Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulating and transforming point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fitting and interpreting spatial and spatio-temporal models with the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE) approaches, Creating interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policymakers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modelling, and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.
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.
Focussing on proven techniques for most real-world data sets, this book presents an overview of the analysis of health data involving a geographic component, in a way that is accessible to any health scientist or student comfortable with large data sets and basic statistics, but not necessarily with any specialized training in geographic information systems (GIS). Providing clear, straightforward explanations with worldwide examples and solutions, the book describes applications of GIS in disaster response.
This book is specifically designed to serve the community of postgraduates and researchers in the fields of epidemiology, health GIS, medical geography, and health management. It starts with the basic concepts and role of remote sensing, GIS in Kala-azar diseases. The book gives an exhaustive coverage of Satellite data, GPS, GIS, spatial and attribute data modeling, and geospatial analysis of Kala-azar diseases. It also presents the modern trends of remote sensing and GIS in health risk assessment with an illustrated discussion on its numerous applications.
Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets
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.
Homeland security and context In the Geographical Dimensions of Terrorism (GDOT) (Cutter et al. 2003), the first book after 9/11 to address homeland security and geography, we developed several thematic research agendas and explored intersections between geographic research and the importance of context, both geographical and political, in relationship to the concepts of terrorism and security. It is good to see that a great deal of new thought and research continues to flow from that initial research agenda, as illustrated by many of the papers of this new book, entitled Geospatial Technologies and Homeland Security: Research Frontiers and Future Challenges. Context is relevant not only to understanding homeland security issues broadly, but also to the conduct of research on geospatial technologies. It is impossible to understand the implications of a homeland security strategy, let alone hope to make predictions, conduct meaningful modeling and research, or assess the value and dangers of geospatial technologies, without consideration of overarching political, social, economic, and geographic contexts within which these questions are posed.
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 as they apply to human health science and analysis, with an emphasis on understanding general geospatial principles and methodologies that are often overlooked in other studies and resources. As a result, the 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, newer 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 main readers, this book is designed such a way so that the public health professions, environmental health scientists and clinicians also find it useful.