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The British Columbia Asthma Prediction System (BCAPS): A Surveillance System to Forecast the Public Health Impacts of Wildfire Smoke

机译:不列颠哥伦比亚省哮喘预测系统(BCAPS):一种监视系统,可预测野火烟对公共健康的影响

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Smoke from severe wildfires during the summers of 2015 and 2017 affected most of the population of British Columbia (BC), Canada. Asthma-related health outcomes are consistently elevated when populations are exposed to wildfire smoke in BC. Timely information during smoke events is important to inform the actions of public health authorities. We developed a surveillance system using short-term wildfire smoke forecasts to predict the potential health impacts of smoke over the coming days and provide this information to public health authorities in easy-to-interpret daily reports. The BCAPS framework is modular such that different data, modelling approaches, and visualizations can be applied. We used daily fine particulate matter (PM2.5) measurements, daily counts of asthma-related population health outcomes, and PM2.5 forecasts to predict and visualize smoke exposures and their health impacts across different geographic areas over the coming 48 hours. We applied BCAPS retrospectively during a 2015 smoke event using a Bayesian latent process model to forecast health outcomes. We prospectively applied BCAPS in 2017 using random forest models to predict PM2.5 exposure and health outcomes. Daily PM2.5 measurements ranged from 0.03 μg/m3 to 301.2 μg/m3 during the 2015 event and from 0.05 μg/m3 to 293.8 μg/m3 in 2017. Daily PM2.5 and daily counts of asthma-related physician visits and medication dispensations were increased during smoky periods in 2015 and 2017. In general, BCAPS predicted the smoke-related increases in asthma outcomes with good accuracy, though performance was dependant on the performance of the smoke forecasts. In 2017 there was a marked decrease in population response to smoke towards the end of the season even though PM2.5 concentrations remained high. Integrating data from multiple sources into a modular framework such as BCAPS can usefully predict the health impacts of smoke exposure in a timely manner to inform public health decision-making and action.
机译:2015年和2017年夏季,野火造成的浓烟影响了加拿大不列颠哥伦比亚(BC)的大多数人口。当人们在卑诗省接触野火烟雾时,与哮喘有关的健康结果将持续提高。烟雾事件期间的及时信息对于通知公共卫生当局的行为很重要。我们开发了使用短期野火烟雾预报的监视系统,以预测未来几天烟雾对健康的潜在影响,并将这些信息通过易于理解的每日报告提供给公共卫生部门。 BCAPS框架是模块化的,因此可以应用不同的数据,建模方法和可视化。我们使用每日细颗粒物(PM2.5)测量,与哮喘相关的人口健康结局的每日计数以及PM2.5预测来预测和可视化未来48小时内不同地理区域的烟尘暴露及其对健康的影响。我们在2015年吸烟事件中使用贝叶斯潜在过程模型回顾性地应用了BCAPS,以预测健康结果。我们使用随机森林模型在2017年前瞻性地应用了BCAPS,以预测PM2.5暴露和健康结果。 2015年事件期间的每日PM2.5测量范围为0.03μg/ m3至301.2μg/ m3,2017年为0.05μg/ m3至293.8μg/ m3。每日PM2.5以及与哮喘相关的医师就诊和配药量的每日计数在2015年和2017年的烟雾弥漫期间,烟尘排放量有所增加。总体而言,BCAPS预测与烟气有关的哮喘结局的准确性较高,尽管其表现取决于烟气预测的表现。 2017年末,尽管PM2.5浓度仍然很高,但人口对烟气的反应明显下降。将来自多个来源的数据集成到BCAPS等模块化框架中,可以及时有效地预测烟雾暴露对健康的影响,从而为公共卫生决策和行动提供信息。

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