Data Analytics for Pandemics: A COVID-19 Case Study (Intelligent Signal Processing and Data Analysis)

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 discussion 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 scenario.
• Explains how different big data analytics techniques can be implemented.
• Provides set of recommendations to minimize infection rate of COVID-19.
• Summarizes various techniques of data processing and knowledge extraction.
• Enables user to understand big data analytics techniques required for prediction purpose.