Case definitions are essential for effectively communicating public health threats. However, the absence of a standardized, machine-readable format poses significant challenges to interoperability, epidemiological research, the exchange of qualitative data, and the effective application of computational analysis methods, including artificial intelligence (AI). This complicates comparisons and collaborations across organizations and regions, limits data integration, and hinders technological innovation in public health. To address these issues, we propose the first open, machine-readable format for representing case and syndrome definitions. Additionally, we introduce the first comprehensive dataset of standardized case definitions and tools to convert existing human-readable definitions into machine-readable formats. We also provide an accessible online platform for browsing, analyzing, and contributing new definitions, available at https://opensyndrome.org. The Open Syndrome Definition format enables consistent, scalable use of case definitions across systems, unlocking AI's potential to strengthen public health preparedness and response. The source code for the format can be found at https://github.com/OpenSyndrome/schema under the MIT license.
@article{arxiv.2509.25434,
title = {The Open Syndrome Definition},
author = {Ana Paula Gomes Ferreira and Aleksandar Anžel and Izabel Oliva Marcilio de Souza and Helen Hughes and Alex J Elliot and Jude Dzevela Kong and Madlen Schranz and Alexander Ullrich and Georges Hattab},
journal= {arXiv preprint arXiv:2509.25434},
year = {2025}
}