Estimating the Acute Health Impacts of Fire‐Originated PM _2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs

摘要

Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision‐making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire‐related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire‐originated PM_(2.5)exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire‐originated PM_(2.5)and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: ?10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire‐originated PM_(2.5). Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context‐specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires. Plain Language Summary Health impact assessments are public health decision‐making tools that quantify the health impacts of environmental exposures by combining two key pieces of information: estimates of the population's level of exposure and a function describing the relationship between exposure and the risk of adverse health outcome(s). For wildfire smoke, an environmental exposure of increasing importance, it is largely unknown how different choices for these two inputs impact the magnitude and uncertainty of the health impacts estimated. To understand this, we evaluated the sensitivity of an impact assessment, which estimated the number of hospital admissions attributable to smoke exposure during the October 2017 California wildfires, to four different estimates of smoke exposure and two different health risk functions. We find that smoke exposure accounted for an estimated 308 excess respiratory and cardiovascular admissions. The health impact assessment is sensitive to the inputs selected, with the admissions estimates' magnitude most impacted by the health risk function and the uncertainty most impacted by the estimates of exposure. In order to estimate the health impacts of wildfires with greater certainty, we recommend using more informed and accurate estimates of smoke exposure and health risk functions that are specific to wildfire smoke. Key Points PM_(2.5)exposure during the 2017 California fires accounted for an estimated 308 excess respiratory and cardiovascular hospital admissions Health impact assessments, used to inform decision‐making processes, are sensitive to the exposure and epidemiologic inputs specified Accurate exposure estimates and context‐specific health risk functions estimate fire‐attributable health impacts with greater certainty