Economics And Mathematical Modeling In Health Related Research

The definition of a healthcare system evolves continuously, becoming broader and more complex with each rendering. Healthcare systems can consist of many different elements, including but not limited to: access to comprehensive medical care, health promotion, disease prevention, institutional framework, financing schemes, government responsibility over health, etc. In light of its broad classification of healthcare, this book focuses on a wide spectrum of health-related issues ranging from risk factors for disease to medical treatment and possible frameworks for healthcare systems. Aging populations, increasing costs of healthcare, advancing technology, and challenges created by the COVID-19 pandemic require an innovative conceptual and methodological framework. By combining the experience and effort of researchers from a variety of fields including mathematics, medicine and economics, this book offers an interdisciplinary approach to studying health-related issues. It contributes to the existing literature by integrating the perspective of treatment with the economic determinants of health care outcomes, such as population density, access to financial resources and institutional frameworks. It also provides new evidence regarding the pharmaceutical industry including innovation, international trade and company performance. Contributors are: Sayansk Da Silva, Joe Feinglass, Scott W. Hegerty, Joseph E. Hibdon, Jr, Arkadiusz Michał Kowalski, Małgorzata Stefania Lewandowska, Dawid Majcherek, Ewelina Nojszewska, Izabela Pruchnicka-Grabias, Agata Sielska and Julian Smółka.

This book analyses the development and use of mathematical models in public health research and policy. By introducing a life cycle metaphor, the author provides a unique perspective on how mathematical modelling techniques have increased our understanding of the governance of infectious risks in society.

The construction of mathematical models is an essential scientific activity. Mathematics is associated with developments in science and engineering, but more recently mathematical modelling has been used to investigate complex systems that arise in other fields. This book demonstrates the application of mathematics to research topics in ecology and environmental science, health and medicine, phylogenetics and neural networks, theoretical chemistry, economics and management.

This book analyses the development and use of mathematical models in public health research and policy. By introducing a life cycle metaphor, the author provides a unique perspective on how mathematical modelling techniques have increased our understanding of the governance of infectious risks in society.

A model is a simplified representation of a real-world situation used to help answer a specific question. This book provides a look into the world of modelling with the focus on modelling in healthcare.--[from preface]

Providing a comparison between context in Europe and the US, this volume investigates the digital transformation of health systems, comparing strategies for digital development while identifying both key innovations and future challenges. The book covers a wide spectrum of topics, from explaining the nature of individual innovations to an analysis of demand-side and supply-side barriers, including funding issues and technological access. It also explores where digitalization is already playing an important role, for example, in clinical trials and disease modeling. Concluding with guidance for policy recommendations, this important book will interest students, scholars, and practitioners across health and social care, medicine, and beyond.

This book provides an introduction to decision analytic cost-effectiveness modelling, giving the theoretical and practical knowledge required to design and implement analyses that meet the methodological standards of health technology assessment organisations. The book guides you through building a decision tree and Markov model and, importantly, shows how the results of cost-effectiveness analyses are interpreted. Given the complex nature of cost-effectiveness modelling and the often unfamiliar language that runs alongside it, we wanted to make this book as accessible as possible whilst still providing a comprehensive, in-depth, practical guide that reflects the state of the art – that includes the most recent developments in cost-effectiveness modelling. Although the nature of cost effectiveness modelling means that some parts are inevitably quite technical, across the 13 chapters we have broken down explanations of theory and methods into bite-sized pieces that you can work through at your own pace; we have provided explanations of terms and methods as we use them. Importantly, the exercises and online workbooks allow you to test your skills and understanding as you go along.

Mathematical Models is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The Theme on Mathematical Models discusses matters of great relevance to our world such as: Basic Principles of Mathematical Modeling; Mathematical Models in Water Sciences; Mathematical Models in Energy Sciences; Mathematical Models of Climate and Global Change; Infiltration and Ponding; Mathematical Models of Biology; Mathematical Models in Medicine and Public Health; Mathematical Models of Society and Development. These three volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.