Designing Studies to Better Understand Food Source Attribution

1. Designing Studies to Better Understand Food Source Attribution Mike Hoekstra National Center for Emerging and Zoonotic Infectious Diseases Division of Foodborne, Waterborne, and Environmental Diseases

2. Abstract Attribution of illness to food commodity is a simple process of relating episodes of human illness through consumption or handling of foods to instances of commodity contamination…except that the available data on human illness, food consumption, and contamination are nowhere configured to make relating them simple. The totality of agents that cause illness is not known. Surveillance for the agents that are known is not complete. Surveillance reports rarely come with food specified as the cause, much less the commodity. Outbreak investigations can produce cases of human illness that are tightly linked to specific food exposures, but such tight links exist for only a fraction of reported outbreak cases, and outbreak cases are, in turn, only a small fraction of all cases. Case control studies are typically aimed at attributing illness to causal food exposures in the much larger population of sporadic illness. These studies link multiple food exposures to cases, but do so in a very noisy fashion. The actual causal exposures are in turn inferred from control food exposures, also noisy and with different potential biases. Consumption models, like that of Hald, link counts of human illness aggregated by type to commodity contamination levels by type, through food consumption estimates, yielding ecological associations. Further, commodity contamination levels can depend on the point in the food chain that they are measured, creating potentially different attributions. Quantitative microbiological risk assessment offers another route to attribution, building causal pathways from reservoir to consumption via probabilistic models applied to the food chain. These are examples of existing ways to relate illness to contaminated food. They are diverse, not exhaustive, and no single method can be deemed definitive given the large inherent uncertainties in the data and in the model structures themselves. We present design considerations for each these examples along with a paradigm for synthesizing an understanding of their collective food source attribution outputs.

3. Outline • Aim and Background • Estimating the burden of foodborne illness • Foodborne illness estimates • Attribution and attributing • Attributions • Future directions

4. Aim • Estimate the “burden” of human illness caused by contaminated food • at the individual pathogen/agent level and in the aggregate • where burden may be defined in terms of severity (eg. illness vs. hospitalizations) • Estimate the proportion of that burden caused by specific food commodities • where commodities are tied to regulation • where burden may be specific to subpopulation or illness outcome

5. Aim • Intervene to reduce illness at point(s) informed by estimated burden and attribution • Measure changes in amount of illness • where power to detect change depends on effect size and data stream • Measure change in the proportion of illness caused by specific food commodities

6. Cycle of public health action • Burden Attribution Intervention Trend Attribution

7. Outline • Aim and Background • Estimating the burden of foodborne illness • Foodborne illness estimates • Attribution and attributing • Attributions • Future directions

8. Estimating illnesses • Multiplicative models • Data summarized with distributions • Factors summarized with distributions • Þ Burden summarized with distributions

9. Estimates of US lab-confirmed Campylobacterillnesses, based on data extrapolated from each FoodNet site, by state

10. Multiplicative model

11. Multiplicative model

12. Estimated distribution of CampylobacterIllness Burden

13. Outline • Aim • Estimating the burden of foodborne illness • Foodborne illness estimates • Attribution and attributing • Attributions • Future directions

14. Annual estimate of domestically acquired foodborne illnesses, hospitalizations and deaths

15. Summary of Results:Domestically Acquired Foodborne illness

16. Summary of Results:Domestically Acquired Foodborne illness Deaths Hospitalizations Illnesses Percent Foodborne

17. Links to additional information can be found at…www.cdc.gov/foodborneburden

18. Outline • Aim • Estimating the burden of foodborne illness • Foodborne illness estimates • Attribution and attributing • Attributions • Future directions

20. The Attribution Framework Eggs Leafy Beef Fruits-Nuts Seafood Norovirus Reservoir Salmonella Production Processing E. Coli O157 Preparation L. mono Consumption Shell Bagged Lettuce Products Retail Beef Cuts Ground Beef Bunch Spinach

21. Pathogen-Vehicle Plane Building Blocks in Framework Eggs Leafy Beef Fruits-Nuts Seafood Norovirus Salmonella E. Coli O157 L. mono

22. Outline • Aim • Estimating the burden of foodborne illness • Foodborne illness estimates • Attribution and attributing • Attributions • Future directions

23. Human Illness Data Sources and Related Attribution Methodologies

24. All Food Aquatic Land animals Plant Fish Shellfish Dairy Eggs Meat-Poultry Produce Grains-beans Oils-sugars Crustaceans Meat Fruits-nuts Mollusks Beef Vegetables Game Fungi Pork Leafy Yellow boxes identify 17 commodities Poultry Root Sprout Painter et al, J Food Protection 2009 Vine-stalk Food Commodity Hierarchy

25. AttributionsIllnesses (%)

26. Outline • Aim • Estimating the burden of foodborne illness • Foodborne illness estimates • Attribution and attributing • Attributions • Future directions

27. NW SE NE S N SW W E

28. Synthesis: Issues • Categories • Partition < 100% • Partition > 100% • Missing values • Incomplete classification • Non-quantitative knowledge • Weighting/combining information

29. Synthesis: Resolutions • Expert elicitation • EE/BMA hybrid • Bayesian model averaging • Integrated blending model (?)

30. Project 3 Project 7 Project 0 JAN 2016 JAN 2013 Analysis Analysis Analysis Analysis Analysis Outbreak Attribution Theory Theory Theory Theory Theory Data Data Data Data Data Project 6 Blended Attribution Project 5 Sporadic Attribution Project 9 Project 4 Consumption-based Models Project 8 Expert Elicitation Project 2 Reporting Synthesis Theory Project 10 Communication Summary description based on existing data and understanding Summary description based on revised data and understanding

31. National Center for Emerging and Zoonotic Infectious Diseases Division of Foodborne, Waterborne, and Environmental Diseases

32. In case you were thinking outbreaks can solve all your problems…