Faculty mentor/PI email address

jim010@aol.cm

Is your research Teaching and Learning based?

1

Keywords

Wildfire smoke; PM2.5; Air Quality Index; Asthma; COPD; Emergency Department surge; Systems forecasting; Complex adaptive systems; Environmental health; Operational readiness; Learning systems

Date of Presentation

5-6-2026 12:00 AM

Poster Abstract

Background: Wildfire smoke produces abrupt increases in PM2.5 and Air Quality Index (AQI) levels. Event-based and multi-season studies demonstrate short-term increases in asthma-related Emergency Department (ED) visits, with additional evidence supporting increased utilization for broader respiratory disease and chronic lower respiratory disease (including COPD) (Reid et al., 2016; Liu et al., 2015; Stowell et al., 2025; CDC, 2023).

Objective: To synthesize current evidence linking wildfire smoke to ED respiratory surge and to propose a systems forecasting model that translates environmental signals into structured operational stabilization within a complex adaptive system (CAS).

Methods (Review & Model Development): Narrative synthesis of event-based surge analyses, time-series studies, and systematic reviews examining wildfire PM2.5 exposure and ED utilization, followed by development of an operational forecasting-to-prevention framework.

Results (Synthesis): Evidence consistently demonstrates reproducible increases in asthma ED visits during wildfire smoke exposure, with lag effects typically occurring same-day or within 24–48 hours. Nonlinear exposure-response relationships suggest threshold effects relevant to operational trigger development.

Conclusion: Wildfire smoke events reveal predictable environmental-to-clinical signal translation. Systems forecasting is the concept of reframing these large system data signals towards structured prevention and adaptive learning.

Disciplines

Disorders of Environmental Origin | Emergency Medicine | Medicine and Health Sciences | Respiratory Tract Diseases

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May 6th, 12:00 AM

Wildfires and Emergency Department Respiratory Surge: Brief Review, Systems Forecasting Implications and Recommendations for Research

Background: Wildfire smoke produces abrupt increases in PM2.5 and Air Quality Index (AQI) levels. Event-based and multi-season studies demonstrate short-term increases in asthma-related Emergency Department (ED) visits, with additional evidence supporting increased utilization for broader respiratory disease and chronic lower respiratory disease (including COPD) (Reid et al., 2016; Liu et al., 2015; Stowell et al., 2025; CDC, 2023).

Objective: To synthesize current evidence linking wildfire smoke to ED respiratory surge and to propose a systems forecasting model that translates environmental signals into structured operational stabilization within a complex adaptive system (CAS).

Methods (Review & Model Development): Narrative synthesis of event-based surge analyses, time-series studies, and systematic reviews examining wildfire PM2.5 exposure and ED utilization, followed by development of an operational forecasting-to-prevention framework.

Results (Synthesis): Evidence consistently demonstrates reproducible increases in asthma ED visits during wildfire smoke exposure, with lag effects typically occurring same-day or within 24–48 hours. Nonlinear exposure-response relationships suggest threshold effects relevant to operational trigger development.

Conclusion: Wildfire smoke events reveal predictable environmental-to-clinical signal translation. Systems forecasting is the concept of reframing these large system data signals towards structured prevention and adaptive learning.

 

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