Heavy precipitation, drinking water source, and acute gastrointestinal illness in Philadelphia, 2015-2017

• Published in: PloS one 2020-02, Vol.15 (2), p.e0229258
• Main Authors: De Roos, Anneclaire J, Kondo, Michelle C, Robinson, Lucy F, Rai, Arjita, Ryan, Michael, Haas, Charles N, Lojo, José, Fagliano, Jerald A
• Format: Article
• Language: English
• Subjects: Airports; Ambient temperature; Analysis; Biology and Life Sciences; Confidence intervals; Contamination; Daily precipitation; Diarrhea; Diseases; Drinking behavior; Drinking water; Earth Sciences; Ecology and Environmental Sciences; Emergency medical care; Emergency medical services; Engineering schools; Environmental engineering; Gastrointestinal diseases; Health surveillance; Heavy precipitation; Intelligence gathering; Medical research; Medicine and Health Sciences; Microbial contamination; Microbiology; Pathogens; Poisson distribution; Postal codes; Precipitation; Proxy; Public health; Rivers; Runoff; Sewer systems; Spring (season); Spring precipitation; Statistical analysis; Stream flow; Studies; Time; Time series; Vomiting; Water; Water shortages; Water supply; Watersheds
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0229258

Runoff from heavy precipitation events can lead to microbiological contamination of source waters for public drinking water supplies. Philadelphia is a city of interest for a study of waterborne acute gastrointestinal illness (AGI) because of frequent heavy precipitation, extensive impervious landcover, and combined sewer systems that lead to overflows. We conducted a time-series analysis of the association between heavy precipitation and AGI incidence in Philadelphia, served by drinking water from Delaware River and Schuylkill River source waters. AGI cases on each day during the study period (2015-2017) were captured through syndromic surveillance of patients' chief complaint upon presentation at local emergency departments. Daily precipitation was represented by measurements at the Philadelphia International Airport and by modeled precipitation within the watershed boundaries, and we also evaluated stream flowrate as a proxy of precipitation. We estimated the association using distributed lag nonlinear models, assuming a quasi-Poisson distribution of the outcome variable and with adjustment for potential confounding by seasonal and long-term time trends, ambient temperature, day-of-week, and major holidays. We observed an association between heavy precipitation and AGI incidence in Philadelphia that was primarily limited to the spring season, with significant increases in AGI that peaked from 8 to 16 days following a heavy precipitation event. For example, the increase in AGI incidence related to airport precipitation above the 95th percentile (vs no precipitation) during spring reached statistical significance on lag day 7, peaked on day 16 (102% increase, 95% confidence interval: 16%, 252%), and declined while remaining significantly elevated through day 28. Similar associations were observed in analyses of watershed-specific precipitation in relation to AGI cases within the populations served by drinking water from each river. Our results suggest that heavy precipitation events in Philadelphia result in detectable local increases in waterborne AGI.