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◆ BMC proceedings2026-09-21

Leveraging AI for infectious disease modelling and public health decision making.

Moritz U G Kraemer, Barbara Tornimbene, Samir Bhatt, Serina Chang, Gautam Prasad, Milind Tambe, Houriiyah Tegally, Oliver Morgan

原始摘要(英文原文)· Original abstract
Artificial intelligence (AI) is expanding the capacity of public health systems to detect infectious disease signals, forecast outbreaks, analyse pathogen evolution, generate localised risk estimates, and support operational decisions. The thirteenth session of the WHO Pandemic and Epidemic Intelligence Innovation Forum brought together experts from academic, public health, and technology organisations to examine current applications of AI in infectious disease modelling and pandemic preparedness. Examples included genomic surveillance, hybrid epidemiological and machine-learning models, spatial foundation models, AI-enabled decision support, and agent-based simulations for resource allocation. Participants emphasised that technical performance alone is insufficient: tools must be transparent, auditable, transferable across settings, operationally usable, and responsive to local data and infrastructure constraints. Sustained interdisciplinary collaboration, human oversight, robust validation, and equitable design will be essential to embed AI safely and effectively within public health decision-making.
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Leveraging AI for infectious disease modelling and public health decision making. — 科研速览 Science Skim