TY - JOUR
T1 - Frequentist and Bayesian approaches for food allergen risk assessment
T2 - risk outcome and uncertainty comparisons
AU - Birot, Sophie
AU - Crépet, Amélie
AU - Remington, Benjamin C.
AU - Madsen, Charlotte B.
AU - Kruizinga, Astrid G.
AU - Baumert, Joseph L.
AU - Brockhoff, Per B.
N1 - Funding Information:
This work was part of the iFAAM project (Integrated Approaches to Food Allergen and Allergy Risk Management, Grant Agreement No. 322147), the national food consumption data for France and Denmark were kindly provided by the work package partners: ANSES and DTU. The national food consumption data of the Netherlands was kindly provided by the National Institute for Public Health and the Environment in the Netherlands. The challenge data for peanut and soy was kindly provided by TNO and FARRP (University of Nebraska – Food Allergy Research and Resource Program). This paper was kindly reviewed and edited by René Crevel.
Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Peer-reviewed probabilistic methods already predict the probability of an allergic reaction resulting from an accidental exposure to food allergens, however, the methods calculate it in different ways. The available methods utilize the same three major input parameters in the risk model: the risk is estimated from the amount of food consumed, the concentration of allergen in the contaminated product and the distribution of thresholds among allergic persons. However, consensus is lacking about the optimal method to estimate the risk of allergic reaction and the associated uncertainty. This study aims to compare estimation of the risk of allergic reaction and associated uncertainty using different methods and suggest improvements. Four cases were developed based on the previous publications and the risk estimations were compared. The risk estimation was found to agree within 0.5% with the different simulation cases. Finally, an uncertainty analysis method is also presented in order to evaluate the uncertainty propagation from the input parameters to the risk.
AB - Peer-reviewed probabilistic methods already predict the probability of an allergic reaction resulting from an accidental exposure to food allergens, however, the methods calculate it in different ways. The available methods utilize the same three major input parameters in the risk model: the risk is estimated from the amount of food consumed, the concentration of allergen in the contaminated product and the distribution of thresholds among allergic persons. However, consensus is lacking about the optimal method to estimate the risk of allergic reaction and the associated uncertainty. This study aims to compare estimation of the risk of allergic reaction and associated uncertainty using different methods and suggest improvements. Four cases were developed based on the previous publications and the risk estimations were compared. The risk estimation was found to agree within 0.5% with the different simulation cases. Finally, an uncertainty analysis method is also presented in order to evaluate the uncertainty propagation from the input parameters to the risk.
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U2 - 10.1038/s41598-019-54844-1
DO - 10.1038/s41598-019-54844-1
M3 - Article
C2 - 31796875
AN - SCOPUS:85075917724
SN - 2045-2322
VL - 9
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 18206
ER -