What Can Data and Analytics Tell Us About COVID-19?

Throughout history, data and analytics have had a profound impact on human health-including isolating the source of London's cholera epidemic in the 1850s and promotion of new routine practices such as hand washing following the Crimean War. What Can Data and Analytics Tell Us About COVID-19? explores the power of analytics to shed light on the novel coronavirus that has threatened the health and economic welfare of people across the globe. This text familiarizes readers with different concepts related to data science, big data technology, and the various applications of machine learning algorithms for analyzing the available data on the global problem related to COVID-19. Covers how different methods, techniques, and powerful tools of data science and machine learning can be utilized to analyze and understand COVID-19. Features chapters on machine learning algorithms and patterns for COVID-19, data visualization and COVID-19 geography, patterns of confirmed cases, and more. Includes ample case studies. Consolidates today's available information on this timely topic into a single, convenient resource.

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.

The tourism sector has been deeply affected particularly in economic terms by the COVID-19 pandemic. This crisis has led to new practices and radical changes. Scientists emphasize that mankind will face pandemics more frequently in the forthcoming years. Thus, it is important to understand the negative impacts the COVID-19 pandemic had on the tourism sector as well as the measures that were and are being put in place to protect the industry during future outbreaks. The Handbook of Research on the Impacts and Implications of COVID-19 on the Tourism Industry is a comprehensive reference source that reflects upon the evaluations of the experienced and ongoing pandemic crisis in the context of the tourism sector. The positive and negative effects experienced by tourism employees and tourists are examined, and post-pandemic processes and business practices are evaluated. Covering topics including consumer rights in tourism, dynamic changes in the tourism industry, and employment in tourism, this book is suitable for travel agencies, restaurateurs, hotel managers, brand managers, marketers, advertisers, managers, executives, hospitality personnel, policymakers, government officials, tourism practitioners, students, academicians, and researchers seeking the latest sustainable policies and practices that are being utilized to increase the productivity of the tourism sector and will allow it to thrive in the years to come.

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions

"In our increasingly digitally enabled education world, analytics used ethically, strategically, and with care holds the potential to help more and more diverse students be more successful on higher education journeys than ever before. Jay Liebowitz and a cadre of the fields best ‘good trouble’ makers in this space help shine a light on the possibilities, potential challenges, and the power of learning together in this work." —Mark David Milliron, Ph.D., Senior Vice President and Executive Dean of the Teachers College, Western Governors University Due to the COVID-19 pandemic and its aftereffects, we have begun to enter the "new normal" of education. Instead of online learning being an "added feature" of K–12 schools and universities worldwide, it will be incorporated as an essential feature in education. There are many questions and concerns from parents, students, teachers, professors, administrators, staff, accrediting bodies, and others regarding the quality of virtual learning and its impact on student learning outcomes. Online Learning Analytics is conceived on trying to answer the questions of those who may be skeptical about online learning. Through better understanding and applying learning analytics, we can assess how successful learning and student/faculty engagement, as examples, can contribute towards producing the educational outcomes needed to advance student learning for future generations. Learning analytics has proven to be successful in many areas, such as the impact of using learning analytics in asynchronous online discussions in higher education. To prepare for a future where online learning plays a major role, this book examines: Data insights for improving curriculum design, teaching practice, and learning Scaling up learning analytics in an evidence-informed way The role of trust in online learning. Online learning faces very real philosophical and operational challenges. This book addresses areas of concern about the future of education and learning. It also energizes the field of learning analytics by presenting research on a range of topics that is broad and recognizes the humanness and depth of educating and learning.

This book showcases the different ways in which contemporary forms of data analysis are being used in urban planning and management. It highlights the emerging possibilities that city-regional governance, technology and data have for better planning and urban management - and discusses how you can apply them to your research. Including perspectives from across the globe, it’s packed with examples of good practice and helps to demystify the process of using big and open data. Learn about different kinds of emergent data sources and how they are processed, visualised and presented. Understand how spatial analysis and GIS are used in city planning. See examples of how contemporary data analytics methods are being applied in a variety of contexts, such as ‘smart’ city management and megacities. Aimed at upper undergraduate and postgraduate students studying spatial analysis and planning, this timely text is the perfect companion to enable you to apply data analytics approaches in your research.

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.

Trust Creating the Foundation for Entrepreneurship in Developing Countries Entrepreneurial ventures often fail in the developing world because of the lack of something taken for granted in the developed world: trust. Over centuries the developed world has built up customs and institutions like enforceable contracts, an impartial legal system, credible regulatory bodies, even unofficial but respected sources of information like Yelp or Consumer Reports that have created a high level of what scholar and entrepreneur Tarun Khanna calls “ambient trust.” If a product is FDA-approved we feel confident it's safe. If someone makes an untrue claim or breaks an agreement we can sue. Police don't demand bribes to do their jobs. Certainly there are exceptions, but when brought to light they provoke a scandal, not a shrug. This is not the case in the developing world. But rather than become casualties of mistrust, Khanna shows that smart entrepreneurs adopt the mindset that, like it or not, it's up to them to weave their own independent web of trust—with their employees, their partners, their clients, their customers and with society as a whole. This can certainly be challenging, and requires innovative approaches in places where the level of societal mistrust is so high that, as in one example Khanna provides, an official certification of quality simply arouses suspicion—and lowers sales! Using vivid examples from Brazil, China, India, Mexico and elsewhere, Khanna shows how entrepreneurs can build on existing customs and practices instead of trying to push against them. He highlights the role new technologies can play (but cautions that these are not panaceas), and explains how entrepreneurs can find dependable partners in national and local governments to create impact at scale. As far back as the 18th century Adam Smith recognized trust as what Khanna calls “the hidden engine of economic progress.” “Frankness and openness conciliate confidence,” Smith wrote. “We trust the man who seems willing to trust us.” That kind of confidence is critical to entrepreneurial success, but in the developing world entrepreneurs have to establish it through their own efforts. As Khanna puts it, “the entrepreneur must not just create, she must create the conditions to create.”

The novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource for computer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences

This forward-thinking book examines the future of public policy as a discipline, both as it is taught and as it is practiced. Critically assessing the limits of current theories and approaches, leading scholars in the field highlight new models and perspectives.

"a provocative new book" -- The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning--to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples--including many from the most powerful and innovative global, AI-driven competitors--and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.

This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book: Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19 Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreak Examines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19 Includes different case studies on COVID-19 Dr. Chhabi Rani Panigrahi is Assistant Professor in the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Bibudhendu Pati is Associate Professor and Head of the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Mamata Rath is Assistant Professor in the School of Management (Information Technology) at Birla Global University, Bhubaneswar, India. Prof. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia.

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.

The days of going to the local department store to buy a television, view the options available and make a purchase, now seem "quaint." The emergence of the internet, smart phones, social media, and other technologies has opened a world of new options for consumers (and businesses) to review, research, and buy online with an ever-increasing array of delivery options. The emergence of e-commerce has resulted in what is commonly known today as "omni-channel" marketing, in which customers engage with companies in a variety of ways, including in a physical store, online via websites and mobile apps. This process puts the supply chain "front and center" as consumers are increasingly demanding and browse, buy, and return goods through various channels and not just the traditional "brick and mortar" way. To accomplish this with high levels of service while remaining profitable, requires real-time visibility of inventory across the supply chain and a single view of the consumer as they continuously move from one channel to another. While this is a boon to consumers, it has made the already complex global supply chain even more challenging to manage. On top of that, the 2020 Covid19 Pandemic has accelerated this omni-channel retail trend as consumers need even more ways to order and additional options for last mile delivery, such as curbside pickup. Covid19 has exposed the lack of flexibility and readiness resulting in shortages of everything from toilet paper and meats to "PPE" (personal protective equipment) and ventilators, due to a variety of capacity and inventory allocation issues. It has been a real-life example of the "bullwhip effect", where variability at the consumer end of the supply chain results in increased variability as you go upstream towards distributors, manufacturers, and suppliers. This results in shortages, misallocation, and increased costs. No longer can a manufacturer, distributor, or retailer of consumer products just "fill the pipeline" and wait for orders to come in. Now they must anticipate the various purchase and delivery items, while at the same time minimize costs. To do this is no easy task, requiring a Lean, agile, and responsive supply chain. Until now, there was no existing "playbook" for organizations to navigate their way through this new world. This book describes the impact of omni-channel marketing on the supply chain and logistics functions, and is intended to help management meet the needs of not only today’s ever-changing world but to anticipate what may be required in the future to achieve superior customer service, profitability, and a competitive advantage.

Lead through the crisis and prepare for recovery. As the Covid-19 pandemic is exacting its toll on the global economy, forward-looking organizations are moving past crisis management and positioning themselves to leap ahead when the worst is over. What should you and your organization be doing now to address today's unprecedented challenges while laying the foundation needed to emerge stronger? Coronavirus: Leadership and Recovery provides you with essential thinking about managing your company through the pandemic, keeping your employees (and yourself) healthy and productive, and spurring your business to continue innovating and reinventing itself ahead of the recovery. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues—blockchain, cybersecurity, AI, and more—each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas—and prepare you and your company for the future.