Leveraging Analytical and Artificial Intelligence for Pandemic Preparedness, Incidence Response and Public Health

The intersection of analytical modelling and artificial intelligence is rapidly reshaping our capacity to anticipate, respond to, and recover from public health crises. From the global disruption of COVID-19 to the persistent threat of emerging zoonotic diseases such as Ebola and hantavirus, the need for robust, data-driven tools across the full spectrum of public health response has never been more urgent.This Research Topic invites contributions that explore how analytical intelligence — including epidemiological modelling, statistical frameworks, and systems dynamics — and artificial intelligence — encompassing machine learning algorithms (MLAs), large language models (LLMs), and digital health technologies — can be harnessed to strengthen pandemic preparedness, support real-time incidence response, and advance precision medicine in public health contexts.We welcome original research articles, systematic reviews, perspectives, and methods papers across three interconnected themes:o Retrospective insights from COVID-19 and past outbreaks — evaluations of digital tools deployed during the COVID-19 pandemic, including digital contact tracing platforms, mobility data analytics, surveillance dashboards, and predictive modelling, with a focus on lessons learned and evidence of real-world impacto Prospective tools for emerging and re-emerging infectious diseases — computational and analytical methods designed to support preparedness and response to outbreak threats such as hantavirus, Ebola, mpox, or novel pathogens, including early warning systems, transmission modelling, and decision-support frameworkso AI applications for precision medicine and public health — deployment of machine learning and deep learning algorithms, natural language processing, and LLMs in clinical and population health settings, including disease risk stratification, drug repurposing, genomic epidemiology, and AI-assisted diagnosticsBy bridging retrospective evaluation with forward-looking innovation, this Research Topic aims to build a comprehensive evidence base for the responsible and effective integration of analytical and artificial intelligence into public health systems worldwide.We acknowledge the initiation and support of this Research Topic by University College London’s RDR Centre of Digital Public Health in Emergencies (dPHE). We hereby state publicly that UCL’s RDR Centre of dPHE has had no editorial input in articles included in this Research Topic, thus ensuring that all aspects of this Research Topic are evaluated objectively, and unbiased by any specific policy or opinion of UCL’s RDR Centre of dPHE. Topic editors: Jasmina Panovska-Griffiths Source: https://www.frontiersin.org/research-topics/86135/leveraging-analytical-and-artificial-intelligence-for-pandemic-preparedness-incidence-response-and-public-health