Risk Analysis and Predictive Modeling

A key effort in the Food Safety Lab is to develop predictive models to support decision-making in food safety applications, particularly in the field of fresh produce. Current research focuses on developing (i) farm-level geographical information system (GIS) models to predict the increased likelihood of pathogen presence in produce fields; (ii) developing quantitative microbial risk assessments for food safety and enterprise risk associated with fresh produce and cold-smoked salmon; (iii) developing agent-based models to simulate Listeria transmission in different production and retail environments to inform proper intervention strategies and sampling plans.

Relevant Key Publications

  • Qian, C., S. I. Murphy, R. H. Orsi, and M. Wiedmann. 2022. How Can AI Help Improve Food Safety? Annu Rev Food Sci Technol. https://doi.org/10.1146/annurev-food-060721-013815
  • Qian, C., Y. Liu, C. Barnett-Neefs, S. Salgia, O. Serbetci, A. Adalja, J. Acharya, Q. Zhao, R. Ivanek, and M. Wiedmann. 2022. A perspective on data sharing in digital food safety systems. Crit. Rev. Food Sci. Nutr. 1–17. https://doi:10.1080/10408398.2022.2103086.
  • Chen, R., R. H. Orsi, V. Guariglia-Oropeza, and M. Wiedmann. 2022. Development of a modeling tool to assess and reduce regulatory and recall risks for cold-smoked salmon due to Listeria monocytogenes contamination. J. Food Prot. 85(9): 1335–1354. https://doi.org/10.4315/JFP-22-025
  • Trmčić, A., E. Demmings, K. Kniel, M. Wiedmann, and S. Alcaine. 2021. Food safety and employee health implications of COVID-19: A review. J. Food Prot. 84:1973–1989. https://doi:10.4315/JFP-21-201.
  • Sullivan, G., C. Zoellner, M. Wiedmann, and R. Ivanek. 2021. In Silico Models for Design and Optimization of Science-Based Listeria Environmental Monitoring Programs in Fresh-Cut Produce Facilities. Appl. Environ. Microbiol. 87:e0079921. https://doi:10.1128/AEM.00799-21.
  • Zwietering, M.H., A. Garre, M. Wiedmann, and R.L. Buchanan. 2021. All food processes have a residual risk, some are small, some very small and some are extremely small: zero risk does not exist. Curr. Opin. Food Sci. 39:83–92. https://doi:10.1016/j.cofs.2020.12.017.
  • Weller, D.L., T.M.T. Love, and M. Wiedmann. 2021. Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to Predict E. coli Levels in Agricultural Water. Front. Artif. Intell. 4. https://doi:10.3389/frai.2021.628441.
  • Cohn, A.R., R.A. Cheng, R.H. Orsi, and M. Wiedmann. 2021. Moving Past Species Classifications for Risk-Based Approaches to Food Safety: Salmonella as a Case Study. Front. Sustain. Food Syst. 5. https://doi:10.3389/fsufs.2021.652132.
  • Farber, J.M., M. Zwietering, M. Wiedmann, D. Schaffner, C.W. Hedberg, M.A. Harrison, E. Hartnett, B. Chapman, C.W. Donnelly, K.E. Goodburn, and S. Gummalla. 2021. Alternative approaches to the risk management of Listeria monocytogenes in low risk foods. Food Control 123. https://doi:10.1016/j.foodcont.2020.107601.
  • Belias A., N. Brassill, S. Roof, C. Rock, M. Wiedmann, and D. Weller. 2021. Cross-Validation Indicates Predictive Models May Provide an Alternative to Indicator Organism Monitoring for Evaluating Pathogen Presence in Southwestern US Agricultural Water. Front. Water 3:693631. https://doi.org/10.3389/frwa.2021.693631
  • Weller D. L., T. M. T. Love, and M. Wiedmann. 2021. Comparison of Resampling Algorithms to Address Class Imbalance when Developing Machine Learning Models to Predict Foodborne Pathogen Presence in Agricultural Water. Front. Environ. Sci. 9:701288. https://doi.org/10.3389/fenvs.2021.701288
  • Belias, A.M., A. Sbodio, P. Truchado, D. Weller, J. Pinzon, M. Skots, A. Allende, D. Munther, T. Suslow, M. Wiedmann, and R. Ivanek. 2020. Effect of weather on the die-off of Escherichia coli and attenuated Salmonella enterica serovar typhimurium on preharvest leafy greens following irrigation with contaminated water. Appl. Environ. Microbiol. 86. https://doi:10.1128/AEM.00899-20
  • Weller D. L., T. M. T. Love, A. Belias, and M. Wiedmann. 2020. Predictive Models May Complement or Provide an Alternative to Existing Strategies for Assessing the Enteric Pathogen Contamination Status of Northeastern Streams Used to Provide Water for Produce Production. Front. Sustain. Food Syst. 4:561517. https://doi.org/10.3389/fsufs.2020.561517
  • Weller D., A. Belias, H. Green, S. Roof, and M. Wiedmann. 2020 Landscape, Water Quality, and Weather Factors Associated With an Increased Likelihood of Foodborne Pathogen Contamination of New York Streams Used to Source Water for Produce Production. Front. Sustain. Food Syst. 3:124. https://doi.org/10.3389/fsufs.2019.00124
  • Weller, D., N. Brassill, C. Rock, R. Ivanek, E. Mudrak, S. Roof, E. Ganda, and M. Wiedmann. 2020. Complex interactions between weather, and microbial and physicochemical water quality impact the likelihood of detecting foodborne pathogens in agricultural water. Front. Microbiol. 11:134. https://doi.org/10.3389/fmicb.2020.00134
  • Weller, D.L., J. Kovac, D.J. Kent, S. Roof, J.I. Tokman, E. Mudrak, and M. Wiedmann. 2019. A conceptual framework for developing recommendations for no-harvest buffers around in-field feces. J. Food Prot. 82:1052–1060. doi:10.4315/0362-028X.JFP-18-414.
  • Zoellner, C., M. Wiedmann, and R. Ivanek. 2019. An assessment of listeriosis risk associated with a contaminated production lot of frozen vegetables consumed under alternative consumer handling scenarios. J. Food Prot. 82(12), 2174-2193. https://doi.org/10.4315/0362-028X.JFP-19-092
  • Zoellner, C., R. Jennings, M. Wiedmann, and R. Ivanek. 2019. EnABLe: An agent-based model to understand Listeria dynamics in food processing facilities. Sci Rep 9, 495 (2019). https://doi.org/10.1038/s41598-018-36654-z
  • Weller, D.L., J. Kovac, S. Roof, D.J. Kent, J.I. Tokman, B. Kowalcyk, D. Oryang, R. Ivanek, A. Aceituno, C. Sroka, and M. Wiedmann. 2017. Survival of Escherichia coli on lettuce under field conditions encountered in the Northeastern United States. J. Food Prot. 80:1214–1221. doi:10.4315/0362-028X.JFP-16-419.
  • Kovac, J., H. den Bakker, L.M. Carroll, and M. Wiedmann. 2017. Precision food safety: A systems approach to food safety facilitated by genomics tools. TrAC - Trends Anal. Chem. 96:52–61. https://doi:10.1016/j.trac.2017.06.001