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Full Description
This book describes the work to be done in building an automated pandemic prevention and response capability for the US with international extensions and extendibility using artificial intelligence. The complexity of operational decisions, information sharing, situational awareness, and planned/ongoing actions by thousands of actors in pandemic prevention, preparedness and response is far too great for anyone to manage effectively. The deaths and economic devastation caused by COVID-19 yet again proved this fact, much like all other major disasters we have endured. There are too many organisations, too many differing plans and agendas, too many different people of varying experience in positions of responsibility, and too much information as well as critical need for optimal decisions and actions, to avoid calamity during the inevitable next pandemic. We need automated planning, information vetting/sharing and rapid action to optimize prevention and, if not prevented, response to minimize spread. Volume I laid out the case for a better approach than exists in the U.S. today, and our nation's military -- touted as the best in the world -- employs methodologies with precision and fidelity that optimise rapid decision making for human-sized enemies. It turns out these same methodologies and associated technologies work just as well with our microscopic enemies, like COVID-19. This book provides an overview of how it should be developed, implemented and evolved nationwide before the next pandemic. Seems like we finally should get our "act" together, otherwise the toll for passage of the next virus could be far higher as we remain unprepared. It will be hard and extensive work, which some have referenced the "Manhattan Project" or the Apollo Program, but the COVID-19 death count mandates we apply our best effort to prevent another pandemic disaster. We are better equipped now than ever to do so.
Contents
Dedication; Foreword; Prologue; Introduction; COVID-19 and Other Disasters: Applying the Lessons Learned; Organizational Enterprise Synthesis of Effective Pandemic Collaboration; Pandemic Response Collaboration Planning; The AI Plan-ning Engine; The SHOULD-BE Implementation Plan; Epilogue; Acknowledgments; Biographies; Epigraph.
