TY - JOUR
T1 - Application of Bayesian Techniques to Model the Burden of Human Salmonellosis Attributable to U.S. Food Commodities at the Point of Processing: Adaptation of a Danish Model
AU - Guo, Chuanfa
AU - Hoekstra, Robert M.
AU - Schroeder, Carl M.
AU - Pires, Sara Monteiro
AU - Ong, Kanyin Liane
AU - Hartnett, Emma
AU - Naugle, Alecia
AU - Harman, Jane
AU - Bennett, Patricia
AU - Cieslak, Paul
AU - Scallan, Elaine
AU - Rose, Bonnie
AU - Holt, Kristin G.
AU - Kissler, Bonnie
AU - Mbandi, Evelyne
AU - Roodsari, Reza
AU - Angulo, Frederick J.
AU - Cole, Dana
PY - 2011
Y1 - 2011
N2 - 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 (
AB - 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 (
U2 - 10.1089/fpd.2010.0714
DO - 10.1089/fpd.2010.0714
M3 - Journal article
SN - 1535-3141
VL - 8
SP - 509
EP - 516
JO - Foodborne Pathogens and Disease
JF - Foodborne Pathogens and Disease
IS - 4
ER -