This study is the first to quantify the association between work-related injury compensations and exposure to summer temperatures according to physical demands of the occupation and this warrants further investigations. In the context of global warming, results can be used to estimate future impacts of summer outdoor temperatures on workers, as well as to plan preventive interventions.

Lyme disease is an emerging public health threat in Canada. In this context, rapid detection of new risk areas is essential for timely application of prevention and control measures. In Canada, information on Lyme disease risk is collected through three surveillance activities: active tick surveillance, passive tick surveillance, and reported human cases. However, each method has shortcomings that limit its ability to rapidly and reliably identify new risk areas. We investigated the relationships between risk signals provided by human cases, passive and active tick surveillance to assess the performance of tick surveillance for early detection of emerging risk areas. We used regression models to investigate the relationships between the reported human cases, Ixodes scapularis (Say; Acari: Ixodidae) ticks collected on humans through passive surveillance and the density of nymphs collected by active surveillance from 2009 to 2014 in the province of Quebec. We then developed new risk indicators and validated their ability to discriminate risk levels used by provincial public health authorities. While there was a significant positive relationship between the risk signals provided all three surveillance methods, the strongest association was between passive tick surveillance and reported human cases. Passive tick submissions were a reasonable indicator of the abundance of ticks in the environment (sensitivity and specificity [Se and Sp] < 0.70), but were a much better indicator of municipalities with more than three human cases reported over 5 yr (Se = 0.88; Sp = 0.90). These results suggest that passive tick surveillance provides a timely and reliable signal of emerging risk areas for Lyme disease in Canada.

Background: Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide.Objectives: We sought to compare the accuracy of three spatiotemporal models to predict summer ground-level O3 in Quebec, Canada.Methods: We developed a land-use mixed-effects regression (LUR) model based on readily available data (air quality and meteorological monitoring data, road networks information, latitude), a Bayesian maximum entropy (BME) model incorporating both O3 monitoring station data and the land-use mixed model outputs (BME-LUR), and a kriging method model based only on available O3 monitoring station data (BME kriging). We performed leave-one-station-out cross-validation and visually assessed the predictive capability of each model by examining the mean temporal and spatial distributions of the average estimated errors.Results: The BME-LUR was the best predictive model (R2 = 0.653) with the lowest root mean-square error (RMSE ;7.06 ppb), followed by the LUR model (R2 = 0.466, RMSE = 8.747) and the BME kriging model (R2 = 0.414, RMSE = 9.164).Conclusions: Our findings suggest that errors of estimation in the interpolation of O3 concentrations with BME can be greatly reduced by incorporating outputs from a LUR model developed with readily available data.Citation: Adam-Poupart A, Brand A, Fournier M, Jerrett M, Smargiassi A. 2014. Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy–LUR approaches. Environ Health Perspect 122:970–976; http://dx.doi.org/10.1289/ehp.1306566

The potential impacts of climate change (CC) on Occupational Health and Safety (OHS)have been studied a little in tropical countries, while they received no attention in northern industrialized countries with a temperate climate. This work aimed to establish an overview of the potential links between CC and OHS in those countries and to determine research priorities for Quebec, Canada. A narrative review of the scientific literature (2005-2010) was presented to a working group of international and national experts and stakeholders during a workshop held in 2010. The working group was invited to identify knowledge gaps, and a modified Delphi method helped prioritize research avenues. This process highlighted five categories of hazards that are likely to impact OHS in northern industrialized countries: heat waves/increased temperatures, air pollutants, UV radiation, extreme weather events, vector-borne/zoonotic diseases. These hazards will affect working activities related to natural resources (i.e. agriculture, fishing and forestry) and may influence the socioeconomic context (built environment and green industries), thus indirectly modifying OHS. From this consensus approach, three categories of research were identified: 1) Knowledge acquisition on hazards, target populations and methods of adaptation; 2) Surveillance of diseases/ accidents/occupational hazards; and 3) Development of new occupational adaptation strategies.