A simulation model of building intervention impacts on indoor environmental quality, pediatric asthma, and costs

Abstract

Background: Although indoor environmental conditions can affect pediatric asthmatic patients, few studies have characterized the effect of building interventions on asthma-related outcomes. Simulation models can evaluate such complex systems but have not been applied in this context.

Objective: We sought to evaluate the impact of building interventions on indoor environmental quality and pediatric asthma health care use, and to conduct cost comparisons between intervention and health care costs and energy savings.

Methods: We applied our previously developed discrete event simulation model (DEM) to simulate the effect of environmental factors, medication compliance, seasonality, and medical history on (1) pollutant concentrations indoors and (2) asthma outcomes in low-income multifamily housing. We estimated health care use and costs at baseline and subsequent to interventions, and then compared health care costs with energy savings and intervention costs.

Results: Interventions, such as integrated pest management and repairing kitchen exhaust fans, led to 7% to 12% reductions in serious asthma events with 1- to 3-year payback periods. Weatherization efforts targeted solely toward tightening a building envelope led to 20% more serious asthma events, but bundling with repairing kitchen exhaust fans and eliminating indoor sources (eg, gas stoves or smokers) mitigated this effect.

Conclusion: Our pediatric asthma model provides a tool to prioritize individual and bundled building interventions based on their effects on health and costs, highlighting the tradeoffs between weatherization, indoor air quality, and health. Our work bridges the gap between clinical and environmental health sciences by increasing physicians' understanding of the effect that home environmental changes can have on their patients' asthma.

Keywords: Air pollution; DEM; Discrete event simulation model; ED; Emergency department; FEV(1)%; IPM; Integrated pest management; MEPS; Medical Expenditure Panel Survey; NO(2); Nitrogen dioxide; PM(2.5); Particulate matter less than 2.5 μm in diameter; Percent predicted forced expiratory volume in 1 second; allergen; asthma; discrete event simulation; energy savings; green building; housing; indoor air; intervention; lung function.

Figure 1

Schematic of pediatric asthma simulation model

Figure 2

Percent change in pollutant concentrations (A. NO₂ and B. PM_2.5) for each intervention scenario compared to baseline scenario.

Figure 3

Percent change in health outcomes for each intervention compared to the baseline scenario. A) asthma symptom days include days with any symptom, including wheeze, cough, night awakenings; B) serious events include asthma hospitalizations, emergency room visits and clinic visits. Asthma outcomes reflect changes in exposure to NO₂, PM_2.5, cockroach allergen and damp homes.

Figure 4

Changes in costs of healthcare utilization for each intervention compared to baseline averaged over all asthmatics