Climate Change, Landscape Fires, and Human Health: A Global Perspective.

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

Protecting Cardiovascular Health From Wildfire Smoke.

Wildfire smoke is a rapidly growing threat to global cardiovascular health. We review the literature linking wildfire smoke exposures to cardiovascular effects. We find substantial evidence that short-term exposures are associated with key cardiovascular outcomes, including mortality, hospitalization, and acute coronary syndrome. Wildfire smoke exposures will continue to increase over the majority of Earth's surface. For example, the United States alone has experienced a 5-fold increase in annual area burned since 1972, with 82 million individuals estimated to be exposed to wildfire smoke by midcentury. The associated rise in excess morbidity and mortality constitutes a growing global public health crisis. Fortunately, the effect of wildfire smoke on cardiovascular health is modifiable at the individual and population levels through specific interventions. Health systems therefore have an opportunity to help safeguard patients from smoke exposures. We provide a roadmap of evidence-based interventions to reduce risk and protect cardiovascular health. Key interventions include preparing health systems for smoke events; identifying and educating vulnerable patients; reducing outdoor activities; creating cleaner air environments; using air filtration devices and personal respirators; and aggressive management of chronic diseases and traditional risk factors. Further research is needed to test the efficacy of interventions on reducing cardiovascular outcomes.

Cannabis Cultivation Facilities: A Review of Their Air Quality Impacts from the Occupational to Community Scale.

This review addresses knowledge gaps in cannabis cultivation facility (CCF) air emissions by synthesizing the peer-reviewed and gray literature. Focus areas include compounds emitted, air quality indoors and outdoors, odor assessment, and the potential health effects of emitted compounds. Studies suggest that ß-myrcene is a tracer candidate for CCF biogenic volatile organic compounds (BVOCs). Furthermore, ß-myrcene, d-limonene, terpinolene, and α-pinene are often reported in air samples collected in and around CCF facilities. The BVOC emission strength per dry weight of plant is higher than most conventional agriculture crops. Nevertheless, reported total CCF BVOC emissions are lower compared with VOCs from other industries. Common descriptors of odors coming from CCFs include "skunky", "herbal", and "pungent". However, there are few peer-reviewed studies addressing the odor impacts of CCFs outdoors. Atmospheric modeling has been limited to back trajectory models of tracers and ozone impact assessment. Health effects of CCFs are mostly related to odor annoyance or occupational hazards. We identify 16 opportunities for future studies, including an emissions database by strain and stage of life (growing cycle) and odor-related setback guidelines. Exploration and implementation of key suggestions presented in this work may help regulators and the industry reduce the environmental footprint of CCF facilities.

Development of methods for citizen scientist mapping of residential woodsmoke in small communities.

BACKGROUND: Residential wood burning is a major source of fine particulate matter (PM2.5) during winter and a leading contributor to air pollution. Exposure to woodsmoke PM2.5 is associated with many health effects, so it is important to characterize the magnitude and spatial variability in exposures. However, high infrastructure and maintenance costs of regulatory monitoring stations limit their spatial resolution and make monitoring infeasible for many small communities where woodsmoke may be prevalent. METHODS: Mobile monitoring was conducted with a nephelometer and multi-wavelength aethalometer, capable of identifying woodsmoke PM2.5, to capture spatially resolved data. This Combined Aethalometer and Nephelometer for Assessment of Woodsmoke (CANAW) method was evaluated in three pairs of communities in British Columbia, Canada. Measurements were also taken at fixed-site monitoring stations. Light scattering measured by a nephelometer (Bsp) was compared with gravimetric filter-based and beta-attenuation measures of PM2.5. The difference in absorbance of 370 nm and 880 nm wavelengths as measured by an aethalometer (delta C), was compared with the chemical woodsmoke tracer levoglucosan. RESULTS: Fixed site measurements of Bsp and delta C were comparable with established methods of monitoring PM2.5 and woodsmoke, respectively. Correlations in each tested relationship across all locations were high (r ≥ 0.93 in all cases). Mobile monitoring captured high spatial variation in woodsmoke PM2.5 and maps of average concentrations during monitoring were created to identify woodsmoke hotspots. CONCLUSION: Following the successful implementation of the mobile CANAW method, training materials were created and tested with lay volunteers along with an online mapping application. Volunteers were able to effectively operate the equipment, collect valuable data on woodsmoke concentrations, and map spatial patterns across their communities using the application. The CANAW method is a valuable option for advancing cost-effective data collection for residential woodsmoke in otherwise unmonitored communities, and to add spatial context to existing monitoring networks.

Snowfall, Temperature, and the Risk of Death From Myocardial Infarction: A Case-Crossover Study.

Previous research has associated snowfall with risk of myocardial infarction (MI). Most studies have been conducted in regions with harsh winters; it remains unclear whether snowfall is associated with risk of MI in regions with milder or more varied climates. A case-crossover design was used to investigate the association between snowfall and death from MI in British Columbia, Canada. Deaths from MI among British Columbia residents between October 15 and March 31 from 2009 to 2017 were identified. The day of each death from MI was treated as the case day, and each case day was matched to control days drawn from the same day of the week during the same month. Daily snowfall amount was assigned to case and control days at the residential address, using weather stations within 15 km of the residence and 100 m in elevation. In total, 3,300 MI case days were matched to 10,441 control days. Compared with days that had no snowfall, odds of death from MI increased 34% (95% confidence interval: 0%, 80%) on days with heavy snowfall (≥5 cm). In stratified analysis of deaths from MI as a function of both maximum temperature and snowfall, risk was significantly increased on snowfall days when the temperature was warmer.

Ambient Particulate Matter and Paramedic Assessments of Acute Diabetic, Cardiovascular, and Respiratory Conditions.

BACKGROUND: Ambulance data provide a useful source of population-based and spatiotemporally resolved information for assessing health impacts of air pollution in nonhospital settings. We used the clinical records of paramedics to quantify associations between particulate matter (PM2.5) and diabetic, cardiovascular, and respiratory conditions commonly managed by those responding to calls for emergency ambulance services. METHODS: We evaluated 394,217 paramedic assessments from three states in Southeastern Australia (population 13.2 million) and daily PM2.5 concentrations modeled at 5 km resolution from 2009 to 2014. We used a time-stratified, case-crossover analysis adjusted for daily meteorology to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for each clinical outcome per 10 µg/m increase in daily PM2.5 at lags from 0 to 2 days. RESULTS: Increased PM2.5 was associated with increased odds of paramedic assessments of hypoglycemia (OR = 1.07; 95% CI = 1.02, 1.12, lag 0), arrhythmia (OR = 1.05; 95% CI = 1.02, 1.09, lag 0), heart failure (OR = 1.07; 95% CI = 1.02, 1.12, lag 1), faint (OR = 1.09; 95% CI = 1.04-1.13, lag 0), asthma (OR = 1.06; 95% CI = 1.01, 1.11, lag 1), chronic obstructive pulmonary disease (OR = 1.07; 95% CI = 1.01, 1.13, lag 1), and croup (OR = 1.09; 95% CI = 1.02, 1.17). We did not identify associations with cerebrovascular outcomes. CONCLUSIONS: Ambulance data enable the evaluation of important clinical syndromes that are often initially managed in nonhospital settings. Daily PM2.5 was associated with hypoglycemia, faint, and croup in addition to the respiratory and cardiovascular outcomes that are better established.

Exposure to natural space, sense of community belonging, and adverse mental health outcomes across an urban region.

In a rapidly urbanizing world, identifying evidence-based strategies to support healthy design is essential. Although urban living offers increased access to critical resources and can help to mitigate climate change, densely populated neighborhood environments are often higher in many of the physical and psychological stressors that are detrimental to health, and lower in the social capital that is beneficial to health. One component of urban form that can reduce these stressors and improve social capital is nature: greenspace, such as parks and street trees, and bluespace, such as rivers and oceans. In this project, we applied measures from a Natural Space Index previously developed for the Vancouver, Canada census metropolitan area to explore the relationship between distinct measures of natural space and prevalence of (1) major depressive disorder, (2) negative mental health, and (3) psychological distress. In addition, we examined direct associations between natural space exposure and neighborhood social capital, as measured via self-reported sense of community belonging (SoC), as well as the potential mental health benefits of natural space mediated via SoC. Using data from the population-based, cross-sectional 2012 Canadian Community Health Survey-Mental Health (weighted n = 1,930,048), we found no direct associations between any measure of natural space and mental health in models adjusted for 11 demographic, socioeconomic, household arrangement, health, and urban design variables. However, publicly accessible neighborhood nature was associated with increased odds of higher SoC. A 1% increase in the percentage of natural space (combined greenspace and bluespace) within 500 m had an odds ratio [95% confidence interval] of 1.05 [1.00, 1.10] for very strong vs. very weak SoC and 1.04 [1.01, 1.08] for somewhat strong vs. very weak SoC. In addition, higher levels of SoC were associated with improvements in all three mental health outcomes. Mediation tests indicated significant indirect effects of both publicly accessible neighborhood nature variables on reductions in psychological distress and reduced odds of negative mental health via increased sense of SoC. This suggests that natural space has the potential to address the pressing issue of social isolation and, in turn, poor mental health faced by residents of dense urban environments.

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.

Beyond the Normalized Difference Vegetation Index (NDVI): Developing a Natural Space Index for population-level health research.

BACKGROUND: Natural spaces can provide psychological benefits to individuals, but population-level epidemiologic studies have produced conflicting results. Refining current exposure-assessment methods is necessary to advance our understanding of population health and to guide the design of health-promoting urban forms. OBJECTIVES: The aim of this study was to develop a comprehensive Natural Space Index that robustly models potential exposure based on the presence, form, accessibility, and quality of multiple forms of greenspace (e.g., parks and street trees) and bluespace (e.g., oceans and lakes). MATERIAL AND METHODS: The index was developed for greater Vancouver, Canada. Greenness presence was derived from remote sensing (NDVI/EVI); forms were extracted from municipal and private databases; and accessibility was based on restrictions such as private ownership. Quality appraisals were conducted for 200 randomly sampled parks using the Public Open Space Desktop Appraisal Tool (POSDAT). Integrating these measures in GIS, exposure was assessed for 60,242 postal codes using 100- to 1,600-m buffers based on hypothesized pathways to mental health. A single index was then derived using principal component analysis (PCA). RESULTS: Comparing NDVI with alternate approaches for assessing natural space resulted in widely divergent results, with quintile rankings shifting for 22-88% of postal codes, depending on the measure. Overall park quality was fairly low (mean of 15 on a scale of 0-45), with no significant difference seen by neighborhood-level household income. The final PCA identified three main sets of variables, with the first two components explaining 68% of the total variance. The first component was dominated by the percentages of public and private greenspace and bluespace and public greenspace within 250m, while the second component was driven by lack of access to bluespace within 1 km. CONCLUSIONS: Many current approaches to modeling natural space may misclassify exposures and have limited specificity. The Natural Space Index represents a novel approach at a regional scale with application to urban planning and policy-making.

Spatiotemporal patterns of paralytic shellfish toxins and their relationships with environmental variables in British Columbia, Canada from 2002 to 2012.

BACKGROUND: Harmful algal blooms produce paralytic shellfish toxins that accumulate in the tissues of filter feeding shellfish. Ingestion of these toxic shellfish can cause a serious and potentially fatal condition known as paralytic shellfish poisoning (PSP). The coast of British Columbia is routinely monitored for shellfish toxicity, and this study uses data from the monitoring program to identify spatiotemporal patterns in shellfish toxicity events and their relationships with environmental variables. METHODS: The dinoflagellate genus Alexandrium produces the most potent paralytic shellfish toxin, saxitoxin (STX). Data on all STX measurements were obtained from 49 different shellfish monitoring sites along the coast of British Columbia for 2002-2012, and monthly toxicity events were identified. We performed hierarchical cluster analysis to group sites that had events in similar areas with similar timing. Machine learning techniques were used to model the complex relationships between toxicity events and environmental variables in each group. RESULTS: The Strait of Georgia and the west coast of Vancouver Island had unique toxicity regimes. Out of the seven environmental variables used, toxicity in each cluster could be described by multivariable models including monthly sea surface temperature, air temperature, sea surface salinity, freshwater discharge, upwelling, and photosynthetically active radiation. The sea surface salinity and freshwater discharge variables produced the strongest univariate models for both geographic areas. CONCLUSIONS: Applying these methods in coastal regions could allow for the prediction of shellfish toxicity events by environmental conditions. This has the potential to optimize biotoxin monitoring, improve public health surveillance, and engage the shellfish industry in helping to reduce the risk of PSP.

Remote sensing measurements of sea surface temperature as an indicator of Vibrio parahaemolyticus in oyster meat and human illnesses.

BACKGROUND: Vibrio parahaemolyticus (Vp) is a naturally occurring bacterium found in marine environments worldwide. It can cause gastrointestinal illness in humans, primarily through raw oyster consumption. Water temperatures, and potentially other environmental factors, play an important role in the growth and proliferation of Vp in the environment. Quantifying the relationships between environmental variables and indicators or incidence of Vp illness is valuable for public health surveillance to inform and enable suitable preventative measures. This study aimed to assess the relationship between environmental parameters and Vp in British Columbia (BC), Canada. METHODS: The study used Vp counts in oyster meat from 2002-2015 and laboratory confirmed Vp illnesses from 2011-2015 for the province of BC. The data were matched to environmental parameters from publicly available sources, including remote sensing measurements of nighttime sea surface temperature (SST) obtained from satellite readings at a spatial resolution of 1 km. Using three separate models, this paper assessed the relationship between (1) daily SST and Vp counts in oyster meat, (2) weekly mean Vp counts in oysters and weekly Vp illnesses, and (3) weekly mean SST and weekly Vp illnesses. The effects of salinity and chlorophyll a were also evaluated. Linear regression was used to quantify the relationship between SST and Vp, and piecewise regression was used to identify SST thresholds of concern. RESULTS: A total of 2327 oyster samples and 293 laboratory confirmed illnesses were included. In model 1, both SST and salinity were significant predictors of log(Vp) counts in oyster meat. In model 2, the mean log(Vp) count in oyster meat was a significant predictor of Vp illnesses. In model 3, weekly mean SST was a significant predictor of weekly Vp illnesses. The piecewise regression models identified a SST threshold of approximately 14oC for both model 1 and 3, indicating increased risk of Vp in oyster meat and Vp illnesses at higher temperatures. CONCLUSION: Monitoring of SST, particularly through readily accessible remote sensing data, could serve as a warning signal for Vp and help inform the introduction and cessation of preventative or control measures.

Associations between extreme precipitation and acute gastro-intestinal illness due to cryptosporidiosis and giardiasis in an urban Canadian drinking water system (1997-2009).

Drinking water related infections are expected to increase in the future due to climate change. Understanding the current links between these infections and environmental factors is vital to understand and reduce the future burden of illness. We investigated the relationship between weekly reported cryptosporidiosis and giardiasis (n = 7,422), extreme precipitation (>90th percentile), drinking water turbidity, and preceding dry periods in a drinking water system located in greater Vancouver, British Columbia, Canada (1997-2009) using distributed lag non-linear Poisson regression models adjusted for seasonality, secular trend, and the effect of holidays on reporting. We found a significant increase in cryptosporidiosis and giardiasis 4-6 weeks after extreme precipitation. The effect was greater following a dry period. Similarly, extreme precipitation led to significantly increased turbidity only after prolonged dry periods. Our results suggest that the risk of cryptosporidiosis and giardiasis increases with extreme precipitation, and that the effects are more pronounced after a prolonged dry period. Given that extreme precipitation events are expected to increase with climate change, it is important to further understand the risks from these events, develop planning tools, and build resilience to these future risks.

A latent process model for forecasting multiple time series in environmental public health surveillance.

This paper outlines a latent process model for forecasting multiple health outcomes arising from a common environmental exposure. Traditionally, surveillance models in environmental health do not link health outcome measures, such as morbidity or mortality counts, to measures of exposure, such as air pollution. Moreover, different measures of health outcomes are treated as independent, while it is known that they are correlated with one another over time as they arise in part from a common underlying exposure. We propose modelling an environmental exposure as a latent process, and we describe the implementation of such a model within a hierarchical Bayesian framework and its efficient computation using integrated nested Laplace approximations. Through a simulation study, we compare distinct univariate models for each health outcome with a bivariate approach. The bivariate model outperforms the univariate models in bias and coverage of parameter estimation, in forecast accuracy and in computational efficiency. The methods are illustrated with a case study using healthcare utilization and air pollution data from British Columbia, Canada, 2003-2011, where seasonal wildfires produce high levels of air pollution, significantly impacting population health. Copyright © 2016 John Wiley & Sons, Ltd.

Portable air cleaners should be at the forefront of the public health response to landscape fire smoke.

Landscape fires can produce large quantities of smoke that degrade air quality in both remote and urban communities. Smoke from these fires is a complex mixture of fine particulate matter and gases, exposure to which is associated with increased respiratory and cardiovascular morbidity and mortality. The public health response to short-lived smoke events typically advises people to remain indoors with windows and doors closed, but does not emphasize the use of portable air cleaners (PAC) to create private or public clean air shelters. High efficiency particulate air filters and electrostatic precipitators can lower indoor concentrations of fine particulate matter and improve respiratory and cardiovascular outcomes. We argue that PACs should be at the forefront of the public health response to landscape fire smoke events.

A proposed case-control framework to probabilistically classify individual deaths as expected or excess during extreme hot weather events.

BACKGROUND: Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada. RESULTS: The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather. CONCLUSIONS: This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.

Evaluation of different radon guideline values based on characterization of ecological risk and visualization of lung cancer mortality trends in British Columbia, Canada.

BACKGROUND: There is no safe concentration of radon gas, but guideline values provide threshold concentrations that are used to map areas at higher risk. These values vary between different regions, countries, and organizations, which can lead to differential classification of risk. For example the World Health Organization suggests a 100 Bq m(-3)value, while Health Canada recommends 200 Bq m(-3). Our objective was to describe how different thresholds characterized ecological radon risk and their visual association with lung cancer mortality trends in British Columbia, Canada. METHODS: Eight threshold values between 50 and 600 Bq m(-3) were identified, and classes of radon vulnerability were defined based on whether the observed 95(th) percentile radon concentration was above or below each value. A balanced random forest algorithm was used to model vulnerability, and the results were mapped. We compared high vulnerability areas, their estimated populations, and differences in lung cancer mortality trends stratified by smoking prevalence and sex. RESULTS: Classification accuracy improved as the threshold concentrations decreased and the area classified as high vulnerability increased. Majority of the population lived within areas of lower vulnerability regardless of the threshold value. Thresholds as low as 50 Bq m(-3) were associated with higher lung cancer mortality, even in areas with low smoking prevalence. Temporal trends in lung cancer mortality were increasing for women, while decreasing for men. CONCLUSIONS: Radon contributes to lung cancer in British Columbia. The results of the study contribute evidence supporting the use of a reference level lower than the current guideline of 200 Bq m(-3) for the province.

Air pollution events from forest fires and emergency department attendances in Sydney, Australia 1996-2007: a case-crossover analysis.

BACKGROUND: Severe air pollution generated by forest fires is becoming an increasingly frequent public health management problem. We measured the association between forest fire smoke events and hospital emergency department (ED) attendances in Sydney from 1996-2007. METHODS: A smoke event occurred when forest fires caused the daily citywide average concentration of particulate matter (PM10 or PM2.5) to exceed the 99th percentile of the entire study period. We used a time-stratified case-crossover design and conditional logistic regression models adjusted for meteorology, influenza epidemics, and holidays to estimate odds ratios (OR) and 95% confidence intervals (CI) for ED attendances on event days compared with non-event days for all non-trauma ED attendances and selected cardiorespiratory conditions. RESULTS: The 46 validated fire smoke event days during the study period were associated with same day increases in ED attendances for all non-trauma conditions (1.03, 95% CI 1.02, 1.04), respiratory conditions (OR 1.07, 95% CI 1.04, 1.10), asthma (OR 1.23, 95% CI 1.15, 1.30), and chronic obstructive pulmonary disease (OR 1.12, 95% CI 1.02, 1.24). Positive associations persisted for one to three days after the event. Ischaemic heart disease ED attendances were increased at a lag of two days (OR 1.07, 95% CI 1.01, 1.15) while arrhythmias had an inverse association at a lag of two days (OR 0.91, 95% CI 0.83, 0.99). In age-specific analyses, no associations present in children less than 15 years of age for any outcome, although a non-significant trend towards a positive association was seen with childhood asthma. A further association between smoke event and heart failure attendances was present for the 15-65 year age group, but not older adults at a lag of two days (OR 1.37 95% CI 1.05, 1.78). CONCLUSION: Smoke events were associated with an immediate increase in presentations for respiratory conditions and a lagged increase in attendances for ischaemic heart disease and heart failure. Respiratory impacts were either absent or considerably attenuated in those <15 years. Similar to previous studies we found inconsistent associations between fire smoke and cardiovascular diseases. Better characterisation of the spectrum of population health risks is needed to guide public heath responses to severe smoke events as this exposure becomes increasingly common with global climate change.

The health risks of marine biotoxins associated with high seafood consumption: Looking beyond the single dose, single outcome paradigm with a view towards addressing the needs of coastal Indigenous populations in British Columbia.

People who consume high quantities of seafood are at a heightened risk for marine biotoxin exposure. Coastal Indigenous peoples may experience higher levels of risk than the general population due to their reliance on traditional marine foods. Most evidence on the health risks associated with biotoxins focus on a single exposure at one point in time. There is limited research on other types of exposures that may occur among those who regularly consume large quantities of seafood. The objective of this review is to assess what is known about the unique biotoxin exposure risks associated with the consumption patterns of many coastal Indigenous populations. These risks include [1]: repeated exposure to low doses of a single or multiple biotoxins [2]; repeated exposures to high doses of a single or multiple biotoxins; and [3] exposure to multiple biotoxins at a single point in time. We performed a literature search and collected 23 recent review articles on the human health effects of different biotoxins. Using a narrative framework synthesis approach, we collated what is known about the health effects of the exposure risks associated with the putative consumption patterns of coastal Indigenous populations. We found that the health effects of repeated low- or high-dose exposures and the chronic health effects of marine biotoxins are rarely studied or documented. There are gaps in our understanding of how risks differ by seafood species and preparation, cooking, and consumption practices. Together, these gaps contribute to a relatively poor understanding of how biotoxins impact the health of those who regularly consume large quantities of seafood. In the context of this uncertainty, we explore how known and potential risks associated with biotoxins can be mitigated, with special attention to coastal Indigenous populations routinely consuming seafood. Overall, we conclude that there is a need to move beyond the single-dose single-outcome model of exposure to better serve Indigenous communities and others who consume high quantities of seafood.

The BC Radon Data Repository (BCRDR) and BC Radon Map: Integrating disparate data sources for improved public health communication.

SETTING: The potential for exposure to indoor radon varies dramatically across British Columbia (BC) due to varied geology. Individuals may struggle to understand their exposure risk and agencies may struggle to understand the value of population-level programs and policies to mitigate risk. INTERVENTION: The BC Centre for Disease Control (BCCDC) established the BC Radon Data Repository (BCRDR) to facilitate radon research, public awareness, and action in the province. The BCRDR aggregates indoor radon measurements collected by government agencies, industry professionals and organizations, and research and advocacy groups. Participation was formalized with a data sharing agreement, which outlines how the BCCDC anonymizes and manages the shared data integrated into the BCRDR. OUTCOMES: The BCRDR currently holds 38,733 measurements from 18 data contributors. The repository continues to grow with new measurements from existing contributors and the addition of new contributors. A prominent use of the BCRDR was to create the online, interactive BC Radon Map, which includes regional concentration summaries, risk interpretation messaging, and health promotion information. Anonymized BCRDR data are also available for external release upon request. IMPLICATIONS: The BCCDC leverages existing radon measurement programs to create a large and integrated database with wide geographic coverage. The development and application of the BCRDR informs public health research and action beyond the BCCDC, and the repository can serve as a model for other regional or national initiatives.

RéSUMé: LIEU: Le potentiel d'exposition au radon à l'intérieur des bâtiments varie beaucoup d'une région à l'autre de la Colombie-Britannique en raison de la géologie variée. Les particuliers peuvent avoir du mal à comprendre leur risque d'exposition, et les organismes, à comprendre l'utilité des programmes et des politiques populationnels pour atténuer le risque. INTERVENTION: Le BC Centre for Disease Control (« le Centre ¼) a créé un organe d'archivage, le BC Radon Data Repository (BCRDR), pour faciliter la recherche, l'information, la sensibilisation du public et l'action liées au radon dans la province. Le BCRDR totalise les relevés du radon à l'intérieur des bâtiments pris par les organismes gouvernementaux, les professionnels et les organismes de l'industrie, ainsi que les groupes de recherche et de revendication. La participation est officialisée par un accord de partage de données qui décrit comment le Centre anonymise et gère les données communes du BCRDR. RéSULTATS: Le BCRDR contient actuellement 38 733 relevés de 18 contributeurs de données. Il continue de croître, avec de nouveaux relevés venant de contributeurs existants et l'ajout de nouveaux contributeurs. Il a servi, entre autres, à créer une carte du radon interactive en ligne pour la Colombie-Britannique, avec des résumés des concentrations régionales, des messages d'interprétation du risque et des informations de promotion de la santé. Sur demande, les données anonymisées du BCRDR sont également disponibles pour diffusion externe. CONSéQUENCES: Le Centre a exploité les programmes de prise de relevés du radon existants pour créer une grande base de données intégrée ayant une vaste couverture géographique. Le développement et les applications du BCRDR éclairent la recherche et l'action en santé publique au-delà du Centre, et l'organe d'archivage peut servir de modèle pour d'autres initiatives régionales ou nationales.