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Author : Longbing Cao
Publisher : Springer Nature
ISBN 13 : 9819999154
Total Pages : 409 pages
Book Rating : 4.8/5 (199 download)
Download or read book Global COVID-19 Research and Modeling written by Longbing Cao and published by Springer Nature. This book was released on with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Longbing Cao
Publisher : Springer
ISBN 13 : 9789819999149
Total Pages : 0 pages
Book Rating : 4.9/5 (991 download)
Download or read book Global COVID-19 Research and Modeling written by Longbing Cao and published by Springer. This book was released on 2024-03-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides answers to fundamental and challenging questions regarding the global response to COVID-19. It creates a historical record of COVID-19 research conducted over the four years of the pandemic, with a focus on how researchers have responded, quantified, and modeled COVID-19 problems. Since mid-2021, we have diligently monitored and analyzed global scientific efforts in tackling COVID-19. Our comprehensive global endeavor involves collecting, processing, analyzing, and discovering COVID-19 related scientific literature in English since January 2020. This provides insights into how scientists across disciplines and almost every country and regions have fought against COVID-19. Additionally, we explore the quantification of COVID-19 problems and impacts through mathematics, AI, machine learning, data science, epidemiology, and domain knowledge. The book reports findings on publication quantities, impacts, collaborations, and correlations with the economy and infections globally, regionally, and country-wide. These results represent the first and only holistic and systematic studies aimed at scientifically understanding, quantifying, and containing the pandemic. We hope this comprehensive analysis will contribute to better preparedness, response, and management of future emergencies and inspire further research in infectious diseases. The book also serves as a valuable resource for research policy, funding management authorities, researchers, policy makers, and funding bodies involved in infectious disease management, public health, and emergency resilience.
Author : Ellen Kuhl
Publisher : Springer Nature
ISBN 13 : 3030828905
Total Pages : 312 pages
Book Rating : 4.0/5 (38 download)
Download or read book Computational Epidemiology written by Ellen Kuhl and published by Springer Nature. This book was released on 2021-09-22 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19. It teaches the relevant tools to model and simulate nonlinear dynamic systems in view of a global pandemic that is acutely relevant to human health. If you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: This book is for you! It serves as a textbook for undergraduates and graduate students, and a monograph for researchers and scientists. It can be used in the mathematical life sciences suitable for courses in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming. This book is a personal reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it.
Author : Chhabi Rani Panigrahi
Publisher : CRC Press
ISBN 13 : 1000384977
Total Pages : 271 pages
Book Rating : 4.0/5 (3 download)
Download or read book Computational Modeling and Data Analysis in COVID-19 Research written by Chhabi Rani Panigrahi and published by CRC Press. This book was released on 2021-05-09 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Peter C. Earle
Publisher : American Institute for Economic Research
ISBN 13 : 1630692115
Total Pages : 278 pages
Book Rating : 4.6/5 (36 download)
Download or read book Coronavirus and Disease Modeling written by Peter C. Earle and published by American Institute for Economic Research. This book was released on 2020-08-21 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: We shut down our schools, sports, theaters, bars, restaurants, and churches—government ignored the rule of law and put individual rights on hold—but it is more than obvious now that this was all a huge distraction. The focus should have been on the aged with underlying conditions living in nursing homes. The models nowhere included what ended up being our reality, even though that reality was upon us as early as February when people in nursing homes began to die in Washington State. We should have seen it long before the lockdowns began. Now the modelers in the epidemiological profession need to learn what the economists figured out long ago: Human life is too complex to be accurately modeled, much less predicted. This book includes contributions from: Phillip W. Magness James L. Caton Jeffrey Tucker John Tamny Gregory van Kipnis Robert E. Wright George Gilder Peter C. Earle Edward P. Stringham Stephen C. Miller Fiona Harrigan Donald J. Boudreaux Ethan Yang David Hart The American Institute for Economic Research in Great Barrington, Massachusetts, was founded in 1933 as the first independent voice for sound economics in the United States. Today it publishes ongoing research, hosts educational programs, publishes books, sponsors interns and scholars, and is home to the world-renowned Bastiat Society and the highly respected Sound Money Project. The American Institute for Economic Research is a 501c3 public charity.
Author : Ahmad Taher Azar
Publisher : Springer Nature
ISBN 13 : 303072834X
Total Pages : 1115 pages
Book Rating : 4.0/5 (37 download)
Download or read book Modeling, Control and Drug Development for COVID-19 Outbreak Prevention written by Ahmad Taher Azar and published by Springer Nature. This book was released on 2021-11-01 with total page 1115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is well-structured book which consists of 31 full chapters. The book chapters' deal with the recent research problems in the areas of modeling, control and drug development, and it presents various techniques of COVID-19 outbreak prevention modeling. The book also concentrates on computational simulations that may help speed up the development of drugs to counter the novel coronavirus responsible for COVID-19. This is an open access book.
Author : Siddhartha Bhattacharyya
Publisher : CRC Press
ISBN 13 : 1000474704
Total Pages : 232 pages
Book Rating : 4.0/5 (4 download)
Download or read book Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data written by Siddhartha Bhattacharyya and published by CRC Press. This book was released on 2021-11-22 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Utku Kose
Publisher : Academic Press
ISBN 13 : 0128245379
Total Pages : 754 pages
Book Rating : 4.1/5 (282 download)
Download or read book Data Science for COVID-19 Volume 1 written by Utku Kose and published by Academic Press. This book was released on 2021-05-20 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : DM Basavarajaiah
Publisher : CRC Press
ISBN 13 : 1000593215
Total Pages : 458 pages
Book Rating : 4.0/5 (5 download)
Download or read book COVID Transmission Modeling written by DM Basavarajaiah and published by CRC Press. This book was released on 2022-06-28 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: COVID Transmission Modeling: An Insight into Infectious Diseases Mechanism provides an interdisciplinary overview of the COVID-19 pandemic crisis and covers various aspects of newer modeling techniques and practical solutions for health emergencies. This book aims to formulate various innovative and pragmatic mathematical, statistical, and epidemiological models using COVID-19 real data sets. It emphasizes interdisciplinary theoretical postulates derived from practical insights and knowledge of public health. Each of the book’s 12 chapters provides invaluable and exploratory tools to enable explicit assumptions, highlights key health indicators, and determines the geometric progression and control measures of the disease. The present developed models will allow readers to extrapolate the exact reason for the outbreak and pave the way for scientific information on vaccine trials and socioeconomic, psychological, and disease burden worldwide. These advanced techniques of modeling and their applications are in greater need than ever for effective connection between mathematicians, statisticians, epidemiologists, researchers, clinicians, and policymakers for making appropriate decisions at the right time. With the advent of emerging health science, all models are demonstrated with real-life data sets and provided with illustrations and eye-catching graphs and diagrams so that the readers can easily understand the concept of COVID-19 pandemic interventions and their control measures, and their impact. Features Addresses all aspects of mitigation/control measures, estimation of transmission rate, economic impact assessment, genetic complexity of COVID-19, herd immunity, and various methods, including newer mathematical, statistical, and epidemiological models in the analysis of COVID-19 pandemic outbreak Covers the application of innovative, advanced statistical and epidemiological models and demonstrates possible solutions toward supportive treatment aspects of COVID-19 and its control measures Includes models that can easily be followed in formulating the mathematical derivations and key points Supplemented with ample illustrations, images, diagrams, and figures This book is aimed at postgraduate students studying medicine and healthcare, mathematics, and statistical information. Researchers will also find this book very helpful.
Author : Rupa Mahanti
Publisher : CRC Press
ISBN 13 : 1000574431
Total Pages : 218 pages
Book Rating : 4.0/5 (5 download)
Download or read book How Data Can Manage Global Health Pandemics written by Rupa Mahanti and published by CRC Press. This book was released on 2022-05-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book bridges the fields of health care and data to clarify how to use data to manage pandemics. Written while COVID-19 was raging, it identifies both effective practices and misfires, and is grounded in clear, research-based explanations of pandemics and data strategy....The author has written an essential book for students and professionals in both health care and data. While serving the needs of academics and experts, the book is accessible for the general reader." – Eileen Forrester, CEO of Forrester Leadership Group, Author of CMMI for Services, Guidelines for Superior Service "...Rupa Mahanti explores the connections between data and the human response to the spread of disease in her new book,... She recognizes the value of data and the kind of insight it can bring, while at the same time recognizing that using data to solve problems requires not just technology, but also leadership and courage. This is a book for people who want to better understand the role of data and people in solving human problems." -- Laura Sebastian-Coleman, Author of Meeting the Challenges of Data Quality Management In contrast to the 1918 Spanish flu pandemic which occurred in a non-digital age, the timing of the COVID-19 pandemic intersects with the digital age, characterized by the collection of large amounts of data and sophisticated technologies. Data and technology are being used to combat this digital age pandemic in ways that were not possible in the pre-digital age. Given the adverse impacts of pandemics in general and the COVID-19 pandemic in particular, it is imperative that people understand the meaning, origin of pandemics, related terms, trajectory of a new disease, butterfly effect of contagious diseases, factors governing the pandemic potential of a disease, strategies to combat a pandemic, role of data, data sharing, data strategy, data governance, analytics, and data visualization in managing pandemics, pandemic myths, critical success factors in managing pandemics, and lessons learned. How Data Can Manage Global Health Pandemics: Analyzing and Understanding COVID-19 discusses these elements with special reference to COVID-19. Dr. Rupa Mahanti is a business and data consultant and has expertise in different data management disciplines, business process improvement, regulatory reporting, quality management, and more. She is the author of Data Quality (ASQ Quality Press) and the series Data Governance: The Way Forward (Springer).
Author : Mamata Mohapatra
Publisher : Springer Nature
ISBN 13 : 9811643725
Total Pages : 212 pages
Book Rating : 4.8/5 (116 download)
Download or read book COVID-19 Pandemic written by Mamata Mohapatra and published by Springer Nature. This book was released on 2022-01-06 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of recent novel coronavirus (SARS-CoV-2) infection and discusses developments in the field of nanoparticle/inorganic/organic materials development for antiviral application, therapeutic applications, PPE kit formulations and inclusion of simulated data. The contents focus on measures to keep the infections in check, materials aspects for detection and monitoring, AI modeling for prediction of spread of the virus, among others. This book will be a useful reference for researchers, scientists and policy makers alike.
Author : Subhendu Kumar Pani
Publisher : Springer Nature
ISBN 13 : 3030797538
Total Pages : 416 pages
Book Rating : 4.0/5 (37 download)
Download or read book Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis written by Subhendu Kumar Pani and published by Springer Nature. This book was released on 2021-12-13 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively covers the topic of COVID-19 and other pandemics and epidemics data analytics using computational modelling. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. The new era of pandemics and epidemics bring tremendous opportunities and challenges due to the plentiful and easily available medical data allowing for further analysis. The aim of pandemics and epidemics research is to ensure high-quality, efficient healthcare, better treatment and quality of life by efficiently analyzing the abundant medical, and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. In the past, it was a common requirement to have domain experts for developing models for biomedical or healthcare. However, recent advances in representation learning algorithms allow us to automatically learn the pattern and representation of the given data for the development of such models. Medical Image Mining, a novel research area (due to its large amount of medical images) are increasingly generated and stored digitally. These images are mainly in the form of: computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions related to health care. Image mining in medicine can help to uncover new relationships between data and reveal new and useful information that can be helpful for scientists and biomedical practitioners. Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis will play a vital role in improving human life in response to pandemics and epidemics. The state-of-the-art approaches for data mining-based medical and health related applications will be of great value to researchers and practitioners working in biomedical, health informatics, and artificial intelligence..
Author : Utku Kose
Publisher : Academic Press
ISBN 13 : 0323907709
Total Pages : 812 pages
Book Rating : 4.3/5 (239 download)
Download or read book Data Science for COVID-19 written by Utku Kose and published by Academic Press. This book was released on 2021-10-22 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : Joao Alexandre Lobo Marques
Publisher : Springer Nature
ISBN 13 : 3030619133
Total Pages : 103 pages
Book Rating : 4.0/5 (36 download)
Download or read book Predictive Models for Decision Support in the COVID-19 Crisis written by Joao Alexandre Lobo Marques and published by Springer Nature. This book was released on 2020-11-30 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.
Author : Nicola Bellomo
Publisher : Springer Nature
ISBN 13 : 3030965627
Total Pages : 314 pages
Book Rating : 4.0/5 (39 download)
Download or read book Predicting Pandemics in a Globally Connected World, Volume 1 written by Nicola Bellomo and published by Springer Nature. This book was released on 2022-09-22 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume investigates several mathematical techniques for the modeling and simulation of viral pandemics, with a special focus on COVID-19. Modeling a pandemic requires an interdisciplinary approach with other fields such as epidemiology, virology, immunology, and biology in general. Spatial dynamics and interactions are also important features to be considered, and a multiscale framework is needed at the level of individuals and the level of virus particles and the immune system. Chapters in this volume address these items, as well as offer perspectives for the future.
Author : Till D. Frank
Publisher : Springer Nature
ISBN 13 : 3030971783
Total Pages : 367 pages
Book Rating : 4.0/5 (39 download)
Download or read book COVID-19 Epidemiology and Virus Dynamics written by Till D. Frank and published by Springer Nature. This book was released on 2022-03-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the COVID-19 pandemic from a quantitative perspective based on mathematical models and methods largely used in nonlinear physics. It aims to study COVID-19 epidemics in countries and SARS-CoV-2 infections in individuals from the nonlinear physics perspective and to model explicitly COVID-19 data observed in countries and virus load data observed in COVID-19 patients. The first part of this book provides a short technical introduction into amplitude spaces given by eigenvalues, eigenvectors, and amplitudes.In the second part of the book, mathematical models of epidemiology are introduced such as the SIR and SEIR models and applied to describe COVID-19 epidemics in various countries around the world. In the third part of the book, virus dynamics models are considered and applied to infections in COVID-19 patients. This book is written for researchers, modellers, and graduate students in physics and medicine, epidemiology and virology, biology, applied mathematics, and computer sciences. This book identifies the relevant mechanisms behind past COVID-19 outbreaks and in doing so can help efforts to stop future COVID-19 outbreaks and other epidemic outbreaks. Likewise, this book points out the physics underlying SARS-CoV-2 infections in patients and in doing so supports a physics perspective to address human immune reactions to SARS-CoV-2 infections and similar virus infections.
Author : Esteban A. Hernandez-Vargas
Publisher : Elsevier
ISBN 13 : 0323950655
Total Pages : 352 pages
Book Rating : 4.3/5 (239 download)
Download or read book Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases written by Esteban A. Hernandez-Vargas and published by Elsevier. This book was released on 2023-03-21 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modeling, Simulations, and Artificial Intelligence for Emergent Pandemic Diseases: Lessons Learned from COVID-19 includes new research, models and simulations developed during the COVID-19 pandemic into how mathematical methods and practice can impact future response. Chapters go beyond forecasting COVID-19, bringing different scale angles and mathematical techniques (e.g., ordinary differential and difference equations, agent-based models, artificial intelligence, and complex networks) which could have potential use in modeling other emergent pandemic diseases. A major part of the book focuses on preparing the scientific community for the next pandemic, particularly the application of mathematical modeling in ecology, economics and epidemiology. Readers will benefit from learning how to apply advanced mathematical modeling to a variety of topics of practical interest, including optimal allocations of masks and vaccines but also more theoretical problems such as the evolution of viral variants. Provides a comprehensive overview of the state-of-the-art in mathematical modeling and computational simulations for emerging pandemics Presents modeling techniques that go beyond COVID-19, and that can be applied to tailoring interventions to attenuate high death tolls Includes illustrations, tables and dialog boxes to explain highly specialized concepts and insights with complex algorithms, along with links to programming code
