ArticleFrontiers in digital health2026
AI-generated medical realism and hantavirus misinformation: a new public health threat?
Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
10 authors.
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Abstract
The widespread availability of generative artificial intelligence (AI) has substantially reshaped the health-information environment compared with the COVID-19 pandemic. Contemporary AI tools can rapidly generate highly realistic medical-looking content from text, including laboratory reports, radiological images, histological slides, and institutional clinical documentation. During infectious disease outbreaks, such simulated medical content may exploit the visual authority traditionally associated with healthcare institutions and influence public risk perception. During media coverage of the May 2026 Andes virus (ANDV) alert in Italy, news outlets published realistic AI-generated medical imagery depicting hantavirus diagnostic reports, hospital-associated laboratory materials, and outbreak-response scenes linked to real healthcare institutions. One image, in particular, reproduced the visual identity of a real laboratory report produced at "Luigi Sacco" University Hospital despite displaying multiple inconsistencies. In some additional examples, AI generation was not clearly disclosed despite the use of recognizable institutional names and logos. This phenomenon has the potential to extend beyond isolated misinformation events. Emerging evidence indicates that experts may struggle to reliably distinguish AI-generated biomedical and radiological images from authentic materials, raising concern that future infectious disease outbreaks may occur within an information ecosystem increasingly shaped by visually persuasive synthetic media. Such content may amplify public anxiety, distort perceptions of authority, and erode trust in institutions. Synthetic medical realism should therefore be considered a potential emerging category of public-health risk during infectious disease emergencies that requires coordinated action from institutions and regulators developing verification systems, while news media, platforms, and publishers implement AI-disclosure standards and guidelines for synthetic biomedical content.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.