Spatiotemporal Analysis of Human Response to Wildfire Events and PM2.5 Exposure

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Overview

Wildfire-induced PM2.5 poses an increasing public health risk due to the rising frequency and intensity of wildfires. However, its health impacts remain poorly understood, largely because of the temporal and spatial heterogeneity of PM2.5 effects. In this paper, we used Relative Search Interest (RSI) data from Google Trends to assess public response to smoke PM2.5. We also collected smoke PM2.5 concentration in 12 Designated Market Areas (DMAs) of California, together with the environmental and socioeconomic characteristics, from 2016 to 2020. We developed a Bayesian spatiotemporal distributed lag model to examine the effects of smoke PM2.5 exposure on human behavior and how location-specific environmental conditions and social vulnerabilities modified these effects over time. We found that smoke PM2.5 effects persisted significantly for up to two weeks and were amplified by wildfire scale, temperature, humidity, and atmospheric pressure but mitigated by wind speed. Additionally, individuals experiencing poverty or lacking health insurance were more sensitive to the increase of smoking PM2.5, while racial/ethnic minorities and those with limited mobility or English proficiency were less sensitive. The disparities in people's response to wildfire smoke, combined with inequalities in health vulnerability, underscore the importance of developing equity-focused, location-specific environmental policies to mitigate the health impacts of wildfire smoke.