-being. Although adverse health impacts from extreme events declined over the past few decades, climate change and more people moving into harm's way could alter this trend. Long-term changes to Earth's energy balance are increasing the frequency and intensity of many extreme events and the probability of compound events, with trends projected to accelerate under certain greenhouse gas emissions scenarios. While most of these events cannot be completely avoided, many of the health risks could be prevented through building climate-resilient health systems with improved risk reduction, preparation, response, and recovery. Conducting vulnerability and adaptation assessments and developing health system adaptation plans can identify priority actions to effectively reduce risks, such as disaster risk management and more resilient infrastructure. The risks are urgent, so action is needed now.

The economics of precision health: preventing air pollution-induced exacerbation in asthma

The demonstrable value of precision medicine, in the context of common environmental exposures, has scarcely been explored. This study evaluated the cost effectiveness of a preventive personalised intervention to reduce the adverse effect of air pollution in the context of asthma.

A decision–analytic model was used to conduct a cost-utility analysis of prevention interventions in case of acute exposure to air pollution in mild asthma. Three different strategies, as follows, were compared: no preventive intervention; precision health strategy based on information from genotype testing, followed with treating high-risk patients; and prescribing additional medication to all mild asthmatics as a preventive intervention. The costs and quality-adjusted life years (QALYs) in the base case and alternative scenarios were obtained through probabilistic analysis.

The results showed that the precision prevention intervention (anticipatory intervention for asthmatics, guided by relevant genetic abnormality, in the face of acute air pollution) is a cost-effective strategy compared with no such intervention, with an incremental cost-effectiveness ratio of CAD 49 555 per QALY. Furthermore, this strategy is a dominant strategy compared with an intervention that prescribes medication indiscriminately to all asthmatics.

The incorporation of genomic testing to stratify risk of asthmatics to pollution-driven exacerbations, and then tailoring a preventive intervention accordingly, may be cost effective relative to untailored methods. These results lend plausibility to the use of precision medicine for limiting asthma exacerbation in the context of air pollution and, potentially, other exposures.

Glutathione-S-transferase genotyping to determine the use of preventive asthma medication in the face of air pollution is cost effective in this model. Precision prevention in the setting of common environmental exposures may be used in other contexts.https://bit.ly/35Lab4b

Staying Ahead of the Epidemiologic Curve: Evaluation of the British Columbia Asthma Prediction System (BCAPS) During the Unprecedented 2018 Wildfire Season

Background: The modular British Columbia Asthma Prediction System (BCAPS) is designed to reduce information burden during wildfire smoke events by automatically gathering, integrating, generating, and visualizing data for public health users. The BCAPS framework comprises five flexible and geographically scalable modules: (1) historic data on fine particulate matter (PM_2.5) concentrations; (2) historic data on relevant health indicator counts; (3) PM_2.5 forecasts for the upcoming days; (4) a health forecasting model that uses the relationship between (1) and (2) to predict the impacts of (3); and (5) a reporting mechanism. Methods: The 2018 wildfire season was the most extreme in British Columbia history. Every morning BCAPS generated forecasts of salbutamol sulfate (e.g., Ventolin) inhaler dispensations for the upcoming days in 16 Health Service Delivery Areas (HSDAs) using random forest machine learning. These forecasts were compared with observations over a 63-day study period using different methods including the index of agreement (IOA), which ranges from 0 (no agreement) to 1 (perfect agreement). Some observations were compared with the same period in the milder wildfire season of 2016 for context. Results: The mean province-wide population-weighted PM_2.5 concentration over the study period was 22.0 μg/m³, compared with 4.2 μg/m³ during the milder wildfire season of 2016. The PM_2.5 forecasts underpredicted the severe smoke impacts, but the IOA was relatively strong with a population-weighted average of 0.85, ranging from 0.65 to 0.95 among the HSDAs. Inhaler dispensations increased by 30% over 2016 values. Forecasted dispensations were within 20% of the observed value in 71% of cases, and the IOA was strong with a population-weighted average of 0.95, ranging from 0.92 to 0.98. All measures of agreement were correlated with HSDA population, where BCAPS performance was better in the larger populations with more moderate smoke impacts. The accuracy of the health forecasts was partially dependent on the accuracy of the PM_2.5 forecasts, but they were robust to over- and underpredictions of PM_2.5 exposure. Conclusions: Daily reports from the BCAPS framework provided timely and reasonable insight into the population health impacts of predicted smoke exposures, though more work is necessary to improve the PM_2.5 and health indicator forecasts.

Differential Cardiopulmonary Health Impacts of Local and Long-Range Transport of Wildfire Smoke

We estimated cardiopulmonary morbidity and mortality associated with wildfire smoke (WFS) fine particulate matter (PM2.5) in the Front Range of Colorado from 2010 to 2015. To estimate WFS PM2.5, we developed a daily kriged PM2.5 surface at a 15  × 15 km resolution based on the Environmental Protection Agency Air Quality System monitors for the western United States; we subtracted out local seasonal-average PM2.5 of nonsmoky days, identified using satellite-based smoke plume estimates, from the local daily estimated PM2.5 if smoke was identified by National Oceanic and Atmospheric Administration's Hazard Mapping System. We implemented time-stratified case-crossover analyses to estimate the effect of a 10 µg/m3 increase in WFS PM2.5 with cardiopulmonary hospitalizations and deaths using single and distributed lag models for lags 0-5 and distinct annual impacts based on local and long-range smoke during 2012, and long-range transport of smoke in 2015. A 10 µg/m3 increase in WFS was associated with all respiratory, asthma, and chronic obstructive pulmonary disease hospitalizations for lag day 3 and hospitalizations for ischemic heart disease at lag days 2 and 3. Cardiac arrest deaths were associated with WFS PM2.5 at lag day 0. For 2012 local wildfires, asthma hospitalizations had an inverse association with WFS PM2.5 (OR: 0.716, 95% CI: 0.517-0.993), but a positive association with WFS PM2.5 during the 2015 long-range transport event (OR: 1.455, 95% CI: 1.093-1.939). Cardiovascular mortality was associated with the 2012 long-range transport event (OR: 1.478, 95% CI: 1.124-1.944).

SOS! Summer of Smoke: a retrospective cohort study examining the cardiorespiratory impacts of a severe and prolonged wildfire season in Canada's high subarctic

OBJECTIVES

To determine healthcare service utilisation for cardiorespiratory presentations and outpatient salbutamol dispensation associated with 2.5 months of severe, unabating wildfire smoke in Canada's high subarctic.

DESIGN

A retrospective cohort study using hospital, clinic, pharmacy and environmental data analysed using Poisson regression.

SETTING

Territorial referral hospital and clinics in Yellowknife, Northwest Territories, Canada.

PARTICIPANTS

Individuals from Yellowknife and surrounding communities presenting for care between 2012 and 2015.

MAIN OUTCOME MEASURES

Emergency room (ER) presentations, hospital admissions and clinic visits for cardiorespiratory events, and outpatient salbutamol prescriptions RESULTS: The median 24-hour mean particulate matter (PM_2.5) was fivefold higher in the summer of 2014 compared with 2012, 2013 and 2015 (median=30.8 µg/m³), with the mean peaking at 320.3 µg/m³. A 10 µg/m³ increase in PM_2.5 was associated with an increase in asthma-related (incidence rate ratio (IRR) (95% CI): 1.11 (1.07, 1.14)) and pneumonia-related ER visits (IRR (95% CI): 1.06 (1.02, 1.10)), as well as an increase in chronic obstructive pulmonary disease hospitalisations (IRR (95% CI): 1.11 (1.02, 1.20). Compared with 2012 and 2013, salbutamol dispensations in 2014 increased by 48%; clinic visits for asthma, pneumonia and cough increased; ER visits for asthma doubled, with the highest rate in females, in adults aged ≥40 years and in Dene people, while pneumonia increased by 57%, with higher rates in males, in individualsaged <40 years and in Inuit people. Cardiac variables were unchanged.

CONCLUSIONS

Severe wildfires in 2014 resulted in extended poor air quality associated with increases in health resource utilization; some impacts were seen disproportionately among vulnerable populations, such as children and Indigenous individuals. Public health advisories asking people to stay inside were inadequately protective, with compliance possibly impacted by the prolonged exposure. Future research should investigate use of at-home air filtration systems, clean-air shelters and public health messaging which addresses mental health and supports physical activity.

Gridded bias correction of modeled PM2.5 for exposure assessment, and estimation of background concentrations over a coastal valley region of northwestern British Columbia, Canada

Chemical transport models (CTM) can have large biases and errors when simulating pollutant concentrations. To improve the characterization of fine particulate matter (PM_2.5) over complex terrain for exposure assessments, three mathematical formulae that utilized the relationship between modeled and observed quantile concentrations at a monitor location were developed. These were then applied to 1 year of CMAQ model output of PM_2.5 over the Terrace-Kitimat Valley of northwestern British Columbia, Canada. The final products enhanced the representation of ambient levels at existing monitoring stations when evaluated with conventional statistical measures. Better agreement of corrected outputs with observed compliance metrics was also found. On average, the absolute errors of amended outputs were 11% and 10% for the annual mean PM_2.5 and 98th percentiles of daily concentrations, respectively, compared to 45% and 61%, respectively, in the original outputs. These improvements provided greater confidence to use the amended outputs to estimate concentrations at locations without monitors. The predominance of pristine conditions in the modeling domain was exploited to derive annual background PM_2.5 concentrations over the valley, which was estimated to be 2.0-2.3 μg m^-3. To our knowledge, this is the first study to calculate background PM_2.5 concentrations over northern BC coastlands using bias-corrected outputs from an air quality model. Implications: Bias correction of CMAQ model output was necessary for assessing regulatory compliance for ambient PM_2.5. The implications are notable. First, for low to moderate spatial heterogeneity in monitoring data, the use of regression equations that relates quantile mean concentrations of model outputs to those of observational data enhances the estimation of PM_2.5 at unmonitored locations. Second, by providing spatial pollutant distribution ahead of planned industrial development in Terrace-Kitimat Valley (TKV), corrected model output offers a baseline for tracking progress in airshed management. Third, correction improved pollutant exposure classification, for which the risk was predominantly low. Finally, 2.0-2.3 μg m^-3 should be considered as PM_2.5 concentrations that are irreducible when setting voluntary targets for ambient levels in the area.

Understanding the relationships between environmental factors and exacerbations of COPD

INTRODUCTION

Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with a significant health burden both for patients and healthcare systems. Exposure to various environmental factors increases the risk of exacerbations.

AREAS COVERED

We searched PubMed and assessed literature published within the last 10 years to include epidemiological evidence on the relationships between air pollution, temperature and COPD exacerbation risk as well as the implications of extreme weather events on exacerbations.

EXPERT OPINION

Ongoing climate change is expected to increase air pollution levels, global temperature and the frequency and severity of extreme weather events, all of which are associated with COPD exacerbations. Further research is needed using patient-focused methodological approaches to better understand and quantify these relationships, so that effective mitigation strategies that decrease the risk of exacerbations can be developed.

Evaluating an Air Quality Health Index (AQHI) amendment for communities impacted by residential woodsmoke in British Columbia, Canada

Smoke from burning biomass is an important source of fine particulate matter (PM_2.5), but the health risks may not be fully captured by the Canadian Air Quality Health Index (AQHI). In May 2018, the province of British Columbia launched an evidence-based amendment (AQHI-Plus) to improve AQHI performance for wildfire smoke, but the AQHI-Plus was not developed or tested on data from the residential woodsmoke season. This study assesses how the AQHI and AQHI-Plus are associated with acute health outcomes during the cooler seasons of 2010-2017 in British Columbia, Canada. Monthly and daily patterns of temperature and PM_2.5 concentrations were used to identify Local Health Areas (LHAs) that were impacted by residential woodsmoke. The effects of the AQHI and AQHI-Plus on five acute health outcomes (including non-accidental mortality, outpatient physician visits, and medical dispensations for cardiopulmonary conditions) were estimated using generalized linear mixed effect models with Poisson distributions adjusted for long- and short-term temperature trends. Values of the Akaike information criterion (AIC) were compared to evaluate whether the AQHI or AQHI-Plus was better fitted to each health outcome. Eleven LHAs were categorized as woodsmoke-impacted. In these LHAs, the AQHI and AQHI-Plus associations with acute health outcomes were sensitive to temperature adjustments. After temperature adjustments, the most consistent associations were observed for the two asthma-specific outcomes where the AQHI-Plus was better fitted than the AQHI. The improved performance of the AQHI-Plus for susceptible populations with asthma is consistent between communities impacted by residential woodsmoke and wildfire smoke. Implications: Canada's Air Quality Health Index (AQHI) is a three pollutant index used to communicate the short term health impact of degraded air quality. As fine particulate matter (PM_2.5) is the lowest weighted pollutant in the AQHI, the index is poorly reflective of woodsmoke impacts. The present analysis found that an AQHI amendment developed for improved sensitivity to PM_2.5 during wildfire seasons (AQHI-Plus) is also more predictive of acute asthma-related health outcomes in communities impacted by residential woodsmoke. The BC Ministry of Environment and Climate Change Strategy has piloted the AQHI-Plus year-round. Other jurisdictions should consider whether their air quality indices are reflective of the risks posed by woodsmoke.

Characterizing environmental asthma triggers and healthcare use patterns in Puerto Rico

Objective: Asthma carries a high burden of disease for residents of Puerto Rico. We conducted this study to better understand asthma-related healthcare use and to examine potential asthma triggers.Methods: We characterized asthma-related healthcare use in 2013 by demographics, region, and date using outpatient, hospital, and emergency department (ED) insurance claims with a primary diagnostic ICD-9-CM code of 493.XX. We examined environmental asthma triggers, including outdoor allergens (i.e., mold and pollen), particulate pollution, and influenza-like illness. Analyses included descriptive statistics and Poisson time-series regression.Results: During 2013, there were 550,655 medical asthma claims reported to the Puerto Rico Healthcare Utilization database, representing 148 asthma claims/1,000 persons; 71% of asthma claims were outpatient visits, 19% were hospitalizations, and 10% were ED visits. Females (63%), children aged ≤9 years (77% among children), and adults aged ≥45 years (80% among adults) had the majority of asthma claims. Among health regions, Caguas had the highest asthma claim-rate at 142/1,000 persons (overall health region claim-rate = 108). Environmental exposures varied across the year and demonstrated seasonal patterns. Metro health region regression models showed positive associations between increases in mold and particulate matter <10 microns in diameter (PM10) and outpatient asthma claims.Conclusions: This study provides information about patterns of asthma-related healthcare use across Puerto Rico. Increases in mold and PM10 were associated with increases in asthma claims. Targeting educational interventions on exposure awareness and reduction techniques, especially to persons with higher asthma-related healthcare use, can support asthma control activities in public health and clinical settings.

The association between wildfire smoke exposure and asthma-specific medical care utilization in Oregon during the 2013 wildfire season

Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter ≤ 2.5 μm in diameter (PM2.5) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM2.5 was evaluated using time-stratified case-crossover designs. The maximum WFS PM2.5 concentration during the study period was 172 µg/m3. A 10 µg/m3 increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.

Sub-Daily Exposure to Fine Particulate Matter and Ambulance Dispatches during Wildfire Seasons: A Case-Crossover Study in British Columbia, Canada

BACKGROUND

Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d.

OBJECTIVES

We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia.

METHODS

We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD).

RESULTS

Increased respiratory health outcomes were observed within 1 h of exposure to a 10-μg/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively.

CONCLUSIONS

We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792.

A Scoping Review of Nurses' Contributions to Health-Related, Wildfire Research

Exposure to unprecedented levels of wildfire smoke is increasing cardiopulmonary mortality and is especially catastrophic to people with preexisting respiratory conditions such as asthma. Wildfire smoke is a mixture of hazardous air pollutants and airborne particulate matter and wildfires are burning larger areas of land and lasting longer, extending the smoke season. The wildfire season is also expected to lengthen as a result of the changing climate. This scoping review examines publications related to wildfires and health in order to explore the ways in which nursing science contributes to research on the health effects of wildfires and strategies to decrease exposure to wildfires and/or wildfire smoke. Nursing's contribution to wildfire research needs to increase to meet the demands of this rapidly growing, international problem. Nurses have an opportunity to protect the public's health through interventional research focused on preventing exposure and applying what is learned to practice.

Associations between Respiratory Health Outcomes and Coal Mine Fire PM2.5 Smoke Exposure: A Cross-Sectional Study

In 2014, wildfires ignited a fire in the Morwell open cut coal mine, Australia, which burned for six weeks. This study examined associations between self-reported respiratory outcomes in adults and mine fire-related PM_2.5 smoke exposure. Self-reported data were collected as part of the Hazelwood Health Study Adult Survey. Eligible participants were adult residents of Morwell. Mine fire-related PM_2.5 concentrations were provided by the Commonwealth Scientific and Industrial Research Organisation Oceans & Atmosphere Flagship. Personalised mean 24-h and peak 12-h mine fire-related PM_2.5 exposures were estimated for each participant. Data were analysed by multivariate logistic regression. There was some evidence of an association between respiratory outcomes and mine fire PM_2.5 exposure. Chronic cough was associated with an odds ratio (OR) of 1.13 (95% confidence interval 1.03 to 1.23) per 10 μg/m³ increment in mean PM_2.5 and 1.07 (1.02 to 1.12) per 100 μg/m³ increment in peak PM_2.5. Current wheeze was associated with peak PM_2.5, OR = 1.06 (1.02 to 1.11) and chronic phlegm with mean PM_2.5 OR = 1.10 (1.00 to 1.20). Coal mine PM_2.5 smoke exposure was associated with increased odds of experiencing cough, phlegm and wheeze. Males, participants 18–64 years, and those residing in homes constructed from non-brick/concrete materials or homes with tin/metal roofs had higher estimated ORs. These findings contribute to the formation of public health policy responses.

Coal-mine fire-related fine particulate matter and medical-service utilization in Australia: a time-series analysis from the Hazelwood Health Study

Background

This study assessed the association between coal-mine-fire-related fine particulate matter (PM2.5) and medical-service utilization, following a 6-week coal-mine fire in Australia, in 2014. Areas in the immediate vicinity of the mine experienced hourly mine-fire-related PM2.5 concentrations of up to 3700 μg/m3.

Methods

Data on medical-service utilization were collected from the Medicare Benefits Schedule—a national database of payment for medical services. PM2.5 concentrations were modelled using atmospheric chemical transport modelling. Quasi-Poisson interrupted distributed lag time-series analysis examined the association between daily mine-fire-related PM2.5 concentrations and medical-service utilization, including General Practitioner (GP) consultations and respiratory, cardiovascular and mental health services. Confounders included seasonality, long-term trend, day of the week, maximum daily temperature and public holidays. Gender and age stratification were conducted.

Results

A 10-μg/m3 increase in PM2.5 was associated with an increased relative risk of service usage for all long and short GP consultations [11% (95% confidence interval: 7 to 15%)] and respiratory services [22% (4 to 43%)] in both men and women. Sex stratification found an increased relative risk in mental health consultations in men [32% (2 to 72%)] but not women. No associations were found for cardiovascular services in men or women.

Conclusions

Coal-mine-fire-related PM2.5 exposure was associated with increased use of medical services for GP consultations and respiratory services in men and women and mental health consultations in men. These findings can inform the development of future public-health-policy responses in the event of major air-pollution episodes.

Modeling Wildland Fire-Specific PM2.5 Concentrations for Uncertainty-Aware Health Impact Assessments

Wildland fire is a major emission source of fine particulate matter (PM_2.5), which has serious adverse health effects. Most fire-related health studies have estimated human exposures to PM_2.5 using ground observations, which have limited spatial/temporal coverage and could not separate PM_2.5 emanating from wildland fires from other sources. The Community Multiscale Air Quality (CMAQ) model has the potential to fill the gaps left by ground observations and estimate wildland fire-specific PM_2.5 concentrations, although the issues around systematic bias in CMAQ models remain to be resolved. To address these problems, we developed a two-step calibration strategy under the consideration of prediction uncertainties. In a case study of the eastern U.S. in 2014, we evaluated the calibration performance using three cross-validation methods, which consistently indicated that the prediction accuracy was improved with an R² of 0.47-0.64. In a health impact study based on the wildland fire-specific PM_2.5 predictions, we identified regions with excess respiratory hospital admissions due to wildland fire events and quantified the estimation uncertainty propagated from multiple components in health impact function. We concluded that the proposed calibration strategy could provide reliable wildland fire-specific PM_2.5 predictions and health burden estimates to support policy development for reducing fire-related risks.

Associations between respiratory health and ozone and fine particulate matter during a wildfire event

Wildfires have been increasing in frequency in the western United States (US) with the 2017 and 2018 fire seasons experiencing some of the worst wildfires in terms of suppression costs and air pollution that the western US has seen. Although growing evidence suggests respiratory exacerbations from elevated fine particulate matter (PM_2.5) during wildfires, significantly less is known about the impacts on human health of ozone (O₃) that may also be increased due to wildfires. Using machine learning, we created daily surface concentration maps for PM_2.5 and O₃ during an intense wildfire in California in 2008. We then linked these daily exposures to counts of respiratory hospitalizations and emergency department visits at the ZIP code level. We calculated relative risks of respiratory health outcomes using Poisson generalized estimating equations models for each exposure in separate and mutually-adjusted models, additionally adjusted for pertinent covariates. During the active fire periods, PM_2.5 was significantly associated with exacerbations of asthma and chronic obstructive pulmonary disease (COPD) and these effects remained after controlling for O₃. Effect estimates of O₃ during the fire period were non-significant for respiratory hospitalizations but were significant for ED visits for asthma (RR = 1.05 and 95% CI = (1.022, 1.078) for a 10 ppb increase in O₃). In mutually-adjusted models, the significant findings for PM_2.5 remained whereas the associations with O₃ were confounded. Adjusted for O₃, the RR for asthma ED visits associated with a 10 μg/m³ increase in PM_2.5 was 1.112 and 95% CI = (1.087, 1.138). The significant findings for PM_2.5 but not for O₃ in mutually-adjusted models is likely due to the fact that PM_2.5 levels during these fires exceeded the 24-hour National Ambient Air Quality Standard (NAAQS) of 35 μg/m³ for 4976 ZIP-code days and reached levels up to 6.073 times the NAAQS, whereas our estimated O₃ levels during the fire period only occasionally exceeded the NAAQS of 70 ppb with low exceedance levels. Future studies should continue to investigate the combined role of O₃ and PM_2.5 during wildfires to get a more comprehensive assessment of the cumulative burden on health from wildfire smoke.

Assessment of the Air Quality Health Index (AQHI) and four alternate AQHI-Plus amendments for wildfire seasons in British Columbia

OBJECTIVE

Wildfire smoke is an important source of air pollution associated with a range of cardiopulmonary health conditions. The Air Quality Health Index (AQHI) is the most widely used tool in Canada to communicate with the public about air pollution, but it may not adequately reflect health risks from wildfire smoke. The objective of this study was to evaluate the ability of the AQHI and four alternate AQHI-Plus amendments to predict adverse population health effects from wildfire smoke.

METHODS

The maximum 1-h values of the AQHI and the four amendments were calculated for each 48-h period of the wildfire seasons from 2010 to 2017 for 32 health units in British Columbia. Generalized Poisson models were used to estimate the association between these values and daily counts of five health outcomes: all-cause mortality; physician visits for all circulatory causes; visits for all respiratory causes, including asthma; asthma-specific visits; and dispensations of salbutamol sulfate (i.e., Ventolin®). Model fit was evaluated with the Akaike information criterion.

RESULTS

The AQHI and the four amendments were all associated with all five health outcomes. The AQHI exhibited best fit to the all-cause mortality and circulatory physician visits during all wildfire seasons, while the 1-h PM_2.5Only AQHI-Plus exhibited best fit to the asthma-related outcomes during all wildfire seasons.

CONCLUSION

Individuals with common respiratory conditions such as asthma and chronic obstructive pulmonary disease are particularly susceptible to wildfire smoke. As such, the 1-h PM_2.5Only AQHI-Plus amendment was recommended for communicating about potential health effects of air quality during wildfire seasons in BC.

Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS

In order to examine associations between asthma morbidity and local ambient air pollution in an area with relatively low levels of pollution, we conducted a time-series analysis of asthma hospital admissions and fine particulate matter pollution (PM_2.5) in and around Jackson, MS, for the period 2003 to 2011. Daily patient-level records were obtained from the Mississippi State Department of Health (MSDH) Asthma Surveillance System. Patient geolocations were aggregated into a grid with 0.1° × 0.1° resolution within the Jackson Metropolitan Statistical Area. Daily PM_2.5 concentrations were estimated via machine-learning algorithms with remotely sensed aerosol optical depth and other associated parameters as inputs. Controlling for long-term temporal trends and meteorology, we estimated a 7.2% (95% confidence interval 1.7-13.1%) increase in daily all-age asthma emergency room admissions per 10 μg/m³ increase in the 3-day average of PM_2.5 levels (current day and two prior days). Stratified analyses reveal significant associations between asthma and 3-day average PM_2.5 for males and blacks. Our results contribute to the current epidemiologic evidence on the association between acute ambient air pollution exposure and asthma morbidity, even in an area characterized by relatively good air quality.

The Associations Between Clinical Respiratory Outcomes and Ambient Wildfire Smoke Exposure Among Pediatric Asthma Patients at National Jewish Health, 2012-2015

Wildfires are a growing threat in the United States. At a population level, exposure to ambient wildfire smoke is known to be associated with severe asthma outcomes such as hospitalizations. However, little work has been done on subacute clinical asthma outcomes, especially in sensitive populations. This study retrospectively investigated associations between ambient wildfire smoke exposure and measures of lung function and asthma control, Forced Expiratory Volume in 1 Second (FEV1) and the Asthma Control Test (ACT) and Children's Asthma Control Test (CACT) test scores, during nonurgent clinic visits. The study population consisted of pediatric asthma patients (ages 4-21; n = 1,404 for FEV1 and n = 395 for ACT/CACT) at National Jewish Health, a respiratory referral hospital in Denver, Colorado, and therefore represents a more severe asthma phenotype than the general pediatric asthma population. Wildfire smoke-related PM2.5 at patients' residential ZIP codes was characterized using satellite-derived smoke polygons from NOAA's Hazard Mapping System combined with kriging of ground-based U.S. EPA monitors. Mixed effect models were used to estimate associations between clinical outcomes and smoke PM2.5 exposure, controlling for known risk factors and confounders. Among older children aged 12-21 we found that wildfire PM2.5 was associated with lower FEV1 the next day but higher FEV1 the day after. We found no associations between wildfire PM2.5 and FEV1 in younger children or between wildfire PM2.5 and asthma control measured by the ACT/CACT in all ages. We speculate that rescue medication usage by older children may decrease respiratory symptoms caused by wildfire smoke.

Fine particulate matter exposure and medication dispensing during and after a coal mine fire: A time series analysis from the Hazelwood Health Study

Limited research has examined the impacts of coal mine fire smoke on human health. The aim of this study was to assess the association between prolonged smoke PM_2.5 exposure from a brown coal mine fire that burned over a seven week period in 2014 and medications dispensed across five localities in South-eastern Victoria, Australia. Spatially resolved PM_2.5 concentrations were retrospectively estimated using a dispersion model coupled with a chemical transport model. Data on medications dispensed were collected from the national Pharmaceutical Benefits Schedule database for 2013-2016. Poisson distributed lag time series analysis was used to examine associations between daily mine fire-related PM_2.5 concentrations and daily counts of medications dispensed for respiratory, cardiovascular or psychiatric conditions. Factors controlled for included: seasonality, long-term trend, day of the week, maximum ambient temperature and public holidays. Positive associations were found between mine fire-related PM_2.5 and increased risks of medications dispensed for respiratory, cardiovascular and psychiatric conditions, over a lag range of 3-7 days. A 10 μg/m³ increase in coal mine fire-related PM_2.5 was associated with a 25% (95%CI 19-32%) increase in respiratory medications, a 10% (95%CI 7-13%) increase in cardiovascular medications and a 12% (95%CI 8-16%) increase in psychiatric medications dispensed. These findings have the potential to better prepare for and develop more appropriate public health responses in the event of future coal mine fires.

Machine Learning Approach To Estimate Hourly Exposure to Fine Particulate Matter for Urban, Rural, and Remote Populations during Wildfire Seasons

Exposure to wildfire smoke averaged over 24-hour periods has been associated with a wide range of acute cardiopulmonary events, but little is known about the effects of sub-daily exposures immediately preceding these events. One challenge for studying sub-daily effects is the lack of spatially and temporally resolved estimates of smoke exposures. Inexpensive and globally applicable tools to reliably estimate exposure are needed. Here we describe a Random Forests machine learning approach to estimate 1-hour average population exposure to fine particulate matter during wildfire seasons from 2010 to 2015 in British Columbia, Canada, at a 5 km × 5 km resolution. The model uses remotely sensed fire activity, meteorology assimilated from multiple data sources, and geographic/ecological information. Compared with observations, model predictions had a correlation of 0.93, root mean squared error of 3.2 μg/m³, mean fractional bias of 15.1%, and mean fractional error of 44.7%. Spatial cross-validation indicated an overall correlation of 0.60, with an interquartile range from 0.48 to 0.70 across monitors. This model can be adapted for global use, even in locations without air quality monitoring. It is useful for epidemiologic studies on sub-daily exposure to wildfire smoke and for informing public health actions if operationalized in near-real-time.

Applications of Space Technologies to Global Health: Scoping Review

BACKGROUND

Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations' Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health.

OBJECTIVE

The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges.

METHODS

We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs' Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified.

RESULTS

A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use.

CONCLUSIONS

Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

Changes in extreme events and the potential impacts on human health

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future.

IMPLICATIONS

Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.

Wildfire smoke exposure and human health: Significant gaps in research for a growing public health issue

Understanding the effect of wildfire smoke exposure on human health represents a unique interdisciplinary challenge to the scientific community. Population health studies indicate that wildfire smoke is a risk to human health and increases the healthcare burden of smoke-impacted areas. However, wildfire smoke composition is complex and dynamic, making characterization and modeling difficult. Furthermore, current efforts to study the effect of wildfire smoke are limited by availability of air quality measures and inconsistent air quality reporting among researchers. To help address these issues, we conducted a substantive review of wildfire smoke effects on population health, wildfire smoke exposure in occupational health, and experimental wood smoke exposure. Our goal was to evaluate the current literature on wildfire smoke and highlight important gaps in research. In particular we emphasize long-term health effects of wildfire smoke, recovery following wildfire smoke exposure, and health consequences of exposure in children.

Seasonal ambient particulate matter and population health outcomes among communities impacted by road dust in British Columbia, Canada

In recent years, many air quality monitoring programs have favored measurement of particles less than 2.5 µm (PM_2.5) over particles less than 10 µm (PM₁₀) in light of evidence that health impacts are mostly from the fine fraction. However, the coarse fraction (PM_10-2.5) may have independent health impacts that support continued measurement of PM₁₀ in some areas, such as those affected by road dust. The objective of this study was to evaluate the associations between different measures of daily PM exposure and two daily indicators of population health in seven communities in British Columbia, Canada, where road dust is an ongoing concern. The measures of exposure were PM₁₀, PM_2.5, PM_10-2.5, PM_2.5 adjusted for PM_10-2.5, and PM_10-2.5 adjusted for PM_2.5. The indicators of population health were dispensations of the respiratory reliever medication salbutamol sulfate and nonaccidental mortality. This study followed a time-series design using Poisson regression over a 2003-2015 study period, with analyses stratified by three seasons: residential woodsmoke in winter; road dust in spring; and wildfire smoke in summer. A random-effects meta-analysis was conducted to establish a pooled estimate. Overall, an interquartile range increase in daily PM_10-2.5 was associated with a 3.6% [1.6, 5.6] increase in nonaccidental mortality during the road dust season, which was reduced to 3.1% [0.8, 5.4] after adjustment for PM_2.5. The adjusted coarse fraction had no effect on salbutamol dispensations in any season. However, an interquartile range increase in PM_2.5 was associated with a 2.7% [2.0, 3.4] increase in dispensations during the wildfire season. These analyses suggest different impacts of different PM fractions by season, with a robust association between the coarse fraction and nonaccidental mortality in communities and periods affected by road dust. We recommend that PM₁₀ monitoring networks be maintained in these communities to provide feedback for future dust mitigation programs.

IMPLICATIONS

There was a significant association between daily concentrations of the coarse fraction and nonaccidental mortality during the road dust season, even after adjustment for the fine fraction. The acute and chronic health effects associated with exposure to the coarse fraction remain unclear, which supports the maintenance of PM₁₀ monitoring networks to allow for further research in communities affected by sources such as road dust.

Early Life Wildfire Smoke Exposure Is Associated with Immune Dysregulation and Lung Function Decrements in Adolescence

The long-term health effects of wildfire smoke exposure in pediatric populations are not known. The objectives of this study were to determine if early life exposure to wildfire smoke can affect parameters of immunity and airway physiology that are detectable with maturity. We studied a mixed-sex cohort of rhesus macaque monkeys that were exposed as infants to ambient wood smoke from a series of Northern California wildfires in the summer of 2008. Peripheral blood mononuclear cells (PBMCs) and pulmonary function measures were obtained when animals were approximately 3 years of age. PBMCs were cultured with either LPS or flagellin, followed by measurement of secreted IL-8 and IL-6 protein. PBMCs from a subset of female animals were also evaluated by Toll-like receptor (TLR) pathway mRNA analysis. Induction of IL-8 protein synthesis with either LPS or flagellin was significantly reduced in PBMC cultures from wildfire smoke-exposed female monkeys. In contrast, LPS- or flagellin-induced IL-6 protein synthesis was significantly reduced in PBMC cultures from wildfire smoke-exposed male monkeys. Baseline and TLR ligand-induced expression of the transcription factor, RelB, was globally modulated in PBMCs from wildfire smoke-exposed monkeys, with additional TLR pathway genes affected in a ligand-dependent manner. Wildfire smoke-exposed monkeys displayed significantly reduced inspiratory capacity, residual volume, vital capacity, functional residual capacity, and total lung capacity per unit of body weight relative to control animals. Our findings suggest that ambient wildfire smoke exposure during infancy results in sex-dependent attenuation of systemic TLR responses and reduced lung volume in adolescence.

Spatial and temporal estimates of population exposure to wildfire smoke during the Washington state 2012 wildfire season using blended model, satellite, and in situ data

In the western U.S., smoke from wild and prescribed fires can severely degrade air quality. Due to changes in climate and land management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of air pollutants in the western U.S. Hence, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools have been used in past studies to assess exposure to wildfire smoke: in situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations. Each of these exposure-estimation tools has associated strengths and weakness. We investigate the utility of blending these tools together to produce estimates of PM2.5 exposure from wildfire smoke during the Washington 2012 fire season. For blending, we use a ridge-regression model and a geographically weighted ridge-regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques by using leave-one-out cross validation. We find that predictions based on in situ monitors are more accurate for this particular fire season than the CTM simulations and satellite-based observations because of the large number of monitors present; therefore, blending provides only marginal improvements above the in situ observations. However, we show that in hypothetical cases with fewer surface monitors, the two blending techniques can produce substantial improvement over any of the individual tools.

Health outcomes associated with smoke exposure in Albuquerque, New Mexico, during the 2011 Wallow fire

OBJECTIVE

This study examined the association between PM2.5 levels and emergency department (ED) visits for selected health outcomes in Albuquerque, New Mexico, during the Wallow fire of 2011.

DESIGN

Measurements of 24-hour average concentrations of PM2.5 obtained from the City of Albuquerque were used to calculate wildfire smoke exposure in Albuquerque. Daily ED visits were collected by the New Mexico Department of Health from individual nonfederal licensed facilities in the Albuquerque area. Poisson regression was used to assess the relationship between ED visits for selected respiratory and cardiovascular conditions and varying levels of PM2.5 exposure.

SETTING

Albuquerque, New Mexico.

PARTICIPANTS

Patients visiting an ED for select conditions before, during, and after the wildfire.

MAIN OUTCOME MEASURE

Relative increase in ED visits for selected conditions during the wildfire period.

RESULTS

Analysis of PM2.5 exposure data and ED visits in Albuquerque before and during the Wallow fire indicated that compared with the period prior to the fire, there was an increased risk of ED visits for some respiratory and cardiovascular conditions during heavy smoke conditions, and risk varied by age and sex. The population of 65+ years was especially at risk for increased ED visits. There was a significantly increased risk of ED visits among the 65+ population for asthma (RR [relative rate] = 1.73, 95% confidence interval [CI] = 1.03-2.93) and for diseases of the veins, lymphatic and circulatory system (RR = 1.56, 95% CI = 1.00-2.43). For the age group of 20 to 64 years, there was a statistically significant increase in ED visits for diseases of pulmonary circulation (RR = 2.64, 95% CI = 1.42-4.9) and for cerebrovascular disease (RR = 1.69, 95% CI = 1.03-2.77).

CONCLUSIONS

High levels of PM2.5 exposure due to the Wallow fire were associated with increased ED visits for respiratory and cardiovascular conditions in Albuquerque. More effective and targeted preventive measures are necessary to reduce morbidity rates associated with wildfire smoke exposure among vulnerable populations.

Critical Review of Health Impacts of Wildfire Smoke Exposure

BACKGROUND

Wildfire activity is predicted to increase in many parts of the world due to changes in temperature and precipitation patterns from global climate change. Wildfire smoke contains numerous hazardous air pollutants and many studies have documented population health effects from this exposure.

OBJECTIVES

We aimed to assess the evidence of health effects from exposure to wildfire smoke and to identify susceptible populations.

METHODS

We reviewed the scientific literature for studies of wildfire smoke exposure on mortality and on respiratory, cardiovascular, mental, and perinatal health. Within those reviewed papers deemed to have minimal risk of bias, we assessed the coherence and consistency of findings.

DISCUSSION

Consistent evidence documents associations between wildfire smoke exposure and general respiratory health effects, specifically exacerbations of asthma and chronic obstructive pulmonary disease. Growing evidence suggests associations with increased risk of respiratory infections and all-cause mortality. Evidence for cardiovascular effects is mixed, but a few recent studies have reported associations for specific cardiovascular end points. Insufficient research exists to identify specific population subgroups that are more susceptible to wildfire smoke exposure.

CONCLUSIONS

Consistent evidence from a large number of studies indicates that wildfire smoke exposure is associated with respiratory morbidity with growing evidence supporting an association with all-cause mortality. More research is needed to clarify which causes of mortality may be associated with wildfire smoke, whether cardiovascular outcomes are associated with wildfire smoke, and if certain populations are more susceptible.

CITATION

Reid CE, Brauer M, Johnston FH, Jerrett M, Balmes JR, Elliott CT. 2016. Critical review of health impacts of wildfire smoke exposure. Environ Health Perspect 124:1334-1343; http://dx.doi.org/10.1289/ehp.1409277.

Evaluation of a spatially resolved forest fire smoke model for population-based epidemiologic exposure assessment

Exposure to forest fire smoke (FFS) is associated with multiple adverse health effects, mostly respiratory. Findings for cardiovascular effects have been inconsistent, possibly related to the limitations of conventional methods to assess FFS exposure. In previous work, we developed an empirical model to estimate smoke-related fine particulate matter (PM2.5) for all populated areas in British Columbia (BC), Canada. Here, we evaluate the utility of our model by comparing epidemiologic associations between modeled and measured PM2.5. For each local health area (LHA), we used Poisson regression to estimate the effects of PM2.5 estimates and measurements on counts of medication dispensations and outpatient physician visits. We then used meta-regression to estimate the overall effects. A 10 μg/m(3) increase in modeled PM2.5 was associated with increased sabutamol dispensations (RR=1.04, 95% CI 1.03-1.06), and physician visits for asthma (1.06, 1.04-1.08), COPD (1.02, 1.00-1.03), lower respiratory infections (1.03, 1.00-1.05), and otitis media (1.05, 1.03-1.07), all comparable to measured PM2.5. Effects on cardiovascular outcomes were only significant using model estimates in all LHAs during extreme fire days. This suggests that the exposure model is a promising tool for increasing the power of epidemiologic studies to detect the health effects of FFS via improved spatial coverage and resolution.

A statistical model for determining impact of wildland fires on Particulate Matter (PM₂.₅) in Central California aided by satellite imagery of smoke

As the climate in California warms and wildfires become larger and more severe, satellite-based observational tools are frequently used for studying impact of those fires on air quality. However little objective work has been done to quantify the skill these satellite observations of smoke plumes have in predicting impacts to PM2.5 concentrations at ground level monitors, especially those monitors used to determine attainment values for air quality under the Clean Air Act. Using PM2.5 monitoring data from a suite of monitors throughout the Central California area, we found a significant, but weak relationship between satellite-observed smoke plumes and PM2.5 concentrations measured at the surface. However, when combined with an autoregressive statistical model that uses weather and seasonal factors to identify thresholds for flagging unusual events at these sites, we found that the presence of smoke plumes could reliably identify periods of wildfire influence with 95% accuracy.

An Evaluation of the British Columbia Asthma Monitoring System (BCAMS) and PM2.5 Exposure Metrics during the 2014 Forest Fire Season

The British Columbia Asthma Monitoring System (BCAMS) tracks forest fire smoke exposure and asthma-related health outcomes, identifying excursions beyond expected daily counts. Weekly reports during the wildfire season support public health and emergency management decision-making. We evaluated BCAMS by identifying excursions for asthma-related physician visits and dispensations of the reliever medication salbutamol sulfate and examining their corresponding smoke exposures. A disease outbreak detection algorithm identified excursions from 1 July to 31 August 2014. Measured, modeled, and forecasted concentrations of fine particulate matter (PM_2.5) were used to assess exposure. We assigned PM_2.5 levels to excursions by choosing the highest value within a seven day window centred on the excursion day. Smoky days were defined as those with PM_2.5 levels ≥ 25 µg/m³. Most excursions (57%–71%) were assigned measured or modeled PM_2.5 concentrations of 10 µg/m³ or higher. Of the smoky days, 55.8% and 69.8% were associated with at least one excursion for physician visits and salbutamol dispensations, respectively. BCAMS alerted most often when measures of smoke exposure were relatively high. Better performance might be realized by combining asthma-related outcome metrics in a bivariate model.

Impact of smoke from prescribed burning: Is it a public health concern?

Given the increase in wildfire intensity and frequency worldwide, prescribed burning is becoming a more common and widespread practice. Prescribed burning is a fire management tool used to reduce fuel loads for wildfire suppression purposes and occurs on an annual basis in many parts of the world. Smoke from prescribed burning can have a substantial impact on air quality and the environment. Prescribed burning is a significant source of fine particulate matter (PM2.5 aerodynamic diameter<2.5µm) and these particulates are found to be consistently elevated during smoke events. Due to their fine nature PM2.5 are particularly harmful to human health. Here we discuss the impact of prescribed burning on air quality particularly focussing on PM2.5. We have summarised available case studies from Australia including a recent study we conducted in regional Victoria, Australia during the prescribed burning season in 2013. The studies reported very high short-term (hourly) concentrations of PM2.5 during prescribed burning. Given the increase in PM2.5 concentrations during smoke events, there is a need to understand the influence of prescribed burning smoke exposure on human health. This is important especially since adverse health impacts have been observed during wildfire events when PM2.5 concentrations were similar to those observed during prescribed burning events. Robust research is required to quantify and determine health impacts from prescribed burning smoke exposure and derive evidence based interventions for managing the risk.

IMPLICATIONS

Given the increase in PM2.5 concentrations during PB smoke events and its impact on the local air quality, the need to understand the influence of PB smoke exposure on human health is important. This knowledge will be important to inform policy and practice of the integrated, consistent, and adaptive approach to the appropriate planning and implementation of public health strategies during PB events. This will also have important implications for land management and public health organizations in developing evidence based objectives to minimize the risk of PB smoke exposure.

Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning

Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11 statistical algorithms and 29 predictor variables. The variables included CTM output, three measures of satellite aerosol optical depth, distance to the nearest fires, meteorological data, and land use, traffic, spatial location, and temporal characteristics. The generalized boosting model (GBM) with 29 predictor variables had the lowest CV root mean squared error and a CV-R2 of 0.803. The most important predictor variable was the Geostationary Operational Environmental Satellite Aerosol/Smoke Product (GASP) Aerosol Optical Depth (AOD), followed by the CTM output and distance to the nearest fire cluster. Parsimonious models with various combinations of fewer variables also predicted PM2.5 well. Using machine learning algorithms to combine spatiotemporal data from satellites and CTMs can reliably predict PM2.5 concentrations during a major wildfire event.

Climate change primer for respirologists

Climate change is already affecting the cardiorespiratory health of populations around the world, and these impacts are expected to increase. The present overview serves as a primer for respirologists who are concerned about how these profound environmental changes may affect their patients. The authors consider recent peer-reviewed literature with a focus on climate interactions with air pollution. They do not discuss in detail cardiorespiratory health effects for which the potential link to climate change is poorly understood. For example, pneumonia and influenza, which affect >500 million people per year, are not addressed, although clear seasonal variation suggests climate-related effects. Additionally, large global health impacts in low-resource countries, including migration precipitated by environmental change, are omitted. The major cardiorespiratory health impacts addressed are due to heat, air pollution and wildfires, shifts in allergens and infectious diseases along with respiratory impacts from flooding. Personal and societal choices about carbon use and fossil energy infrastructure should be informed by their impacts on health, and respirologists can play an important role in this discussion.