Estimating the primary etiologic agents in recreational freshwaters impacted by human sources of faecal contamination

Abstract

Epidemiology studies of recreational waters have demonstrated that swimmers exposed to faecally-contaminated recreational waters are at risk of excess gastrointestinal illness. Epidemiology studies provide valuable information on the nature and extent of health effects, the magnitude of risks, and how these risks are modified or associated with levels of faecal contamination and other measures of pollution. However, such studies have not provided information about the specific microbial agents that are responsible for the observed illnesses in swimmers. The objective of this work was to understand more fully the reported epidemiologic results from studies conducted on the Great Lakes in the US during 2003 and 2004 by identifying pathogens that could have caused the observed illnesses in those studies. We used a Quantitative Microbial Risk Assessment (QMRA) approach to estimate the likelihood of pathogen-induced adverse health effects. The reference pathogens used for this analysis were Norovirus, rotavirus, adenovirus, Cryptosporidium spp., Giardia lamblia, Campylobacter jejuni, Salmonella enterica, and Escherichia coli O157:H7. Two QMRA-based approaches were used to estimate the pathogen combinations that would be consistent with observed illness rates: in the first, swimming-associated gastrointestinal (GI) illnesses were assumed to occur in the same proportion as known illnesses in the US due to all non-foodborne sources, and in the second, pathogens were assumed to occur in the recreational waters in the same proportion as they occur in disinfected secondary effluent. The results indicate that human enteric viruses and in particular, Norovirus could have caused the vast majority of the observed swimming-associated GI illnesses during the 2003/2004 water epidemiology studies. Evaluation of the time-to-onset of illness strongly supports the principal finding and sensitivity analyses support the overall trends of the analyses even given their substantial uncertainties.