Predictive Models for Decision Support in the COVID-19 Crisis

Joao Alexandre Lobo Marques author Simon James Fong author Francisco Nauber Bernardo Gois author José Xavier-Neto author

Format:Paperback

Publisher:Springer Nature Switzerland AG

Published:1st Dec '20

Should be back in stock very soon

Predictive Models for Decision Support in the COVID-19 Crisis cover

COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations.

Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.

“This book is … of great interest for mathematical modelers--it nicely summarizes many important tools, with concrete examples, that could be adapted for other situations. … I strongly recommend this book to advanced undergraduate engineers and mathematicians as well as specialists dealing with dynamical system modeling.” (Arturo Ortiz-Tapia, Computing Reviews, July 26, 2022)

ISBN: 9783030619121

Dimensions: unknown

Weight: unknown

98 pages

1st ed. 2021