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Water Res. 2012 May 1;46(7):2176-86. doi: 10.1016/j.watres.2012.01.033. Epub 2012 Feb 2.

Using rapid indicators for Enterococcus to assess the risk of illness after exposure to urban runoff contaminated marine water.

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University of California Berkeley, School of Public Health, 101 Haviland, MC# 7358, Berkeley, CA 94720-7358, USA.



Traditional fecal indicator bacteria (FIB) measurement is too slow (>18 h) for timely swimmer warnings.


Assess relationship of rapid indicator methods (qPCR) to illness at a marine beach impacted by urban runoff.


We measured baseline and two-week health in 9525 individuals visiting Doheny Beach 2007-08. Illness rates were compared (swimmers vs. non-swimmers). FIB measured by traditional (Enterococcus spp. by EPA Method 1600 or Enterolert™, fecal coliforms, total coliforms) and three rapid qPCR assays for Enterococcus spp. (Taqman, Scorpion-1, Scorpion-2) were compared to health. Primary bacterial source was a creek flowing untreated into ocean; the creek did not reach the ocean when a sand berm formed. This provided a natural experiment for examining FIB-health relationships under varying conditions.


We observed significant increases in diarrhea (OR 1.90, 95% CI 1.29-2.80 for swallowing water) and other outcomes in swimmers compared to non-swimmers. Exposure (body immersion, head immersion, swallowed water) was associated with increasing risk of gastrointestinal illness (GI). Daily GI incidence patterns were different: swimmers (2-day peak) and non-swimmers (no peak). With berm-open, we observed associations between GI and traditional and rapid methods for Enterococcus; fewer associations occurred when berm status was not considered.


We found increased risk of GI at this urban runoff beach. When FIB source flowed freely (berm-open), several traditional and rapid indicators were related to illness. When FIB source was weak (berm-closed) fewer illness associations were seen. These different relationships under different conditions at a single beach demonstrate the difficulties using these indicators to predict health risk.

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