Publication date: Jun 29, 2026
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.
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Semantics
| Type | Source | Name |
|---|---|---|
| disease | MESH | COVID-19 pandemic |
| disease | MESH | Ito |
| drug | DRUGBANK | Factor IX Complex (Human) |
| disease | MESH | PCC |