Data Analytics for Pandemics A COVID-19 Case Study

• Main Authors: Shinde, Gitanjali Rahul, Kalamkar, Asmita Balasaheb, Mahalle, Parikshit N., Dey, Nilanjan
• Format: eBook Book
• Language: English
• Published: Boca Raton, Fla CRC Press 2021; Taylor & Francis Group
• Edition: 1
• Series: Intelligent 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
• ISBN: 0367558467; 9780367564957; 0367564955; 9780367558468
• DOI: 10.1201/9781003095415

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-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.