Predictive And Preventive Measures For Covid 19 Pandemic

This book explores the inputs with regard to individuals and companies who have developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, etc., that can be leveraged for strengthening the fight against coronavirus. It focuses on technology solutions to stop Covid-19 outbreak and mitigate the risk. The book contains innovative ideas from active researchers who are presently working to find solutions, and they give insights to other researchers to explore the innovative methods and predictive modeling techniques. The novel applications and techniques of established technologies like artificial intelligence (AI), Internet of things (IoT), big data, computer vision and machine learning are discussed to fight the spread of this disease, Covid-19. This pandemic has triggered an unprecedented demand for digital health technology solutions and unleashing information technology to win over this pandemic.

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention, and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic socio-economic structure. The book offers a comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior A detailed overview of CI techniques Intelligent modeling, prediction, and diagnostic measures for pandemics Prognostic models Post-pandemic socio-economic structure The accompanying case studies are based on available real-world data sets. While other books may deal with this COVID-19 pandemic, none features topics covering the human immune system as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to benefit medical professionals and healthcare workers as well as the virologists who are essentially the frontline fighters of this pandemic. In addition, it also serves as a vital resource for relevant researchers in this interdisciplinary field as well as for tutors and postgraduate and undergraduate students of information sciences.

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.

The COVID-19 pandemic has highlighted the importance of health data, technology, and access to health informatics. The applications of several information technologies in the context of healthcare are proving instrumental in pandemic control. These technologies were already actively used in the healthcare sector before the pandemic. However, the pandemic has resulted in researchers reassessing how these technologies could have better assisted with the aftermath of the COVID-19 pandemic and how they may mitigate the threat of future pandemics. Health Informatics and Patient Safety in Times of Crisis provides a fresh perspective on how healthcare informatics has managed the current pandemic and how improved healthcare informatics could help in a future crisis. Covering topics such as digital public health, misinformation, and knowledge management, this premier reference source is an indispensable resource for medical professionals, hospital administrators, public health officials, community leaders, international leaders, libraries, medical students, medical professors, researchers, and academicians.

This powerful new volume explores the diverse and sometimes unexpected roles that IoT and AI technologies played during the recent COVID-19 global pandemic. The book discusses the how existing and new state-of-the art technology has been and can be applied for global health crises in a multitude of ways. The chapters in Pandemic Detection and Analysis through Smart Computing Technologies look at exciting technological solutions for virus detection, prediction, classification, prevention, and communication outreach. The book considers the various modes of transmission of the virus as well as how technology has been implemented for personalized healthcare systems and how it can be used for future pandemics. The huge importance of social and mobile communication and networks during the pandemic is addressed such as in business, education, and healthcare; in research and development; for health information and outreach; in social life; and more. A chapter also addresses using smart computing for forecasting the damage caused by COVID-19 using time series analyses. This up-to-the-minute volume illuminates on the many ways AI, IoT, machine learning, and other technologies have important roles in the diverse challenges faced during COVID-19 and how they can be enhanced for future pandemic situations. The volume will be of high interest to those in different fields of computer science and other domains as well as to data scientists, government agencies and policymakers, doctors and healthcare professionals, engineers, economists, and many other professionals. This book will also be very helpful to faculty, students, and research scholars in understanding the pre- and post-effect of this pandemic.

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the 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 the wide variety of impacts the virus is having on societies and medical practice Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics

This book focuses on sustainability issues post COVID-19 outbreak, discusses ways to restrict global spread of the pandemic, and also how to survive holistically in the environment. It also discusses the economic impacts on the world due to the coronavirus outbreak. There is a strong need for monitoring and analysis of pandemics for sustainability like epidemic risk analysis by using pattern recognition or the mental health challenges during an outbreak. This book presents ways to find solutions and gives insights to explore innovative methods and predictive modeling techniques, such that masses are prevented from pandemics.​

Geographic Information System (GIS) is one of the most important tools to help us understand public health and many aspects of our lives. Because of COVID-19, GIS has been brought into the spotlight more than ever before. People and civic leaders worldwide are turning to maps and real-time surveillance data to make sense of what has been happening in the world and to get answers to important questions on every aspect of this pandemic. This book examines the role of GIS in managing and controlling the spread of COVID-19 through 12 global projects and a multidisciplinary approach. It explains the innovative uses of GIS not only limited to data organization and data access, but also how improved GIS tools are used to make decisions, plan, and communicate various measures of control in both local and full-scale outbreaks during the COVID-19 pandemic. Features: Provides cutting-edge GIS visualization, spatial temporal pattern, and hot spot tracking applications used for predictive modeling of COVID-19. Includes real-world case studies with broad geographic scope that reflect COVID-19 trends in cases, deaths, and vaccinations. Provides lifestyle segmentation analysis on the risk of transmission of COVID-19 and spatial patterns of vaccination hesitancy. Highlights real-world issues brought to light with the help of GIS, such as social discrimination, inequalities in women’s access to mental health care, and analyzes the risk of transmission due to vaccination hesitancy. Shows the use of GIS and spatial analysis in pandemic mapping, management, and control from masking and social distancing to testing site locations accounting for at-risk and vulnerable populations. Discusses facilitating policy making with GIS. Edited by a very talented medical geographer and GIS Professor Dr. Esra Ozdenerol, this book highlights key GIS capabilities and lessons learned during the COVID-19 response that can help communities prepare for the next crisis. It is a great resource for industry professionals and experts in health care, public health and safety, disaster management, and for students, academics, and researchers interested in applying GIS and spatial analysis to the study of COVID-19 and other pandemics.