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Geographic information, spatial analysis and geospatial technologies play an important role in understanding changes in planetary health and in defining the drivers contributing to different health outcomes both locally and globally. Patterns influencing health outcomes and disease in the environment are complex and require an understanding of the ecology of the disease and how these interact in space and time. Knowing where and when diseases are prevalent, who is affected and what may be driving these outcomes is important for determining how to respond. In reality, we all would like to be healthy and live in healthy places. In this book, epidemiology and public health are integrated with spatial data science to examine health issues in dynamically changing environments. This is too broad a field to be completely covered in one book, and so, it has been necessary to be selective with the topics, methods and examples used to avoid overwhelming introductory readers while at the same time providing sufficient depth for geospatial experts interested in health and for health professionals interested in integrating geospatial elements for health analysis. A variety of geographic information (some novel, some volunteered, some authoritative, some big and messy) is used with a mix of methods consisting of spatial analysis, data science and spatial statistics to better understand health risks and disease outcomes. Key Features: Makes spatial data science accessible to health Integrates epidemiology and disease ecology with spatial data science Integrates theoretical geographic information science concepts Provides practical and applied approaches for examining and exploring health and disease risks Provides spatial data science skill development ranging from map making to spatial modelling
The book introduces a variety of latest techniques designed to represent, enhance, and empower multi-disciplinary approaches of geographic information system (GIS), artificial intelligence (AI), deep learning (DL), machine learning, and cloud computing research in healthcare. It provides a unique compendium of the current and emerging use of geospatial data for healthcare and reflects the diversity, complexity, and depth and breadth of this multi-disciplinary area. This book addresses various aspects of how smart healthcare devices can be used to detect and analyze diseases. Further, it describes various tools and techniques to evaluate the efficacy, suitability, and efficiency of geospatial data for health-related applications. It features illustrative case studies, including future applications and healthcare challenges. This book is beneficial for computer science and engineering students and researchers, medical professionals, and anyone interested in using geospatial data in healthcare. It is also intended for experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious to learn about this important subject. The book presents an effort to draw how we can build health-related applications using geospatial big data and their subsequent analysis.
This book focuses on a range of geospatial applications for environmental health research, including environmental justice issues, environmental health disparities, air and water contamination, and infectious diseases. Environmental health research is at an exciting point in its use of geotechnologies, and many researchers are working on innovative approaches. This book is a timely scholarly contribution in updating the key concepts and applications of using GIS and other geospatial methods for environmental health research. Each chapter contains original research which utilizes a geotechnical tool (Geographic Information Systems (GIS), remote sensing, GPS, etc.) to address an environmental health problem. The book is divided into three sections organized around the following themes: issues in GIS and environmental health research; using GIS to assess environmental health impacts; and geospatial methods for environmental health. Representing diverse case studies and geospatial methods, the book is likely to be of interest to researchers, practitioners and students across the geographic and environmental health sciences. The authors are leading researchers and practitioners in the field of GIS and environmental health.
Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used by popular companies such as UberA hands-on guide to help you consume spatial data and parallelize GIS operations effectivelyBook Description Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses. This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more. By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease. What you will learnLearn how companies now use location dataSet up your Python environment and install Python geospatial packagesVisualize spatial data as graphsExtract geometry from spatial dataPerform spatial regression from scratchBuild web applications which dynamically references geospatial dataWho this book is for Data Scientists who would like to leverage location-based data and want to use location-based intelligence in their data models will find this book useful. This book is also for GIS developers who wish to incorporate data analysis in their projects. Knowledge of Python programming and some basic understanding of data analysis are all you need to get the most out of this book.
Over the last thirty years or so, there have been tremendous advancements in the area of geospatial health; however, somehow, two aspects have not received as much attention as they should have received. These are a) limitations of different spatial analytical tools and b) progress in making geospatial environmental exposure data available for advanced health science research and for medical practice. This edited volume addresses those two less explored areas of geospatial health with augmented discussions on the theories, methodologies and limitations of contemporary geospatial technologies in a wide range of applications related to human well-being and health. In 20 chapters, readers are presented with an up-to-date assessment of geospatial technologies with an emphasis on understanding general geospatial principles and methodologies that are often overlooked in the research literature. As a result, this book will be of interest to both newcomers and experts in geospatial analysis and will appeal to students and researchers engaged in studying human well-being and health. Chapters are presenting new concepts, new analytical methods and contemporary applications within the framework of geospatial applications in human well-being and health. The topics addressed by the various chapter authors include analytical approaches, newer areas of geospatial health application, introduction to unique resources, geospatial modeling, and environmental pollution assessments for air, water and soil. Although geospatial experts are expected to be the primary readers, this book is designed in such a way so that the public health professionals, environmental health scientists and clinicians also find it useful with or without any familiarity with geospatial analysis.
The neighborhoods and the biophysical, political, and cultural environments all play a key role in affecting health outcomes of individuals. Unequal spatial distribution of resources such as clinics, hospitals, public transportation, fresh food markets, and schools could make some communities as a whole more vulnerable and less resilient to adverse health effects. This somber reality suggests that it is rather the question of "who you are depends upon where you are" and the fact that health inequality is both a people and a place concern. That is why health inequality needs to be investigated in a spatial setting to deepen our understanding of why and how some geographical areas experience poorer health than others. This book introduces how spatial context shapes health inequalities. Spatial Health Inequalities: Adapting GIS Tools and Data Analysis demonstrates the spatial health inequalities in six most important topics in environmental and public health, including food insecurity, birth health outcomes, infectious diseases, children’s lead poisoning, chronic diseases, and health care access. These are the topics that the author has done extensive research on and provides a detailed description of the topic from a global perspective. Each chapter identifies relevant data and data sources, discusses key literature on appropriate techniques, and then illustrates with real data with mapping and GIS techniques. This is a unique book for students, geographers, clinicians, health and research professionals and community members interested in applying GIS and spatial analysis to the study of health inequalities.
This book presents a comprehensive state-of the-art approach to digital health technologies and practices within the broad confines of healthcare practices. It provides a canvas to discuss emerging digital health solutions, propelled by the ubiquitous availability of miniaturized, personalized devices and affordable, easy to use wearable sensors, and innovative technologies like 3D printing, virtual and augmented reality and driverless robots and vehicles including drones. One of the most significant promises the digital health solutions hold is to keep us healthier for longer, even with limited resources, while truly scaling the delivery of healthcare. Digital Health: Scaling Healthcare to the World addresses the emerging trends and enabling technologies contributing to technological advances in healthcare practice in the 21st Century. These areas include generic topics such as mobile health and telemedicine, as well as specific concepts such as social media for health, wearables and quantified-self trends. Also covered are the psychological models leveraged in design of solutions to persuade us to follow some recommended actions, then the design and educational facets of the proposed innovations, as well as ethics, privacy, security, and liability aspects influencing its acceptance. Furthermore, sections on economic aspects of the proposed innovations are included, analyzing the potential business models and entrepreneurship opportunities in the domain.
Adaptive Health Management Information Systems, Fourth Edition is a thorough resource for a broad range of healthcare professionals–from informaticians, physicians and nurses, to pharmacists, public health and allied health professionals–who need to keep pace the digital transformation of health care. Wholly revised, updated, and expanded in scope, the fourth edition covers the latest developments in the field of health management information systems (HMIS) including big data analytics and machine learning in health care; precision medicine; digital health commercialization; supply chain management; informatics for pharmacy and public health; digital health leadership; cybersecurity; and social media analytics.
Geographic Information Science and Technology (GISc&T) has been at the forefront of education innovation in geography and allied sciences for two decades. Teaching Geographic Information Science and Technology in Higher Education is an invaluable reference for educators and researchers working in GISc&T, providing coverage of the latest innovations in the field and discussion of what the future holds for GI Science education in the years to come. This book clearly documents teaching innovations and takes stock of lessons learned from experience in the discipline. The content will be of interest both to educators and researchers working in GISc&T, and to educators in other related fields. More importantly, this book also anticipates some of the opportunities and challenges in GI Science and Technology education that may arise in the next decade. As such it will be of interest to chairs, deans, administrators, faculty in other subfields, and educators in general. Innovative book taking a look at recent innovations and teaching developments in the course provision of GI Science and Technology in higher education. Edited by leaders in the field of GISc&T who have been at the forefront of education innovation in GI Science and allied science subjects. Provides coverage of GISc & Technology in a range of institutional settings from an international perspective at all levels of higher education. An invaluable text for all educators within the field of GISc&T and allied subjects with advice from experts in the field on best practice. Includes coverage and practical advice on curriculum design, teaching with GIS technology, distance and eLearning with global examples from leading academics in the field.
Dive into the dynamic world of Geographic Information Systems (GIS) and data science with our comprehensive book in which innovation and insights converge. This book presents a pioneering exploration at the intersection of GIS and data science, providing a comprehensive view of their symbiotic relationship and transformative potential. It encapsulates advanced methodologies, real-world applications, and interdisciplinary approaches that redefine how we perceive and utilize spatial data. Offering a gateway to cutting-edge research and practical insights, this book serves as a crucial resource for scholars, practitioners, and enthusiasts alike. It addresses pressing challenges across diverse domains, from environmental studies to public health and predictive analytics, demonstrating the paramount significance of integrating GIS with data science methodologies. It is an essential compass guiding readers toward a deeper understanding and application of these dynamic fields in today's data-driven world.