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Successful interventions by public health authorities will require quantitative modelling for evaluating trade-offs and prioritization. Herein, we reviewed methodologies for One Health modelling relevant to the food system and proposed a framework for supporting international and national One Health initiatives within governmental institutions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study first identified an operational scope of One Health by reviewing the One Health Joint Plan of Action (OH-JPA) for proposed activities related to the food system. Then we cross-referenced their implementation within the Group of 20 countries through a review of their publicly available One Health resources. We next conducted a PRIMSA scoping review on One Health quantitative modelling with relevance to the food system from 2021 to 2026 to determine interdisciplinary collaboration, data types, and modelling methodologies. Lastly, we developed a conceptual framework for modelling within One Health initiatives involving the food system.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We found a narrow scope of institutional initiatives at the intersection of One Health and the food system. The activities proposed in the OH-JPA and executed in G20 governments focused on coordination, interoperability, and data sharing to support programs on antimicrobial resistance, zoonoses, and vector-borne diseases. The scoping review produced 129 relevant One Health research articles. In addition to epidemiologic data, One Health modelling used agricultural, geospatial, and ecological data for supporting food system topics. Quantitative modelling approaches either used heterogenous data, incorporated mixed effects, or integrated multiple models for scenario analysis. We proposed a modular framework for the operationalization of modelling in institutions to support interdisciplinary collaboration between food systems and One Health research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>One Health is a holistic approach, but in practice is narrowly implemented. Quantitative modelling in One Health reflects the complex dynamics in the animal-human-environment interface. Infrastructure for genomic, geospatial, and agricultural data would facilitate interdisciplinary modelling approaches beneficial for One Health in the food system.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12889-026-29666-2","type":"journal-article","created":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T03:33:13Z","timestamp":1790998393000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Interdisciplinary modelling approaches for One Health in agri-food systems: a scoping review and conceptual analysis"],"prefix":"10.1186","volume":"26","author":[{"given":"Thomas Art","family":"Burke","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antje","family":"Risius","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,3]]},"reference":[{"key":"29666_CR1","doi-asserted-by":"crossref","unstructured":"FAO, UNEP, WHO., WOAH. 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