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

Abstract

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 (PM2.5) were used to assess exposure. We assigned PM2.5 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 PM2.5 levels ≥ 25 µg/m3. Most excursions (57%-71%) were assigned measured or modeled PM2.5 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.

Keywords: asthma; environmental exposure; evaluation studies; forest fire smoke; particulate matter; public health surveillance.

Figure 1

Sample Health Service Delivery Area (HSDA) summary page from a 2014 BC Asthma Monitoring System (BCAMS) report on outpatient physician visits. The upper panel shows expected daily counts of an asthma indicator, based on data from June 2012 onwards, and observed counts with any excursions highlighted. An alerting algorithm was used to identify excursions from the expected values, where counts over the 95th percentile of the expected distribution were considered unusual, and counts over the 99.9th percentile of the expected distribution were rare. The lower panel shows the different PM_2.5 metrics. The plot for BlueSky shows the prediction made 48 h previously for the current day.

Figure 2

Health Service Delivery Areas in British Columbia and locations of fires during July and August, 2014 from the Hazard Mapping System at the United States National Oceanic and Atmospheric Administration.

Figure 3

Exposure metrics timeline showing data used to calculate 24-h average exposure levels for Day 0.

Figure 4

Percentage of excursions by highest PM_2.5 level (µg/m³) within the seven-day window for each exposure metric.