Aug 2026
Artificial Intelligence for Epidemic Preparedness: Innovations and Insights from the Global South (forthcoming)
Edited by Christo El Morr, Antoine Saab, and Elie Salem-Sokhn
How can Artificial Intelligence strengthen our collective capacity to predict, detect, and respond to epidemics—while advancing equity and justice?
As pandemics continue to expose global health vulnerabilities, Artificial Intelligence for Epidemic Preparedness: Innovations and Insights from the Global South brings together scholars and practitioners from diverse disciplines and regions to critically examine how AI can transform epidemic surveillance, health systems, and community resilience without reproducing historical inequities.
Spanning four major sections--Foundations and Cross-Cutting Themes; AI for Early Detection, Surveillance, and Prediction; AI Applications for Health Equity and Community Well-Being; and AI Governance, Ethics, and Equity—this volume moves from conceptual and methodological mapping to cutting-edge applications and governance frameworks. Chapters explore innovative AI-driven diagnostics, real-time surveillance, culturally aware design, and decolonial approaches to data and algorithmic decision-making.
Contributors interrogate the promises and perils of AI in epidemic preparedness, asking not only what can be predicted, but who benefits and who may be left behind. The book invites researchers, policymakers, technologists, and global health practitioners to rethink AI beyond technical innovation—toward tools and systems that build fairer, more resilient futures in the face of emerging health crises.
Edited by Christo El Morr, Antoine Saab, and Elie Salem-Sokhn
How can Artificial Intelligence strengthen our collective capacity to predict, detect, and respond to epidemics—while advancing equity and justice?
As pandemics continue to expose global health vulnerabilities, Artificial Intelligence for Epidemic Preparedness: Innovations and Insights from the Global South brings together scholars and practitioners from diverse disciplines and regions to critically examine how AI can transform epidemic surveillance, health systems, and community resilience without reproducing historical inequities.
Spanning four major sections--Foundations and Cross-Cutting Themes; AI for Early Detection, Surveillance, and Prediction; AI Applications for Health Equity and Community Well-Being; and AI Governance, Ethics, and Equity—this volume moves from conceptual and methodological mapping to cutting-edge applications and governance frameworks. Chapters explore innovative AI-driven diagnostics, real-time surveillance, culturally aware design, and decolonial approaches to data and algorithmic decision-making.
Contributors interrogate the promises and perils of AI in epidemic preparedness, asking not only what can be predicted, but who benefits and who may be left behind. The book invites researchers, policymakers, technologists, and global health practitioners to rethink AI beyond technical innovation—toward tools and systems that build fairer, more resilient futures in the face of emerging health crises.