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Dana Cole, DVM, PhD Enteric Disease Epidemiology Branch, Division of Foodborne, Waterborne, and Environmental Diseases January 31 st, 2012 ESTIMATING THE.

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Presentation on theme: "Dana Cole, DVM, PhD Enteric Disease Epidemiology Branch, Division of Foodborne, Waterborne, and Environmental Diseases January 31 st, 2012 ESTIMATING THE."— Presentation transcript:

1 Dana Cole, DVM, PhD Enteric Disease Epidemiology Branch, Division of Foodborne, Waterborne, and Environmental Diseases January 31 st, 2012 ESTIMATING THE SOURCES OF FOODBORNE ILLNESS IN THE UNITED STATES Enteric Diseases Epidemiology Branch National Center for Emerging and Zoonotic Infectious Diseases

2 Outline Background and purpose Where source attribution starts Painting a clearer picture Looking forward 2

3 Outline Background and purpose – Goal – Questions Where source attribution starts Painting a clearer picture Looking forward 3

4 “ Art and science have their meeting point in method.” Earl Edward George Bulwer-Lytton (1875) 4

5 “ Art and science have their meeting point in method.” Earl Edward George Bulwer-Lytton (1875)

6 Our Overarching Goal To prevent illness and death by gathering and analyzing information to create collective knowledge and stop food problems before they happen 6

7 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 3 rd quote. at·tri·bu·tion: [a-tr ə -byü-sh ə n] 1.The act of attributing, especially the act of establishing a particular person as the creator of a work of art. 1.The act of attributing, especially specifically the act of establishing a particular person food as the creator source of an work of art infection. 7

8  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 Purpose: Inform food safety decision-making 8 8

9 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

10 Outline Background and purpose Where source attribution starts Painting a clearer picture Looking forward 10

11 Cycle of Foodborne Disease Control and Prevention Surveillance Epidemiologic Investigation Applied Research Prevention Measures 11

12 Cycle of Foodborne Disease Control and Prevention Surveillance Epidemiologic Investigation Applied Research Prevention Measures OUTBREAK 12

13 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

14 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. Captures outbreak data on agents, foods, and settings responsible for illness FDOSS Foodborne Disease Outbreak Surveillance System 14

15 Foodborne Disease Outbreaks, 1973–2009 ~500 outbreaks/year ~1,200 outbreaks/year 1998: improved surveillance All data from Foodborne Disease Outbreak Surveillance System. Color of bars indicates improvements in data reporting systems.

16 Current Hierarchical Scheme for Grouping Foods Into Commodities Represent 17 individual commodities Commodity groups All Food AquaticLandPlant ShellfishMeat-poultry Meat Produce Vegetables FishDairyEggsGrains-beansOils-sugars Crustaceans Mollusks Poultry Beef Game Pork Fruits-nuts Fungi Leafy Root Sprout Vine-stalk Painter et al, J Food Protection 2009

17 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 17

18 Attributing Outbreaks to Simple Foods Data from Foodborne Disease Outbreak Surveillance System Outbreak surveillance provides data for determining what foods are major causes of illness Outbreaks Attributed to Simple Food Commodities 2003–2008 (n=1,570 outbreaks)

19 Annual MMWR Reports and Analysis 2008

20 The Foodborne Outbreak Online Database (FOOD) 20

21 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 21

22 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

23 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

24 Step 1: Estimate Number of Foodborne Illness 24

25 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 25

26 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

27 Attribution of foodborne disease outbreaks and illnesses to simple foods Surveillance for Foodborne Disease Outbreaks, United States, 2008 ) 27

28 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

29 Food Commodity Outbreaks (Illnesses) Top causes of foodborne illness FishDairyEggsBeefPorkPoultryFruits- Nuts Vine- Stalk Norovirus001 (15) 2 (29) 0018 (261) 0 Salmonella1 (4) 1 (70) 7 (85) 3 (106) 4 (133) 11 (228) 8 (1401) 3 (1604) E. coli STEC03 (24) 012 (283) 001 (5) 4 (103) Campylobacter010 (118) 001 (27) 3 (16) 00 C. perfringens01 (24) 06 (330) 5 (358) 6 (150) 00 Listeria01 (8) Attribution of foodborne disease outbreaks and illnesses to simple foods Surveillance for Foodborne Disease Outbreaks, United States, 2008

30 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

31 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 31

32 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

33 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

34 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 34

35 Painting a Clearer Picture Consumption Data 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 Surveillance Studies Product Testing Data Scientific Experts Complex Food Attribution Case- control Studies Hald Model Product Testing Data Consumption Data Food Ingredients Surveillance Data

36 Complex Food Attribution Consumption Data Incorporates food ingredient information to attribute illnesses to both simple and complex foods Surveillance Studies Product Testing Data Scientific Experts Complex Food Attribution Case- control Studies Hald Model Product Testing Data Consumption Data Food Ingredients Surveillance Data

37 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 St. Louis et al. JAMA 1988 Outbreaks in the Northeast Outbreaks in the rest of the country

38 Estimating the Number of Illnesses Attributed to Each Food Commodity Painter et al. submitted 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

39 Studies of sporadic (non-outbreak) cases Consumption Data 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 Surveillance Studies Product Testing Data Scientific Experts Complex Food Attribution Case- control Studies Hald Model Product Testing Data Consumption Data Food Ingredients Surveillance Data

40 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

41 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%)

42 Hald Model Consumption Data A model first published by Danish scientists links food contamination and consumption patterns to foodborne illnesses Surveillance Studies Product Testing Data Scientific Experts Complex Food Attribution Case- control Studies Hald Model Product Testing Data Consumption Data Food Ingredients Surveillance Data

43 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 43

44 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 Guo et al. Foodborne Path Dis (http://www.liebertonline.com/doi/pdfplus/ /fpd )

45 Painting a Clearer Picture Consumption Data Surveillance Studies Product Testing Data Scientific Experts Complex Food Attribution Case- control Studies Hald Model Product Testing Data Consumption Data Food Ingredients Surveillance Data 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

46 Outline Background and purpose Where source attribution starts Painting a clearer picture Looking forward 46

47 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 47

48 Looking Forward 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 3 rd quote.  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. 48

49 Questions?

50 For more information please contact Centers for Disease Control and Prevention 1600 Clifton Road NE, Atlanta, GA Telephone, CDC-INFO ( )/TTY: Web: Thank You! National Center for Emerging and Zoonotic Infectious Diseases Enteric Diseases Epidemiology Branch 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.


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