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2018 BayesiaLab Conference in Chicago

Conference Presentation

Methicillin-Resistant Staphylococcus aureus in Children Living with Industrial Hog Operation Workers: Bayesian Network Risk Models

Jacqueline MacDonald Gibson, Ph.D.
RTI University Scholar, 2017-2018
Associate Professor, Department of Environmental Sciences and Engineering
Gillings School of Global Public Health
University of North Carolina, Chapel Hill

Abstract

Since the first documented transmission of antibiotic-resistant Staphylococcus aureus from hogs to a Dutch child in 2004, evidence of such hog-to-human transfer has mounted. However, the factors contributing to transmission risk remain poorly understood. Using empirical data collected from 198 children living with workers employed by North Carolina, USA, industrial hog operations, we developed the first Bayesian network models quantifying transmission of methicillin-resistant S. aureus (MRSA) from industrial hog operation workers to children living in the same household. Multiple learning algorithms were tested for variable selection, and the augmented naïve Bayes algorithm was then used to learn a network from the resulting variables. Network performance in predicting children’s carriage of MRSA was evaluated through 10 runs of five-fold cross-validation. The network with the highest area under the receiver-operating characteristic (AUROC) curve was selected as the final model, with other networks used for sensitivity analysis. Overall, 14% of the children living with hog farm workers carried MRSA. The best-performing network maintained an AUROC above 0.90 during cross-validation. The network revealed that the variables with the most influence on the risk of MRSA transmission to children living with hog farm workers include workers having direct contact with hog manure, workers bringing home face masks and work suits, and the type of health insurance available to the child. The results can be used to design intervention programs to prevent the spread of MRSA from hog farms to human populations.

About the Presenter

Jackie MacDonald Gibson has a multi-disciplinary background in mathematics and engineering that she applies to risk assessment and policy problems.  Before joining the University of North Carolina faculty, she was Associate Director of the Water Science and Technology Board, U.S. National Research Council.  She also was Senior Engineer at the RAND Corp.  She holds Ph.D. degrees in Engineering and Public Policy and Civil and Environmental Engineering from Carnegie Mellon University; an M.S. in Civil and Environmental Engineering from the University of Illinois at Urbana–Champaign; and a B.A. in mathematics from Bryn Mawr College.