Global Healthcare Disasters (eBook, ePUB)

Predicting the Unpredictable with Emerging Technologies

Redaktion: Garg, Adarsh; Goyal, D. P.

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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.

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Adarsh Garg, PhD, is currently Professor (IT and Analytics), GL Bajaj Institute of Management and Research, Greater Noida, India. She was formerly Professor at Galgotias University, Gautam Buddh Nagar, Greater Noida, India, and Visiting Professor at Delhi Technical University, Delhi, India. Prior to joining Galgotias University, she worked with organizations including WIPRO Tech, GE, IMT Ghaziabad, Punjabi University, and Patiala. She is currently supervising several PhD candidates. Dr. Garg has published over 50 research papers in refereed international/national journals and conference proceedings. She is a member of various professional bodies, including the Computer Society of India and the ACM-Computer Science Teachers' Association. She has 20 years of teaching, corporate, and research within the areas of her interest, which include business analytics, data mining, business intelligence, MIS, e-learning, and project management experience. D. P. Goyal, PhD, Director and Professor at the Indian Institute of Management, Shillong, India, and is also a visiting professor at Aarhus University, Denmark. Prior to joining IIM Shillong, he was Professor at MDI¿ Gurgaon, India. He has more than 32 years of corporate, teaching, and research experience to his credit. His teaching and research interest areas include IS value, IS strategy, MIS, e-government, and business process management. He has published over 100 research papers in refereed international/national journals and conference proceedings. He is a member of various professional bodies and is associated with many business schools and universities in the capacity of member of Board of Governors, Academic Council, Board of Studies, Academic Advisory Board, etc. He has been a consultant to the government of India for various assignments, and has authored almost 20 books, including textbooks on management information systems, IT project management, and enterprise resource planning.