Use of Wildfire Smoke Forecasting Model to Mitigate Burden on a Population’s Health and Wellbeing

Abstract

Background Wildfires are a major source of fine particular matter and other air pollutants associated with adverse health outcomes. A number of methods are available to forecast wildfire plume transport, but there is no systematic public health program that mitigates the burden on a population’s wellbeing. Objective To evaluate the feasibility of a smoke forecasting system to mitigate health care utilization and societal cost attributed to a major wildfire. Methods Daily counts of emergency department (ED) visits for cardiorespiratory outcomes were obtained during the period of a major wildfire in North Carolina. Dispersion and chemical transport atmospheric models were used to estimate daily forecast predictions of smoke-related fine particular matter (PM2.5). For each day of the period, spatial regions likely to be impacted under the 24 h and 48 h forecast were determined, followed by the estimation of the expected daily counts in the absence of a smoke event and the subsequent calculation of the corresponding relative risk. Health burden due to smoke exposure was determined by the difference in RR with and without the forecast and was evaluated using the Environmental Benefits Mapping and Analysis Program for incidence of cardiorespiratory outcomes, school absences and lost work days. Results A reduction from 50% to 0% excess risk (per 100µg/m3 PM2.5) at lag 0 and from 20% to 1% at lag 1 was observed for asthma. Statewide hospitalization rate of ED visits associated with asthma was 19% with expected total cost of illness per individual of $10K and average hospital stay of 3 days for those 64 yrs and younger and $15.8K with 4.79 day average stay for 65 yrs and older. We will present the results on the corresponding reduction in health burden and the amount of time before the health savings are equal to the cost of remediation. Conclusion This study demonstrates the ability of forecasting to mitigate smoke-related health care utilization and social costs. Disclaimer: This abstract does not necessarily reflect U.S. EPA policy.