Full Description
This book explores innovative applications of artificial intelligence, machine learning, and modeling to enhance public and global health security. It advocates for a shift from reactive to proactive management of health crises, emphasizing systems-based futures thinking and anticipatory scenarios. Highlighting the lessons from COVID-19, the book underscores the importance of tech-enabled solutions like large-scale simulations and advanced analytics for early detection and response to biological threats. It integrates insights from ecology, climate change, and multi-hazard events, aiming to balance disease control with societal well-being. Essential for public health researchers, policymakers, and national security experts, the book offers recommendations and roadmaps for future health crisis management.
Contents
Overview of Artificial Intelligence and Machine Learning for Public Health applications.- Vector borne disease: Seek and Destroy: Malaria eradication in East Africa using AI/ML/GIS.- Building a Public Health/ Global Health Intelligence capability.- Pandemic Planning: Digital Twins to support COVID-19 management.- Decision Support for Public/Global Health.- Mapping community vulnerability to disease outbreaks: hot spot and cold spot mapping.- Tech literacy for Public Health Professionals: insights into tech enabling the public health workforce.- Applying artificial intelligence to solve humanitarian crisis dilemmas.- Implementation Science: from design to impact- bringing AI/ML solutions.- Tech informed Global Health: considering and including the cultural and social implications.- FemTech: the intersection of technology and womans health.
