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

This repository contains the extracted data and analysis code supporting our scoping review characterizing peer-reviewed digital twins for modeling food safety microorganisms (foodborne pathogens and indicator organisms), published between 2012 and 2024.

Repository structure

Data dictionary

Full variable definitions and classification schemes are described in Table 1 of the manuscript. Briefly:

• main_extraction.xlsx - one row per included study: publication year, modeling approach (Mechanistic / Data-driven / Hybrid), validation status (Full / Partial / No), Transparency (Yes / Upon request), ...
• micro_industry_pairings.xlsx - links each study (Article_ID) to the food microorganism(s) and industry it addresses.
• industry_sectors.xlsx - links each study ('Article_ID') to the primary food industry sector(s) it addresses.

All three files share 'Article_ID' as a common key and are merged in the notebook to reproduced the figures.

Reproducing the manuscript figures

Open 'notebooks/Scoping_Review_Figures.ipynb' in Google Colab or Jupyter. The noteook:

1. Installs and imports required packages ('Upsetplot', 'pandas', 'matplotlib', 'seaborn')
2. Loads and merges the three data files above
3. Generates Figures 2, 4-7 as reported in the manuscript

Figure 1 (PRISMA flow diagram) and 3 (Sankey diagram) were produced outside this notebook and are not included here.

Citation

Kalunga, L., Ruser, S., Nelson, A., Soto, S. L., Qian, C., Grover, L., Murphy, S. I., Wiedmann, M., & Ivanek, R. (2026). Characteristics of Peer-Reviewed Digital Tools for Modeling Food Safety Microorganisms: A Scoping Review. Journal of Food Protection, 100920. https://doi.org/10.1016/j.jfp.2026.100920

Contact

Linda Kalunga - lk549@cornell.edu