This handbook compiles methods for gathering, organizing and disseminating data to inform policy and manage health systems worldwide. Contributing authors describe national and international structures for generating data and explain the relevance of ethics, policy, epidemiology, health economics, demography, statistics, geography and qualitative methods to describing population health. The reader, whether a student of global health, public health practitioner, programme manager, data analyst or policymaker, will appreciate the methods, context and importance of collecting and using global health data.
The current book, Global Health Security - Contemporary Considerations and Developments, represents a collective work of multiple authors from around the world, with an ultimate goal of providing the reader with a comprehensive exploration of critical issues shaping modern global health security, especially in the post-COVID-19 reality of today. It not only highlights the latest trends, challenges, and advancements shaping the field but also delves into unique topics like the impact of geopolitical tensions and barriers, funding gaps, intentional and unintentional misuse of social media platforms, medical and health misinformation, and the need for greater equity and inclusivity. Moreover, the book outlines potential future directions for strengthening global health security, including the enhancement of multisectoral collaboration, investment in research and development, and promotion of health equity. These are critical measures that can help address the current challenges facing our planet following the most devastating pandemic in over a century. This collection of expert manuscripts provides valuable insights and practical recommendations that can help inform policy decisions and guide future research and development efforts. We hope that the reader will find this book to be an essential resource, especially for those looking to gain a deeper understanding of the issues surrounding global health security.
Since the emergence of contemporary area classifications, population geography has witnessed a renaissance in the area of policy related spatial analysis. Area classifications subsume geodemographic systems which often use data mining techniques and machine learning algorithms to simplify large and complex bodies of information about people and the places in which they live, work and undertake other social activities. Outputs developed from the grouping of small geographical areas on the basis of multi- dimensional data have proved beneficial particularly for decision-making in the commercial sectors of a vast number of countries in the northern hemisphere. This book argues that small area classifications offer countries in the Global South a distinct opportunity to address human population policy related challenges in novel ways using area-based initiatives and evidence-based methods. This book exposes researchers, practitioners, and students to small area segmentation techniques for understanding, interpreting, and visualizing the configuration, dynamics, and correlates of development policy challenges at small spatial scales. It presents strategic and operational responses to these challenges in cost effective ways. Using two developing countries as case studies, the book connects new transdisciplinary ways of thinking about social and spatial inequalities from a scientific perspective with GIS and Data Science. This offers all stakeholders a framework for engaging in practical dialogue on development policy within urban and rural settings, based on real-world examples. Features: The first book to address the huge potential of small area segmentation for sustainable development, combining explanations of concepts, a range of techniques, and current applications. Includes case studies focused on core challenges that confront developing countries and provides thorough analytical appraisal of issues that resonate with audiences from the Global South. Combines GIS and machine learning methods for studying interrelated disciplines such as Demography, Urban Science, Sociology, Statistics, Sustainable Development and Public Policy. Uses a multi-method approach and analytical techniques of primary and secondary data. Embraces a balanced, chronological, and well sequenced presentation of information, which is very practical for readers.
This handbook is an essential resource which brings into focus key advances, challenges and lessons learned in strengthening human resources for health (HRH) data and evidence as a strategic objective of implementing the Global Strategy on Human Resources for Health: Workforce 2030, the recommendations of the United Nations Secretary-General High-level Commission on Health Employment and Economic Growth, and in the achievement of the WHO Thirteenth General Programme of Work (2019–2023 (GPW 13) targets, for a measurable impact on population health and development. Divided into three parts, the handbook presents the complementarity between WHO Health Labour Market Analysis Guidebook and WHO handbook on national health workforce accounts (NHWA) system strengthening approach to improving the availability, quality, analysis, dissemination and use of health workforce data and evidence to inform decision-making and planning in countries. It also features the committed country efforts, catalysed by networks and partner investments, in strengthening HRH information systems and their growing success in implementing NHWA and other WHO normative tools. Contributed by the six technical working groups of the Global Health Workforce Network (GHWN) Data and Evidence hub, the handbook is aimed at HRH policy-makers and planners, to provide contemporary insight on data sources and information needs to address policy questions around health workforce development, and as part of the broader intersectoral agenda to strengthening health systems resilience.
This book presents volume 1 of selected research papers presented at the third International Conference on Digital Technologies and Applications (ICDTA 23). This book highlights the latest innovations in digital technologies as: artificial intelligence, Internet of things, embedded systems, network technology, digital transformation and their applications in several areas as Industry 4.0, renewable energy, mechatronics, digital healthcare. The respective papers encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.
GeoComputation and Public Health is fundamentally a multi-disciplinary book, which presents an overview and case studies to exemplify numerous methods and solicitations in addressing vectors borne diseases (e.g, Visceral leishmaniasis, Malaria, Filaria). This book includes a practical coverage of the use of spatial analysis techniques in vector-borne disease using open source software solutions. Environmental factors (relief characters, climatology, ecology, vegetation, water bodies etc.) and socio-economic issues (housing type & pattern, education level, economic status, income level, domestics’ animals, census data, etc) are investigated at micro -level and large scale in addressing the various vector-borne disease. This book will also generate a framework for interdisciplinary discussion, latest innovations, and discoveries on public health. The first section of the book highlights the basic and principal aspects of advanced computational practices. Other sections of the book contain geo-simulation, agent-based modeling, spatio-temporal analysis, geospatial data mining, various geocomputational applications, accuracy and uncertainty of geospatial models, applications in environmental, ecological, and biological modeling and analysis in public health research. This book will be useful to the postgraduate students of geography, remote sensing, ecology, environmental sciences and research scholars, along with health professionals looking to solve grand challenges and management on public health.
The book provides a multidisciplinary outlook on using Artificial Intelligence (AI)-based solutions in the field of Personalized Medicine and its transitioning towards Personalized Digital Medicine. The first section integrates different perspectives on AI-based solutions and highlights their potential in biomedical research and patient care. In the second section, the authors present several real-world examples that demonstrate the successful use of AI technologies in various contexts. These include examples from digital therapeutics, in silico clinical trials, and network pharmacology. In the final section of the book, the authors explore future directions in AI-enhanced biomedical technologies and discuss emerging technologies such as blockchain, quantum computing and the “metaverse”. The book includes discussions on the ethical, regulatory, and social implications for an AI-based personalized medicine. The integration of heterogeneous disciplines brings together multiple stakeholders and decision makers involved in the personalization of care. Clinicians, students, and researchers from academia and the industry can benefit from this book, since it provides foundational knowledge to drive advances in personalized biomedical research and health care.
