{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:50:35Z","timestamp":1782989435319,"version":"3.54.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686684","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T00:00:00Z","timestamp":1782691200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,29]]},"abstract":"<jats:p>Artificial intelligence (AI)-enabled public health surveillance systems have expanded rapidly following the COVID-19 pandemic, yet governance and implementation structures guiding their deployment remain inconsistently defined. We conducted a scoping review following PRISMA-ScR guidelines to examine governance and regulatory frameworks associated with AI-enabled surveillance systems. A search of three databases yielded 707 unique records after deduplication. Preliminary findings indicate a predominance of centralized governance models and limited explicit articulation of equity safeguards or public oversight mechanisms. Results will provide a typology of centralized, federated, and hybrid governance models characterized by authorization structure, data governance architecture, oversight mechanisms, and equity safeguards, to inform the design of accountable AI surveillance systems.<\/jats:p>","DOI":"10.3233\/shti260831","type":"book-chapter","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:00:23Z","timestamp":1782986423000},"source":"Crossref","is-referenced-by-count":0,"title":["AI-Enabled Public Health Surveillance: Interim Findings from a Scoping Review of Governance and Implementation Frameworks"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-5940-017X","authenticated-orcid":false,"given":"Erika","family":"Ito","sequence":"first","affiliation":[{"name":"Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leroy","family":"Harris","sequence":"additional","affiliation":[{"name":"Adloris Foundation, Inc."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sigfried","family":"Gold","sequence":"additional","affiliation":[{"name":"Adloris Foundation, Inc."},{"name":"Johns Hopkins University School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adler","family":"Archer","sequence":"additional","affiliation":[{"name":"Adloris Foundation, Inc."},{"name":"Johns Hopkins University School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Health Sciences Informatics Leads and Empowers the Digital Health Transformation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260831","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:00:24Z","timestamp":1782986424000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260831"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,29]]},"ISBN":["9781643686684"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260831","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,29]]}}}