Computational Modeling and Data Analysis in COVID-19 Research


Book Description

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 Static and Dynamic Continuum Theory of Liquid Crystals


Book Description

Given the widespread interest in macroscopic phenomena in liquid crystals, stemming from their applications in displays and devices. The need has arisen for a rigorous yet accessible text suitable for graduate students, whatever their scientific background. This book satisfies that need. The approach taken in this text, is to introduce the basic continuum theory for nematic liquid crystals in equilibria, then it proceeds to simple application of this theory- in particular, there is a discussion of electrical and magnetic field effects which give rise to Freedericksz transitions, which are important in devices. This is followed by an account of dynamic theory and elementary viscometry of nemantics Discussions of backflow and flow-induced instabilities are also included. Smetic theory is also briefly introduced and summarised with some examples of equilibrium solutions as well as those with dynamic effects. A number of mathematical techniques, such as Cartesian tensors and some variational calculus, are presented in the appendices.




Applied Mathematical Ecology


Book Description

The Second Autumn Course on Mathematical Ecology was held at the Intern ational Centre for Theoretical Physics in Trieste, Italy in November and December of 1986. During the four year period that had elapsed since the First Autumn Course on Mathematical Ecology, sufficient progress had been made in applied mathemat ical ecology to merit tilting the balance maintained between theoretical aspects and applications in the 1982 Course toward applications. The course format, while similar to that of the first Autumn Course on Mathematical Ecology, consequently focused upon applications of mathematical ecology. Current areas of application are almost as diverse as the spectrum covered by ecology. The topiys of this book reflect this diversity and were chosen because of perceived interest and utility to developing countries. Topical lectures began with foundational material mostly derived from Math ematical Ecology: An Introduction (a compilation of the lectures of the 1982 course published by Springer-Verlag in this series, Volume 17) and, when possible, progressed to the frontiers of research. In addition to the course lectures, workshops were arranged for small groups to supplement and enhance the learning experience. Other perspectives were provided through presentations by course participants and speakers at the associated Research Conference. Many of the research papers are in a companion volume, Mathematical Ecology: Proceedings Trieste 1986, published by World Scientific Press in 1988. This book is structured primarily by application area. Part II provides an introduction to mathematical and statistical applications in resource management.




Computational Epidemiology


Book Description

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.




Mathematical Epidemiology


Book Description

Based on lecture notes of two summer schools with a mixed audience from mathematical sciences, epidemiology and public health, this volume offers a comprehensive introduction to basic ideas and techniques in modeling infectious diseases, for the comparison of strategies to plan for an anticipated epidemic or pandemic, and to deal with a disease outbreak in real time. It covers detailed case studies for diseases including pandemic influenza, West Nile virus, and childhood diseases. Models for other diseases including Severe Acute Respiratory Syndrome, fox rabies, and sexually transmitted infections are included as applications. Its chapters are coherent and complementary independent units. In order to accustom students to look at the current literature and to experience different perspectives, no attempt has been made to achieve united writing style or unified notation. Notes on some mathematical background (calculus, matrix algebra, differential equations, and probability) have been prepared and may be downloaded at the web site of the Centre for Disease Modeling (www.cdm.yorku.ca).




Handbook of Research on Pathophysiology and Strategies for the Management of COVID-19


Book Description

According to the World Health Organization (WHO), coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus (SARS-Cov2), which may cause mild to moderate respiratory complications in most infected people. Older people and those with chronic and/or acute illnesses may present serious complications. Underlying mechanisms of the cellular responses to the virus are not fully revealed; therefore, understanding the pathophysiology of COVID-19 is crucial to provide efficient data to define the appropriate and effective therapeutic strategies to cure and prevent COVID-19-associated complications. The Handbook of Research on Pathophysiology and Strategies for the Management of COVID-19 summarizes and assembles the published data on COVID-19 and provides an answer to the reader for the mystery of SARS-Cov2’s impact on human health through a deep analysis of the current data available in the literature. This book addresses the epidemiology and infectious patterns of the disease and the recent pathophysiological mechanisms of the disease and relationships to the medical history of the patient. Covering topics from the tie between COVID-19 and respiratory disease to vaccination information, this comprehensive reference source is ideal for clinicians, health professionals, pathologists, virologists, researchers, academicians, and medical and PhD students.




The Stability of Dynamical Systems


Book Description

An introduction to aspects of the theory of dynamial systems based on extensions of Liapunov's direct method. The main ideas and structure for the theory are presented for difference equations and for the analogous theory for ordinary differential equations and retarded functional differential equations. The latest results on invariance properties for non-autonomous time-varying systems processes are presented for difference and differential equations.




Toward a Containment Strategy for Smallpox Bioterror


Book Description

In the United States, routine smallpox vaccination ended in 1972. The level of immunity remaining in the U.S. population is uncertain, but is generally assumed to be quite low. Smallpox is a deadly and infectious pathogen with a fatality rate of 30 percent. If smallpox were successfully deployed as an agent of bioterrorism today, the public health and economic consequences could be devastating. Toward a Containment Strategy for Smallpox Bioterror describes the scientific results and policy implications of a simulation of a smallpox epidemic in a two-town county. The model was developed by an interdisicplinary team from the Johns Hopkins Bloomberg School of Public Health and the Brookings Institution Center on Social and Economic Dynamics, employing agent-based and other advanced computational techniques. Such models are playing a critical role in the crafting of a national strategy for the containment of smallpox by providing public health policymakers with a variety of novel and feasible approaches to vaccination and isolation under different circumstances. The extension of these techniques to the containment of emerging pathogens, such as SARS, is discussed. About the Authors Joshua M. Epstein and Shubha Chakravarty are with the Brookings Institution. Derek A. T. Cummings, Ramesh M. Singha, and Donald S. Burke are with the Johns Hopkins Bloomberg School of Public Health.




The Rules of Contagion


Book Description

An Observer Book of the Year A Times Science Book of the Year A New Statesman Book of the Year A Financial Times Science Book of the Year 'Astonishingly bold' Daily Mail 'It is hard to imagine a more timely book ... much of the modern world will make more sense having read it.' The Times We live in a world that's more interconnected than ever before. Our lives are shaped by outbreaks - of disease, of misinformation, even of violence - that appear, spread and fade away with bewildering speed. To understand them, we need to learn the hidden laws that govern them. From 'superspreaders' who might spark a pandemic or bring down a financial system to the social dynamics that make loneliness catch on, The Rules of Contagion offers compelling insights into human behaviour and explains how we can get better at predicting what happens next. Along the way, Adam Kucharski explores how innovations spread through friendship networks, what links computer viruses with folk stories - and why the most useful predictions aren't necessarily the ones that come true. Now revised and updated with content on Covid-19.