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Volume 11, Number 7—July 2005
Perspective

Attributing Illness to Food

Michael B. Batz*Comments to Author , Michael S. Doyle†, J. Glenn Morris‡, John Painter§, Ruby Singh¶, Robert V. Tauxe§, Michael R. Taylor*, Danilo M.A. Lo Fo Wong#, and for the Food Attribution Working Group
Author affiliations: *Resources for the Future, Washington, DC, USA; †University of Georgia, Griffin, Georgia, USA; ‡University of Maryland School of Medicine, Baltimore, Maryland, USA; §Centers for Disease Control and Prevention, Atlanta, Georgia, USA; ¶Food and Drug Administration, Laurel, Maryland, USA; #Danish Institute for Food and Veterinary Research, Copenhagen, Denmark

Main Article

Table

Current approaches to food attribution

Approach Primary advantages Primary limitations Refs
Denmark Salmonella Accounts Microbial subtyping provides direct link between public health endpoint and animal Difficult to expand to other pathogens; requires distinctive subtypes across reservoirs 5,6
High reporting of illnesses (social health care) Focus on animals ignores nonanimal sources
National, temporal coverage for both illnesses and animal/product monitoring Focus on reservoirs, not food products at point of consumption
UK outbreak data Large dataset: national, temporal coverage May not correlate with sporadic case data 8
Results correlate with local epidemiologic findings Not all pathogens well represented
Dependence on general practitioners
US outbreak data National and temporal coverage May not correlate with sporadic case data 11,12
Large common dataset Geographic and temporal inconsistencies (local reporting) and biases towards certain foods
Straightforward, uses existing data Not all pathogens well represented
Outbreaks and outbreak cases can be aggregated into food categories
Case-control studies Population-based studies Survey format has recall bias and other limits 17,2024
Captures risk factors not included in most surveillance data (travel, food preparation questions) Long exposure windows (problems with common exposures)
Can implicate risks missed by laboratory testing Durable immunity in population can impede associating exposures with illnesses
No laboratory verification
Microbial subtyping Subtyping of illnesses and foods can provide direct link between public health endpoint and source of infection For animal sourcing, subtypes must be distinctive across species (see Danish Salmonella Accounts) 2528,5,6
Can be used to identify specific foods (outbreak investigations) or animal reservoirs (source tracking by species) Utility may be limited to certain pathogens
Many different techniques, growing fast Resource intensive; requires human surveillance, extensive monitoring of food and animals, plus laboratory testing, data storage, analysis
Risk assessments Can estimate cases not captured by surveillance methods (not limited by underreporting or biases in epidemiologic methods) Predictive; cannot be verified 2933
Uses consumption and contamination data ignored by surveillance-based approaches Large uncertainties in dose-response models and exposure estimates
Resource- and time-intensive (each pathogen-food combination requires its own exhaustive study)
Food monitoring data Captures upstream contamination (avoids environmental and cross-contamination after purchase) Not usable for food attribution unless made compatible (through subtyping or other means) with public health data 3436
Expert elicitation/judgment Useful when data are sparse or conflicting Respondents can be similarly biased 15,3739
Formal methods increase utility Requires some level of consensus for reasonable error bounds
Based on perception, not data

Main Article

References
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Main Article

1In addition to the authors, the presenters and attendees who constitute the Food Attribution Working Group are: Fred Angulo (CDC), Robert Buchanan (FDA), H. Gregg Claycamp (FDA), Caroline Smith DeWaal, Center for Science in the Public Interest (CSPI), Jorge Santo Domingo (EPA), Katherine Field (Oregon State University), David Goldman (USDA), Matthew Moore (CDC), Sarah O'Brien (Communicable Disease Surveillance Centre, England), Efrain Ribot (CDC), Stephen Sundlof (FDA), and Catherine Woteki (Iowa State University).

Page created: April 23, 2012
Page updated: April 23, 2012
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The conclusions, findings, and opinions expressed by authors contributing to this journal do not necessarily reflect the official position of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.
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