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The effects of indoor environmental exposures on pediatric asthma: a discrete event simulation model
M Patricia Fabian1, Natasha K Stout, Gary Adamkiewicz
1Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA. pfabian@bu.edu
Insights
This study developed a simulation model to assess how environmental factors impact childhood asthma in low-income housing. Improving ventilation reduced pollutant levels and healthcare use, showing simulation
Area of Science:
- Environmental health
- Pediatric pulmonology
- Computational epidemiology
Background:
- Childhood asthma is a prevalent chronic disease in the U.S., frequently leading to hospitalizations.
- Asthma exacerbations are linked to residential environmental stressors like allergens and air pollutants.
- Simulation modeling is underutilized for studying complex multifactorial diseases like asthma.
Purpose of the Study:
- To design and evaluate a discrete event simulation model for pediatric asthma.
- To investigate the impact of environmental factors on asthma exacerbations in school-aged children in low-income housing.
- To assess the utility of simulation modeling for evaluating building interventions.
Main Methods:
- Developed a discrete event simulation model focusing on environmental factors and asthma exacerbations.
- Linked environmental exposures (NO2, PM2.5, cockroach allergen, dampness) to lung function (FEV1%) and health outcomes.
- Simulated 50,000 children over 10 years, comparing model outputs to literature values.
Main Results:
- Model validation showed comparable pollutant concentrations and health outcome rates to existing literature.
- Simulated improvements in kitchen and bathroom exhaust fans led to reduced pollutant levels.
- Healthcare utilization rates decreased following simulated ventilation improvements.
Conclusions:
- A discrete event simulation model for pediatric asthma in low-income housing was successfully designed and evaluated.
- The model integrates environmental factors, medication compliance, and medical history to predict asthma outcomes.
- This simulation approach demonstrates value for evaluating building interventions and green building practices on health and costs.
Background:
In the United States, asthma is the most common chronic disease of childhood across all socioeconomic classes and is the most frequent cause of hospitalization among children. Asthma exacerbations have been associated with exposure to residential indoor environmental stressors such as allergens and air pollutants as well as numerous additional factors. Simulation modeling is a valuable tool that can be used to evaluate interventions for complex multifactorial diseases such as asthma but in spite of its flexibility and applicability, modeling applications in either environmental exposures or asthma have been limited to date.
Methods:
We designed a discrete event simulation model to study the effect of environmental factors on asthma exacerbations in school-age children living in low-income multi-family housing. Model outcomes include asthma symptoms, medication use, hospitalizations, and emergency room visits. Environmental factors were linked to percent predicted forced expiratory volume in 1 second (FEV1%), which in turn was linked to risk equations for each outcome. Exposures affecting FEV1% included indoor and outdoor sources of NO2 and PM2.5, cockroach allergen, and dampness as a proxy for mold.
Results:
Model design parameters and equations are described in detail. We evaluated the model by simulating 50,000 children over 10 years and showed that pollutant concentrations and health outcome rates are comparable to values reported in the literature. In an application example, we simulated what would happen if the kitchen and bathroom exhaust fans were improved for the entire cohort, and showed reductions in pollutant concentrations and healthcare utilization rates.
Conclusions:
We describe the design and evaluation of a discrete event simulation model of pediatric asthma for children living in low-income multi-family housing. Our model simulates the effect of environmental factors (combustion pollutants and allergens), medication compliance, seasonality, and medical history on asthma outcomes (symptom-days, medication use, hospitalizations, and emergency room visits). The model can be used to evaluate building interventions and green building construction practices on pollutant concentrations, energy savings, and asthma healthcare utilization costs, and demonstrates the value of a simulation approach for studying complex diseases such as asthma.
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