AuthorDerby, Mary Patricia
Foodborne Disease Outbreaks
Poison Control Centers
Public Health Department
Committee ChairRanger-Moore, James
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractFoodborne illnesses continue to have a negative impact on the nation's health, accounting annually for an estimated 76 million illnesses, 325,000 hospitalizations, and 5,000 deaths in the United States. Syndromic surveillance systems that analyze pre-diagnostic data, such as pharmaceutical sales data are being used to monitor diarrheal disease. The purpose of this study is to evaluate the usefulness of a poison control center (PCC) data collection and triage system for early detection of increases in foodborne illnesses.Data on calls to the Arizona Poison and Drug Information Center (APDIC) reporting suspected foodborne illnesses, and Pima County Health Department (PCHD) enteric illness reports were obtained for July 1, 2002 - June 30, 2007. Prediction algorithms were constructed using the first two and a half years, and validated in the remaining two and a half years. Multiple outcomes were assessed using unadjusted and adjusted raw counts, five and seven day moving averages, and exponentially weighted moving averages. Sensitivity analyses were conducted to evaluate model performance. Increases in PCHD laboratory reports of enteric illnesses were used as a proxy measure for foodborne disease outbreaks.Over the five year study period there were 1,094 APDIC calls reporting suspected foodborne illnesses, and 2,433 PCHD enteric illness cases. Seventy-five percent of cases were reported to PCHD within 23 days of symptom onset. In contrast, 62% of callers contacted APDIC within 24 hours of symptom onset. Forty percent of PCHD cases were missing symptom onset dates, which necessitated constructing and validating predictive algorithms using only those PCHD cases with known symptom onset dates.None of the prediction models performed at sensitivity levels considered acceptable by public health department standards. However, it is possible that a temporal relationship actually exists, but data quality (lack of outbreak dates, and missing symptom onset dates) may have prevented its detection. The study suggests that current surveillance by PCCs is insufficient as a univariate model for syndromic surveillance of diarrheal illness because of low caller volume reporting suspected foodborne illnesses; this can be improved. Methods were discussed to utilize PCCs for active surveillance of foodborne illnesses that are of public health significance.