Data Analytics for Pandemics A COVID-19 Case Study

Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-...

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Bibliographic Details
Main Authors Shinde, Gitanjali Rahul, Kalamkar, Asmita Balasaheb, Mahalle, Parikshit N., Dey, Nilanjan
Format eBook Book
LanguageEnglish
Published Boca Raton, Fla CRC Press 2021
Taylor & Francis Group
Edition1
SeriesIntelligent Signal Processing and Data Analysis
Subjects
Big Data
big data analytics
BIOMEDICALSCIENCEnetBASE
BIOSCIENCEnetBASE
COMPUTERSCIENCEnetBASE
COVID-19
COVID-19 (Disease)
COVID-19 (Disease) > Data processing
COVID-19 (Disease) > Forecasting
COVID-19 (Disease) > Statistical methods
Data Preparation & Mining
Data Processing
epidemic trend analysis
Epidemiology
Infectious Diseases
INFORMATIONSCIENCEnetBASE
Knowledge Extraction
Mitigation
Pandemic
Prediction
SCI-TECHnetBASE
Statistical methods
STATSnetBASE
STMnetBASE
timeline progression
Object Storage
Infant Feeding Options
Big Data Analytics
Cluster Transmission
Data Preprocessing
Amazon S3
ASOS
Pregnant Ladies
Ml Model
NTT
Cloud Platforms
Semi-supervised Learning
Hybrid Neural Network Models
Block Storage
Data Preprocessing Techniques
Knowledge Extraction
Object Storage Service
Community Mitigation
Big Data
NTT DOCOMO
Situational Awareness
Storage Service
Big Data Tools
Data Cleaning Tools
MERS
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Table of Contents:
  • Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgment -- Authors -- Chapter 1 COVID-19 Outbreak -- 1.1 Introduction -- 1.2 Epidemic and Pandemic Overview -- 1.2.1 Stages of Disease -- 1.2.2 Pandemic Phases -- 1.2.2.1 Pandemic Risk Factors -- 1.2.2.2 Pandemic Mitigation -- 1.2.2.3 Situational Awareness -- 1.2.2.4 History of Pandemics -- 1.3 Novel Coronavirus -- 1.4 Medical Overview - Nature and Spread -- 1.5 Vulnerability Index -- References -- Chapter 2 Data Processing and Knowledge Extraction -- 2.1 Data Sources and Related Challenges -- 2.2 Data Storage: Platform -- 2.2.1 Storage Services -- 2.2.2 Big Data Analytics Services -- 2.2.3 Data Warehousing Services -- 2.3 Data Processing -- 2.3.1 Missing Values Imputation -- 2.3.2 Noise Treatment -- 2.4 Knowledge Extraction -- 2.4.1 Knowledge Extraction Based on Data Types -- 2.4.1.1 Knowledge Extraction from Text Data -- 2.4.1.2 Knowledge Extraction from Image Data -- 2.4.1.3 Knowledge Extraction from Audio Data -- 2.4.1.4 Knowledge Extraction from Video Data -- 2.4.2 Knowledge Extraction Techniques -- References -- Chapter 3 Big Data Analytics for COVID-19 -- 3.1 All You Need to Know -- 3.1.1 WEB 2.0 -- 3.1.2 Critical Thinking -- 3.1.3 Statistical Programming (R/Python) -- 3.1.4 R Programming Language -- 3.1.5 Python Programming Language -- 3.2 Data Visualization -- 3.2.1 Big Data Analytics and COVID-19 -- 3.2.1.1 Statistical Parameters -- 3.2.1.2 Predictive Analytics -- 3.3 Data Models and Performance -- 3.3.1 Data Modeling Phases -- 3.3.2 Ensemble Data Model -- 3.3.3 Model Performance -- 3.4 Big Data Techniques -- 3.4.1 Association Rule Learning -- 3.4.2 Classification Tree Analysis -- 3.4.3 Genetic Algorithm -- 3.4.4 Machine Learning -- 3.4.5 Regression Analysis -- 3.4.6 Social Network Analysis -- 3.5 Big Data Tools and Technology
  • References -- Chapter 4 Mitigation Strategies and Recommendations -- 4.1 Case Studies of COVID-19 Outbreak: Global Scenario -- 4.1.1 COVID-19 Spread in China -- 4.1.2 COVID-19 Spread in Italy -- 4.1.3 COVID-19 Spread in the United States -- 4.2 Mitigation Strategies and Discussion -- 4.3 Issues and Challenges -- 4.4 Recommendations -- 4.4.1 Recommendations for Citizens -- 4.4.2 Recommendations for COVID-19 Suspected and Infected Patients -- 4.4.3 Recommendations for Hospital Management: Adults -- 4.4.3.1 IPC Measures -- 4.4.4 Recommendations and Caring for Pregnant Ladies -- 4.4.5 Recommendations for Quarantine -- 4.5 Conclusions -- 4.6 Future Outlook -- References -- Index