Association between Gastrointestinal Illness and Precipitation in Areas Impacted by Combined Sewer Systems: Utilizing a Distributed Lag Model

Combined sewer systems collect rainwater runoff, sewage, and industrial wastewater for transit to treatment facilities. With heavy precipitation, volumes can exceed capacity of treatment facilities, and wastewater discharges directly to receiving waters. These combined sewer overflows (CSOs) are a source of episodic pollution for downstream water users. We evaluate associations between heavy precipitation and emergency room (ER) visits for gastrointestinal illness (GI) in areas with and without exposure to CSOs in Massachusetts (MA) using a distributed lag model. We considered three regions for analysis: two exposed regions (with recreational and drinking water exposure) and one unexposed region. ER visits, obtained from the MA Department of Healthcare Finance, during 2003–2007 for GI diagnoses (ICD9-CM 001-009, 558.9, 787.0, 787.01, 787.03, 787.4, 787.9, 787.91) were aggregated by region of residence and date of admission to create a time series for each region. Precipitation and temperature was abstracted from National Climatic Data Center for regions and heavy precipitation events defined (daily precipitation ≥ 99th percentile). We assessed associations between ER visits and heavy precipitation events using a distributed lag poisson regression model, with an 8 day lag, adjusting for temperature and a natural spline for time to control for unmeasured covariates. In the drinking water exposed region, heavy precipitation events were associated with an increased cumulative relative risk for ER visits over the 8 days following an event (RR: 1.15 (95% CI: 1.02, 1.30)). Associations in the recreational water exposed region and unexposed region were generally null. Analysis was also conducted by age group and associations varied by age. With the expected increase in variability of rainfall due to climate change and aging infrastructure in parts of the U.S. it is important to understand the impact of heavy precipitation on human health. This abstract does not necessarily reflect EPA policy.