Oct 2026· npj Digital Public Health· Vol 1· 0 citations· 94 references
TL;DR
This work proposes reframing early warning as the perceptual foundation of AI-native decision intelligence for public health governance, and introduces ACCESS—integrating situational sensing, cognitive reasoning, scenario simulation, collective coordination, explainable accountability, and adaptive evolution.
Abstract
Epidemic early warning has been framed mainly as prediction, yet sophisticated forecasts often fail to translate into timely, coordinated action. We propose reframing early warning as the perceptual foundation of AI-native decision intelligence for public health governance, and introduce ACCESS—integrating situational sensing, cognitive reasoning, scenario simulation, collective coordination, explainable accountability, and adaptive evolution. This conceptual framework prioritizes decision robustness, transparency, and human accountability over predictive accuracy alone.
This policy brief highlights the urgent need for responsible AI governance through international standards, explainable algorithms, independent validation, strong data protection, and inclusive stakeholder engagement to maximize its potential for improving disease surveillance and global health security.
Abdullahi Osman Mohamed, A. Afyare, Abdinasir Mohamed Abdi et al.· Frontiers in Digital Health· 0 citations
A review of infectious disease surveillance platforms examined 20 platforms according to primary data inputs, surveillance function, AI methods, data privacy, geographic scope and pathogen focus and three archetypes emerged: Early Warning Networks, Situational Awareness Platforms and Integrated Surveillance Platforms.
Marya Getchell, Michael Barber, Tom Carpino et al.· npj Digital Medicine· 1 citation· ⚡1
Conflict early-warning systems have evolved significantly with the emergence of big data, artificial intelligence, and machine learning, offering new opportunities to anticipate violent conflict and support timely preventive interventions. This paper examines the use of big data in conflict early-warning, focusing on t...
K. Samuel J.· IDOSR Journal of Arts and Ma...· 0 citations
El Niño creates an important opportunity for anticipatory public health action because its development can often be detected before many downstream hazards emerge. Yet predictability does not transfer uniformly from the large-scale El Niño Southern Oscillation (ENSO) signal to regional climate anomalies and ultimately...
L. Bajrai, E. Azhar· Frontiers in Public Health· 0 citations
A structured framework of behavioral indicators that may signal progression toward potentially catastrophic threats from artificial intelligence systems is presented, inspired by established methodologies in cybersecurity and national security.
T. Bauer, W. Kegelmeyer, Edmon Begoli et al.· 0 citations
A theoretical framework is developed that conceptualizes AI implementation in disease surveillance as simultaneously a socio-technical and normative process and offers a structured perspective for designing more context-sensitive, ethically grounded, and institutionally sustainable AI-enabled disease surveillance syste...
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
