A Machine-Readable Standard for Public Health #

We are happy to share that our paper — The Open Syndrome Definition as a Machine-Readable Standard for Public Health: Design and Implementation Study — has been published in the Journal of Medical Internet Research (JMIR).

Public health surveillance relies on case and syndrome definitions: the criteria that decide whether someone counts as a case of a disease or fits a given syndrome. They are the backbone of how outbreaks are detected and compared, yet they still live as prose in PDFs that machines cannot read and that differ from one agency to the next.

We propose the first open, machine-readable standard for these definitions. Think of it as a shared grammar, so public health systems around the world can finally talk to each other and to machines.

This is also where AI gets powerful. Once a definition is structured, language models can help author, validate, and apply it, opening the door to AI-driven surveillance that was hard to do before.

It was a truly international effort, with RKI, Fiocruz, UKHSA, and York University. Since publication, we have also released an R package and a visual editor, with a hands-on workshop on the way.

How to cite #

If you use Open Syndrome definitions, datasets, or tools, please cite the published paper. The full guidance — APA, JMIR, and BibTeX formats for the paper, definitions, dataset, and tools — lives in our citation guide.

JMIR’s preferred format:

Gomes Ferreira AP, Anžel A, Marcilio I, Hughes H, Elliot AJ, Kong JD, Schranz M, Ullrich A, Hattab G.
The Open Syndrome Definition as a Machine-Readable Standard for Public Health: Design and Implementation Study.
J Med Internet Res 2026;28:e86249. URL: https://www.jmir.org/2026/1/e86249. doi: 10.2196/86249

Join us #

Our goal is to grow this into a community, and we are eager to collaborate, in AI and well beyond it. The definitions repository and the tools keep growing, and we would love your contributions.

• Paper: dx.doi.org/10.2196/86249

Every definition that becomes machine-readable is one more piece of a faster, more standardized global disease surveillance system.