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

Wildfire-induced fine particulate matter (PM2.5) poses a growing public health risk. To examine public responses to wildfire smoke, we analyzed smoke PM2.5 and Google Trends data across 11 Designated Market Areas (DMAs) in California from 2016 to 2020. Scaled Relative Search Interest (RSI) for 'air pollution' and 'air purifier' was used as a proxy for public awareness and preparedness. Applying a Bayesian spatiotemporal distributed lag model, we found that a one-unit increase in smoke PM2.5 (6.6 μg/m3) was associated with 149% (95% Credible Interval (CrI): 107%, 486%) higher 'air pollution' searches and 34% (95% CrI: 3%, 76%) and 68% (95% CrI: 26%, 123%) higher 'air purifier' searches over the first two weeks, respectively. Among all DMAs, Palm Springs showed the strongest responses. Public search responses were amplified under higher temperature and pressure but decreased with higher wind speed and humidity. Communities with greater socioeconomic vulnerability exhibited lower search interest in both awareness- and preparedness-related terms. These findings highlight the need for timely, targeted, and equitable public communication strategies that align with real-time environmental conditions and improve access to protective resources among vulnerable populations.