predicting human dose-response relationships from multiple biological models: issues with...
TRANSCRIPT
Predicting human dose-response relationships from multiple
biological models:Issues with Cryptosporidium
parvum
Predicting human dose-response relationships from multiple
biological models:Issues with Cryptosporidium
parvum
Risk Assessment Consortium
Cryptosporidiosis: Introduction
• Cryptosporidium parvum– coccidian protozoan – recognized as human
pathogen in 1976
• In the 1990s– one of the leading known causes of
waterborne disease outbreaks– important OI among HIV (+) persons– important cause of diarrhea outbreaks in day
care centers
Outbreaks of Cryptosporidiosis Associated with Drinking Water - United States, 1984 - 1995
OREGON
WASHINGTON
TEXAS
WISCONSIN
GEORGIA
NEVADA
PENNSYLVANIA
CARROLLTON
1987 (13,000)
LAS VEGAS
1993 ( ? )
READING1991(551)
1994 (113)
WAWALLA WALLA
1992(3,000)
MEDFORD
TALENT&
MILWAUKEE
1993 (400,000)
1984 (2,000)
SAN ANTONIO
NEW MEXICO
Foodborne Outbreaks of Cryptosporidiosisin the United States
Suspect Food
Est.Cases Location
HowContaminated
Chicken Salad
Green Onions
Green/Fruit Salad
Apple Cider (homemade)
Apple Cider (commercial)
Minnesota
Washington
Washington DC
Maine
New York
15
54
101
160
31
Food Handler
? Food Handler / Field
Food Handler
Cattle Feces in Field
? Rinse Water
Sampling of Surface Water for Cryptosporidium
(LeChevallier 1988 - 1993)
67 treatment Plants14 states
sites pos. 60%-80%only 2 sites consistently negativemean of 2.4 oocysts per liter
Source water
54% of sites positive
87% of sites positive
Finished (Filtered Water)
(Rose et. al.)
Dose-response IntroductionDose-response Introduction
• The determination of the relationship between the magnitude of exposure (dose) to a chemical, biological or physical agent and the severity and/or frequency of associated adverse health effects (response).
• Relate the level of a biological agent ingested with the frequency of infection or disease
Dose-response IntroductionDose-response Introduction
• Relate the level of a biological agent ingested with the frequency of infection or disease
• A variety of endpoints may be considered
Dose-response IntroductionDose-response Introduction
• Pathogen, host and environment are all factors• Complex relationship to predict
What is the RAC?What is the RAC?
• An inter-agency, interdisciplinary group
• Working collectively to enhance communication and coordination between federal agencies
What is the RAC?What is the RAC?
• An inter-agency, interdisciplinary group
• Promoting the conduct of scientific research that will facilitate risk assessments and assist the regulatory agencies in fulfilling their specific food-safety risk management mandates.
Who are the members of the RAC?Who are the members of the RAC?
U.S. Department of Agriculture Animal and Plant Health Inspection Service Cooperative State Research, Education, and
Extension Service Agricultural Research Service Economic Research Service Food Safety and Inspection Service Office of Risk Assessment and Cost Benefit
Analysis
Environmental Protection Agency Office of Water
Office of Prevention, Pesticides and Toxic Substances
Office of Research and Development
Department of Commerce National Marine Fisheries Service
Department of Defense Veterinary Service Activity
Department of Health and Human Services Center for Veterinary Medicine, FDA
National Center for Food Safety and Technology, FDA
National Center for Toxicological Research, FDA
Centers for Disease Control and Prevention
National Institutes of Health
Center for Food Safety and Applied Nutrition, FDA
Office of Women’s Health, FDA
Understanding Microbial Dose-Response
Understanding Microbial Dose-Response
Efforts of the RACDose-response workgroupInterest in development of plausible dose-response
models
Understanding Microbial Dose-Response
Understanding Microbial Dose-Response
Efforts of the RACDose-response workgroup
Cooperative Agreements
Relating Numbers of Foodborne Pathogens to Human Illness
Why are we here today?Why are we here today?
• Cryptosporidium was selected for this meeting because the body of evidence is extensive
Why are we here today?Why are we here today?
• What lessons can we learn from Cryptosporidium dose-response modeling that can inform model systems for other pathogens?
• How useful are different biological models as a source of data for modeling human dose-response relationships?