Predictive Models for Decision Support in the COVID-19 Crisis

✍ Scribed by Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong

Publisher: Springer International Publishing;Springer
Year: 2021
Tongue: English
Leaves: 103
Series: SpringerBriefs in Applied Sciences and Technology
Edition: 1st ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-vii
Prediction for Decision Support During the COVID-19 Pandemic (Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong)....Pages 1-13
Epidemiology Compartmental Models—SIR, SEIR, and SEIR with Intervention (Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong)....Pages 15-39
Forecasting COVID-19 Time Series Based on an Autoregressive Model (Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong)....Pages 41-54
Nonlinear Prediction for the COVID-19 Data Based on Quadratic Kalman Filtering (Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong)....Pages 55-68
Artificial Intelligence Prediction for the COVID-19 Data Based on LSTM Neural Networks and H2O AutoML (Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong)....Pages 69-87
Predicting the Geographic Spread of the COVID-19 Pandemic: A Case Study from Brazil (Joao Alexandre Lobo Marques, Francisco Nauber Bernardo Gois, José Xavier-Neto, Simon James Fong)....Pages 89-98

✦ Subjects

Engineering; Engineering Economics, Organization, Logistics, Marketing; Epidemiology; Operations Research/Decision Theory; Data Mining and Knowledge Discovery; Health Promotion and Disease Prevention

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