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  • Author: Guo, Chuanfa

    Food Safety and Inspection Service

  • Author: Hoekstra, Robert M.

    National Center for Emerging and Zoonotic Infectious Diseases

  • Author: Schroeder, Carl M.

    Food Safety and Inspection Service

  • Author: Pires, Sara Monteiro

    Division of Microbiology and Risk Assessment, National Food Institute, Technical University of Denmark, Mørkhøj Bygade 19, 2860, Søborg, Denmark

  • Author: Ong, Kanyin Liane

    National Center for Emerging and Zoonotic Infectious Diseases

  • Author: Hartnett, Emma

    Decisionalysis Risk Consultants

  • Author: Naugle, Alecia

    Food Safety and Inspection Service

  • Author: Harman, Jane

    Food Safety and Inspection Service

  • Author: Bennett, Patricia

    Food Safety and Inspection Service

  • Author: Cieslak, Paul

    Oregon Department of Human Services

  • Author: Scallan, Elaine

    Colorado School of Public Health

  • Author: Rose, Bonnie

    Food Safety and Inspection Service

  • Author: Holt, Kristin G.

    Food Safety and Inspection Service

  • Author: Kissler, Bonnie

    Food Safety and Inspection Service

  • Author: Mbandi, Evelyne

    Food Safety and Inspection Service

  • Author: Roodsari, Reza

    Food Safety and Inspection Service

  • Author: Angulo, Frederick J.

    Waterborne, and Environmental Diseases

  • Author: Cole, Dana

    Waterborne, and Environmental Diseases

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Mathematical models that estimate the proportion of foodborne illnesses attributable to food commodities at specific points in the food chain may be useful to risk managers and policy makers to formulate public health goals, prioritize interventions, and document the effectiveness of mitigations aimed at reducing illness. Using human surveillance data on laboratory-confirmed Salmonella infections from the Centers for Disease Control and Prevention and Salmonella testing data from U.S. Department of Agriculture Food Safety and Inspection Service's regulatory programs, we developed a point-of-processing foodborne illness attribution model by adapting the Hald Salmonella Bayesian source attribution model. Key model outputs include estimates of the relative proportions of domestically acquired sporadic human Salmonella infections resulting from contamination of raw meat, poultry, and egg products processed in the United States from 1998 through 2003. The current model estimates the relative contribution of chicken (48%), ground beef (28%), turkey (17%), egg products (6%), intact beef (1%), and pork (
Original languageEnglish
JournalFoodborne Pathogens and Disease
Publication date2011
Volume8
Issue4
Pages509-516
ISSN1535-3141
DOIs
StatePublished
CitationsWeb of Science® Times Cited: 34
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