Characteristics of Peer-Reviewed Digital Tools for Modeling Food Safety Microorganisms: A Scoping Review

As digital tools for modeling microorganisms of food safety concern (foodborne pathogens and indicator microorganisms) become more widespread in food safety decision-making, a comprehensive assessment of existing model alignment with public health and stakeholder needs is lacking. This scoping review systematically characterized published digital tools for food safety microorganism modeling to evaluate their purpose, modeling approach, validation extent, code transparency, and user interface design. We searched six databases (PubMed, Web of Science, FSTA, AGRICOLA, CAB Abstracts, Medline) for peer-reviewed studies on digital tools that model food safety microorganisms in food/agriculture matrices published between 2012 and 2024. We identified 62 eligible studies with code access provided and found that model purpose largely aligned with established public health priorities. Mechanistic models were the dominant modeling approach (48%), followed by data-driven (32%), and hybrid (19%) models. Most included models demonstrated rigorous validation (82%) and were developer-oriented tools (58%) requiring programming or command-line interaction. During full-text screening of 375 articles, we first assessed code transparency, which resulted in the exclusion of 208 studies where the underlying code was not publicly available. Furthermore, among the 62 eligible studies with available code, 21% made their code available only upon request via email. Reporting of model characteristics remained heterogeneous despite the availability of software reporting standards. These findings provide a foundation to guide future research priorities and highlight the need for collaborative efforts among researchers, journals, and funding bodies to improve transparency, reproducibility, and usability for diverse stakeholder needs.