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ESTIMATING THE SOURCES OF FOODBORNE ILLNESS IN THE UNITED STATES
Dana Cole, DVM, PhD Enteric Disease Epidemiology Branch, Division of Foodborne, Waterborne, and Environmental Diseases January 31st, 2012 National Center for Emerging and Zoonotic Infectious Diseases Enteric Diseases Epidemiology Branch
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Outline Background and purpose Where source attribution starts
Painting a clearer picture Looking forward
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Outline Background and purpose Where source attribution starts
Goal Questions Where source attribution starts Painting a clearer picture Looking forward
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“Art and science have their meeting point in method.”
Earl Edward George Bulwer-Lytton (1875) 4
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“Art and science have their meeting point in method.”
Earl Edward George Bulwer-Lytton (1875) ditto
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Our Overarching Goal To prevent illness and death by gathering and analyzing information to create collective knowledge and stop food problems before they happen
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Foodborne Illness Source Attribution: What is it?
My vision is a slide with the first 2 questions. Then next slide adds a picture, maybe of lots Of people frantically doing everything, saying the 3rd quote. Foodborne Illness Source Attribution: What is it? at·tri·bu·tion: [a-trə-byü-shən] The act of attributing, especially the act of establishing a particular person as the creator of a work of art. <The American Heritage® Dictionary of the English Language> The act of attributing, especially specifically the act of establishing a particular person food as the creator source of an work of art infection.
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Purpose: Inform food safety decision-making
Determine the most pressing food safety priorities Intervene to reduce illness at points in food chain where intervention can have the greatest impact Target prevention measures to meet long-term goals Measure progress toward food safety goals 8 8
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Attribution of Illnesses to Food Sources
We need to use new tools to understand today’s food safety challenges Using these tools, we will paint a clearer picture of foodborne illness source attribution 9
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Outline Background and purpose Where source attribution starts
Painting a clearer picture Looking forward
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Cycle of Foodborne Disease Control and Prevention
Surveillance Prevention Measures Epidemiologic Investigation Familiar cycle of foodborne disease control and prevention Applied Research
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Cycle of Foodborne Disease Control and Prevention
Surveillance OUTBREAK Prevention Measures Epidemiologic Investigation This is where attribution starts—at the time of an outbreak investigation. CDC has been doing this for decades. Applied Research
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Investigating the Source of Outbreaks
Escherichia coli O157 outbreaks in mid 1980’s and early 1990’s traced to ground beef Information used to guide interventions taken by regulatory agencies: Recommended minimum cooking temperature of hamburgers was raised Food Safety Inspection Service (FSIS): Implemented HACCP (Hazard Analysis and Critical Control Points) Made E. coli O157 an adulterant in ground beef 13
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Foodborne Disease Outbreak Surveillance System
fdoss Captures outbreak data on agents, foods, and settings responsible for illness Developed: 1967, standardized in 1973 Because: Outbreaks are the major way we learn what foods are causing illness and how to prevent it. Now: States report hundreds of outbreaks each year through the National Outbreak Reporting System (NORS). The data is used to determine pathogen-food combinations to target for prevention.
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Foodborne Disease Outbreaks, 1973–2009
~1,200 outbreaks/year 1998: improved surveillance ~500 outbreaks/year NEW SLIDE THROUGH 2009—illness line deleted. All data from Foodborne Disease Outbreak Surveillance System. Color of bars indicates improvements in data reporting systems.
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Current Hierarchical Scheme for Grouping Foods Into Commodities
All Food Aquatic Land Plant Shellfish Meat-poultry Meat Produce Vegetables Fish Dairy Eggs Grains-beans Oils-sugars Crustaceans Mollusks Poultry Beef Game Pork Fruits-nuts Fungi Leafy Root Sprout Vine-stalk The hierarchical structure currently used for grouping foods into commodities was determined in collaboration with our regulatory partners Represent 17 individual commodities Commodity groups Painter et al, J Food Protection 2009
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Source Attribution Definitions
Simple foods: foods that can be grouped into only one commodity ‘Green salad’ with ‘spinach,’ ‘tomatoes,’ and ‘carrots’ but contaminated ingredient is ‘spinach’ Leafy Green ‘Steak’ Beef ‘Fruit salad’ Fruits-nuts Complex foods: foods that can be grouped into more than one commodity ‘Lasagna’ with ‘tomatoes,’ ‘noodles,’ ‘egg,’ and ‘beef’ Vine-stalk, Grains-beans, Egg, Beef ‘Chow Mein with green salad’ Grains-beans, Pork, Vine-Stalk, Leafy Greens, Oils-Sugars See my edits to this slide on other talk (project 4?)-pmg
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Attributing Outbreaks to Simple Foods
Outbreaks Attributed to Simple Food Commodities 2003–2008 (n=1,570 outbreaks) Outbreak surveillance provides data for determining what foods are major causes of illness Data from Foodborne Disease Outbreak Surveillance System
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Annual MMWR Reports and Analysis 2008
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The Foodborne Outbreak Online Database (FOOD)
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Outline Background and purpose Where source attribution starts
Painting a clearer picture 3 steps to foodborne illness source attribution Limitations of outbreak data A palette of different data sources Looking forward
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3 Steps to Improved Understanding
Step 1: Estimate total number of annual US foodborne illnesses caused by each pathogen Step 2: Attribute illnesses to foods Step 3: Determine the top priority pathogens and their food sources
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3 Steps to Improved Understanding
Step 1: Estimate total number of annual US foodborne illnesses caused by each pathogen Step 2: Attribute illnesses to foods Step 3: Determine the top priority pathogens and their food sources
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Step 1: Estimate Number of Foodborne Illness
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Annual estimate of domestically acquired foodborne illnesses caused by 31 known pathogens
Nearly 48 million illnesses, resulting in ~128,000 hospitalizations, 3,000 deaths 7 pathogens cause 90% of illnesses, hospitalizations, and deaths due to known pathogens Salmonella, norovirus, Campylobacter, Toxoplasma, E. coli O157, Listeria, and Clostridium perfringens Five pathogens account for 88% of hospitalizations caused by known pathogens Salmonella, norovirus, Campylobacter, Toxoplasma, E. coli O157 1/28: same comment as before: Title should be “Illnesses and…” or better, delete hosp, just say “Caused by 31 known pathogens” Slide is very crowded. I would delete last 2 bullets. Delete underline of “known pathogens” 25
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3 Steps to Improved Understanding
Step 1: Estimate total number of annual US foodborne illnesses caused by each pathogen Step 2: Attribute illnesses to foods Step 3: Determine the top priority pathogens and their food sources
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Attribution of foodborne disease outbreaks and illnesses to simple foods Surveillance for Foodborne Disease Outbreaks, United States, 2008)
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3 Steps to Improved Understanding
Step 1: Estimate total number of annual US foodborne illnesses caused by each pathogen Step 2: Attribute illnesses to foods Step 3: Determine the top priority pathogens and their food sources
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Outbreaks (Illnesses)
Attribution of foodborne disease outbreaks and illnesses to simple foods Surveillance for Foodborne Disease Outbreaks, United States, 2008 Food Commodity Outbreaks (Illnesses) Top causes of foodborne illness Fish Dairy Eggs Beef Pork Poultry Fruits-Nuts Vine-Stalk Norovirus 1 (15) 2 (29) 18 (261) Salmonella (4) (70) 7 (85) 3 (106) 4 (133) 11 (228) 8 (1401) (1604) E. coli STEC (24) 12 (283) (5) (103) Campylobacter 10 (118) (27) (16) C. perfringens 6 (330) 5 (358) (150) Listeria (8)
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Determining Major Food Sources
Using data from outbreaks caused by simple foods to attribute illnesses to commodities paints a picture of the pathogen-food commodity pairs that contribute to foodborne disease
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Outline Background and purpose Where source attribution starts
Painting a clearer picture 3 steps to foodborne illness source attribution Limitations of outbreak data A palette of different data sources Looking forward
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Limitations of Outbreak Data
Outbreaks account for a small proportion of total number of foodborne illnesses Need methods that encompass a larger proportion of foodborne illnesses Multi-state Data from Foodborne Diseases Active Surveillance Network (FoodNet) and Foodborne Disease Outbreak Surveillance System
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Limitations of Outbreak Data
More than half of foods reported are complex Many outbreak investigations don’t implicate a single food Small outbreak Delay in reporting to public health department Not all pathogens contributing to foodborne disease cause outbreaks: Toxoplasma gondii
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Outline Background and purpose Where source attribution starts
Painting a clearer picture 3 steps to foodborne illness source attribution Limitations of outbreak data A palette of different data sources Looking forward
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Painting a Clearer Picture
Product Testing Data Product Testing Data Consumption Data Food Ingredients The art in the science of source attribution brings in a palette of data sources (colors) and analytic approaches (brushes) to paint a more complete picture of food source attribution Consumption Data Surveillance Studies Scientific Experts Surveillance Data Complex Food Attribution Case-control Studies Hald Model
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Complex Food Attribution
Product Testing Data Food Ingredients Product Testing Data Consumption Data Incorporates food ingredient information to attribute illnesses to both simple and complex foods Consumption Data Surveillance Studies Surveillance Data Scientific Experts Complex Food Attribution Case-control Studies Hald Model
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The Power of Numbers In the early 1980’s outbreaks of Salmonella Enteritidis were increasing in the Northeast Only 7 of 35 (20%) outbreaks specifically implicated eggs When outbreaks due to egg-containing foods examined, 27 of 35 outbreaks (77%) were associated with eggs Outbreaks in the Northeast Outbreaks in the rest of the country Need to add text box labeling the 2 lines St. Louis et al. JAMA 1988
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Estimating the Number of Illnesses Attributed to Each Food Commodity
CDC has developed a method to use data from both simple and complex food outbreaks to estimate how many illnesses can be attributed to each food commodity Title sounds like scallan paper. I think title better “…attributed to each food commodity” Be sure to remove the numbers and label from y axis!! I find the text a bit obtuse. How about something like: CDC has developed a method to use data from both simple and complex food outbreaks to estimate how many illnesses can be attributed to each food commodity Painter et al. submitted
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Studies of sporadic (non-outbreak) cases
Product Testing Data Product Testing Data Consumption Data Food Ingredients In case-control studies, people with laboratory-confirmed infection and healthy “controls” answer questions about exposures Exposures that cause infection are more common among cases Consumption Data Surveillance Studies Surveillance Data Scientific Experts Complex Food Attribution Case-control Studies Hald Model Would say “persons” or “people” rather than “those”. Would delete “and are identified”
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Case-control Studies Sources of illness are usually not known
Ill people are not routinely interviewed unless part of an outbreak or a special study , such as a case-control study People who are sick cannot determine what food (or other exposure) made them sick, and interviewer can’t either Exposure to contaminated source often days, even weeks, before illness Case-control studies ask about many exposures, compare exposures of ill persons and non ill persons to identify likely sources, but do not identify the source of an individual illness Good. Would put in beginning of this section after you explain that 80% are not outbreaks (not more than 80%?).
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Case-control Studies Case-control studies provide population attributable fractions for significant exposures Source attribution example from studies of Campylobacter infection: Travel (12% of cases) Chicken (24%) or other meat (21%) consumed in a restaurant Undercooked or pink chicken (3%)
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Complex Food Attribution
Product Testing Data Hald Model Product Testing Data Consumption Data Food Ingredients A model first published by Danish scientists links food contamination and consumption patterns to foodborne illnesses Consumption Data Surveillance Studies Surveillance Data Scientific Experts Complex Food Attribution Case-control Studies Hald Model Again, show outline slide first, then go to description of the model
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Hald Model Estimate the expected number of human illnesses attributable to specific food products using human illness data, food consumption data, and pathogen isolation data from food products I find “method principle” a bit cryptic. Can we just delete?
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Adaptation of Hald Attribution Model to US Data
Data Sources US Department of Agriculture (USDA) Food Safety Inspection Service (FSIS) verification testing data Data from CDC on laboratory-confirmed Salmonella infections USDA Economic Research Service data on market availability of food commodities regulated by USDA Spell verification Delete enterica for this audience Delete colon Guo et al. Foodborne Path Dis (
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Painting a Clearer Picture
Product Testing Data Product Testing Data Consumption Data Food Ingredients Food borne illness source attribution as determined from outbreak investigations provides the framework for determining the food-pathogen pairs that contribute to foodborne disease However, source attribution can be strengthened by using additional data sources and analytic methods Consumption Data Surveillance Studies Scientific Experts Surveillance Data Complex Food Attribution Case-control Studies Hald Model One word “foodborne
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Outline Background and purpose Where source attribution starts
Painting a clearer picture Looking forward
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Challenge: Communicating Clearly
How to explain uncertainty associated with different estimates How to interpret “change” Changing data Different methods Real change What it means to consumers for a food to be “risky”: how to provide information that helps consumers without generating fear I would delete this slide
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My vision is a slide with the first 2 questions
My vision is a slide with the first 2 questions. Then next slide adds a picture, maybe of lots Of people frantically doing everything, saying the 3rd quote. Looking Forward Attribution estimates are always changing: Data is improving New data sources are being incorporated Analytic methods continue to evolve Our goal is to continue to improve estimates by using the best available data and methods, which will enable us to use the most current, accurate, state-of-the-art information when making decisions.
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Questions?
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Thank You! Would consolidate last 2 slides
The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. National Center for Emerging and Zoonotic Infectious Diseases Enteric Diseases Epidemiology Branch
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