Suchergebnisse

A quantitative microbial risk assessment model was developed to simulate the role of recreational water contact in the transmission of cryptosporidiosis in a model Ontario community. Stochastic simulations were based on plausible modes of contamination of a pool (literature derived), river (site‐specific), and recreational lakes (literature derived). The highest estimated risks of infection were derived from the (highly contaminated) recreational lake scenario, considered the upper end for risk of infection for both children (10 infections per 1,000 swims [5‰: two infections per 1,000 swims; 95‰: three infections per 100 swims]) and adults (four infections per 1,000 swims [5‰: four infections per 1,000 swims; 95‰: one infection per 100 swims]). Simulating the likely Cryptosporidium oocyst concentration in a lane pool that a child would be exposed to following a diarrheal fecal release event resulted in the third highest mean risk of infection (four infections per 10,000 swims [5‰: three infections per 100,000; 95‰: 10 infections per 10,000 swims]). The findings from this study illustrate the need for systematic and standardized research to quantify Cryptosporidium oocyst levels in Canadian public pools and recreational beaches. There is also a need to capture the swimming practices of the Canadian public, including most common forms and frequency measures. The study findings suggest that swimming in natural swim environments and in pools following a recent fecal contamination event pose significant public health risks. When considering these risks relative to other modes of cryptosporidiosis transmission, they are significant.

Through the use of case‐control analyses and quantitative microbial risk assessment (QMRA), relative risks of transmission of cryptosporidiosis have been evaluated (recreational water exposure vs. drinking water consumption) for a Canadian community with higher than national rates of cryptosporidiosis. A QMRA was developed to assess the risk of Cryptosporidium infection through the consumption of municipally treated drinking water. Simulations were based on site‐specific surface water contamination levels and drinking water treatment log10 reduction capacity for Cryptosporidium. Results suggested that the risk of Cryptosporidium infection via drinking water in the study community, assuming routine operation of the water treatment plant, was negligible (6 infections per 1013 persons per day—5th percentile: 2 infections per 1015 persons per day; 95th percentile: 3 infections per 1012 persons per day). The risk is essentially nonexistent during optimized, routine treatment operations. The study community achieves between 7 and 9 log10Cryptosporidium oocyst reduction through routine water treatment processes. Although these results do not preclude the need for constant vigilance by both water treatment and public health professionals in this community, they suggest that the cause of higher rates of cryptosporidiosis are more likely due to recreational water contact, or perhaps direct animal contact. QMRA can be successfully applied at the community level to identify data gaps, rank relative public health risks, and forecast future risk scenarios. It is most useful when performed in a collaborative way with local stakeholders, from beginning to end of the risk analysis paradigm.