The recent COVID-19 global pandemic exemplifies the need for efficient, reliable, and real-time tools and technology for forecasting and predicting healthcare disasters as well as for helping to restrict the subsequent spread and fatality of deadly diseases. This new book discusses many of the innovative and state-of-the-art tools and technology that can help meet the challenges of predicting such disasters. The chapters offer a plethora of useful information for designing healthcare disaster management systems that can be dynamically configurable with implementation of today’s modern technology, such as cloud computing, artificial intelligence, IoT, data analytics, and machine learning. These can increase effectiveness in remote sensing technologies, data analytics, data storage, communication networks, geographic information system (GIS), and global positioning System (GPS), to name a few.
This book discusses mathematical models using graph-based approaches for analyzing dynamic, heterogeneous, and unstructured data for applications in epidemiology. The authors also address the use of mobile applications for communication efforts and remote monitoring for gauging health and the effectiveness of preventive healthcare measures. The chapters discuss influencing factors that directly or indirectly target public health infrastructure that can lead to or exacerbate global health crises, such as extreme climate changes, refugee health crises, terrorism and cyberterrorism, and technology-related incidents. The book further looks at efficient methods to analyze disasters and how to deliver healthcare in areas of conflict and crisis.
This important volume, Global Healthcare Disasters: Predicting the Unpredictable with Emerging Technologies, provides a bounty of useful information for health professionals, academicians, researchers, governmental agencies, and policymakers across the world to predict, mitigate, and manage global health disaster with emerging technologies.
Author(s): Adarsh Garg, D. P. Goyal
Publisher: CRC Press/Apple Academic Press
Year: 2022
Language: English
Pages: 221
City: Palm Bay
Cover
Half Title
Title Page
Copyright Page
Dedicated
Table of Contents
Contributors
Abbreviations
Acknowledgments
Preface
Chapter 1: Role of Knowledge Graphs in Analyzing Epidemics and Health Disasters
Chapter 2: Forecasting of COVID-19 with the ARIMA Model in India as a Preventive Measure of Healthcare Catastrophe
Chapter 3: Role of Artificial Intelligence in the Era of COVID-19 to Improve Hospital Management
Chapter 4: Challenges of Global Healthcare Disasters
Chapter 5: Healthcare Disaster Prediction with IoT, Data Analytics, and Machine Learning
Chapter 6: Effectiveness of Aarogya Setu Mobile Application During COVID-19 Healthcare Management: A Technology Acceptance Model-Based Approach
Chapter 7: CoReS-Respiratory Strength Predicting Framework Using Noninvasive Technology for Remote Monitoring During Heath Disasters
Chapter 8: Exploring the Scope of Policy Issues Influencing IoT Health and Big Data: A Structured Review
Chapter 9: COVID-19 Disaster Healthcare Management System in Rural Areas
Chapter 10: Sentiment Analysis for Sustainable Healthcare During Pandemic Outbreak: Lessons Learned from COVID-19
Chapter 11: Design Schema to Offer Security and Confidentiality to Healthcare Data in Cloud Environment
Index
