Inferences drawn from a risk assessment compared directly with a randomized trial of a home drinking water intervention.
Risk assessments and intervention trials have been used by the U.S. Environmental Protection Agency to estimate drinking water health risks. Seldom are both methods used concurrently. Between 2001 and 2003, illness data from a trial were collected simultaneously with exposure data, providing a unique opportunity to compare direct risk estimates of waterborne disease from the intervention trial with indirect estimates from a risk assessment. Comparing the group with water treatment (active) with that without water treatment (sham), the estimated annual attributable disease rate (cases per 10,000 persons per year) from the trial provided no evidence of a significantly elevated drinking water risk [attributable risk=-365 cases/year, sham minus active; 95% confidence interval (CI) , -2,555 to 1,825]. The predicted mean rate of disease per 10,000 persons per person-year from the risk assessment was 13.9 (2.5, 97.5 percentiles: 1.6, 37.7) assuming 4 log removal due to viral disinfection and 5.5 (2.5, 97.5 percentiles: 1.4, 19.2) assuming 6 log removal. Risk assessments are important under conditions of low risk when estimates are difficult to attain from trials. In particular, this assessment pointed toward the importance of attaining site-specific treatment data and the clear need for a better understanding of viral removal by disinfection. Trials provide direct risk estimates, and the upper confidence limit estimates, even if not statistically significant, are informative about possible upper estimates of likely risk. These differences suggest that conclusions about waterborne disease risk may be strengthened by the joint use of these two approaches. Key words: drinking water, gastrointestinal, intervention trial, microbial risk assessment, waterborne pathogens.
Eisenberg
Joseph N S
JN
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan 48104, USA. jnse@umich.edu
Hubbard
Alan
A
Wade
Timothy J
TJ
Sylvester
Matthew D
MD
LeChevallier
Mark W
MW
Levy
Deborah A
DA
Colford
John M
JM
D000465:Algorithms; D000818:Animals; D003458:Cryptosporidium; D004203:Disinfection; D005374:Filtration; D005872:Giardia; D006801:Humans; D007239:Infections / Q000453:epidemiology; D007484:Iowa / Q000453:epidemiology; D008954:Models, Biological; D018570:Risk Assessment; D014780:Viruses; D014871:Water Microbiology; D014881:Water Supply / Q000032:analysis*