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Forecast-Based Interventions Can Reduce the Health and Economic Burden of Wildfires

Ana G. Rappold, Neal L. Fann, James Crooks, Jin Huang, Wayne E. Cascio, Robert B. Devlin, and David Diaz-Sanchez


December 29, 2014
The authors simulated public health forecast-based interventions during a wildfire smoke episode in rural North Carolina to show the potential for use of modeled smoke forecasts toward reducing the health burden and showed a significant economic benefit of reducing exposures. Daily and county wide intervention advisories were designed to occur when fine particulate matter (PM2.5) from smoke, forecasted 24 or 48 hours in advance, was expected to exceed a predetermined threshold. Three different thresholds were considered in simulations, each with three different levels of adherence to the advisories. Interventions were simulated in the adult population susceptible to health exacerbations related to the chronic conditions of asthma and congestive heart failure. Associations between Emergency Department (ED) visits for these conditions and daily PM2.5 concentrations under each intervention were evaluated. Triggering interventions at lower PM2.5 thresholds with good compliance yielded the greatest risk reduction. At the highest threshold levels interventions were ineffective in reducing health risks at any level of compliance. The economic benefit of effective interventions exceeded $1M in excess ED visits for asthma and heart failure, $2M in loss of productivity, $100K in respiratory conditions in children, and $42M due to excess mortality.
North America