By Ding-Geng (Din) Chen, Samuel O. M. Manda, Tobias F. Chirwa

This book provides an overview of the emerging topics in biostatistical theories and methods through their applications to evidence-based global health research and decision-making. It brings together some of the top scholars engaged in biostatistical method development on global health to highlight and describe recent advances in evidence-based global health applications. The volume is composed of five main parts: data harmonization and analysis; systematic review and statistical meta-analysis; spatial-temporal modeling and disease mapping; Bayesian statistical modeling; and statistical methods for longitudinal data or survival data.

It is designed to be illuminating and valuable to both expert biostatisticians and to health researchers engaged in methodological applications in evidence-based global health research. It is particularly relevant to countries where global health research is being rigorously conducted.

This book is an essential resource for any researcher or practitioner interested in biostatistical theories and their application in evidence-based global health research. The authors, Ding-Geng (Din) Chen, Samuel O. M. Manda, and Tobias F. Chirwa, are leading experts in the field and have compiled a comprehensive collection of the latest advancements in biostatistical methods.

The book is divided into five main parts, each covering a different aspect of biostatistical theories and methods. The first part focuses on data harmonization and analysis, providing insights into how to effectively collect, manage, and analyze data for global health research. The second part delves into systematic review and statistical meta-analysis, which are essential tools for synthesizing and summarizing evidence from multiple studies. The third part explores spatial-temporal modeling and disease mapping, demonstrating how to identify and analyze spatial and temporal patterns in disease data. The fourth part introduces Bayesian statistical modeling, offering a powerful alternative to traditional frequentist methods. Finally, the fifth part discusses statistical methods for longitudinal data or survival data, providing techniques for analyzing data collected over a period of time or data related to survival outcomes.

One of the key strengths of this book is its emphasis on evidence-based global health research and its practical application. The authors not only present the theoretical underpinnings of biostatistical methods but also provide real-world examples and case studies to illustrate how these methods can be applied in practice. This makes the book accessible and relevant to researchers and practitioners at all levels of expertise.

The book also addresses the specific challenges and considerations of global health research, particularly in countries where resources may be limited. The authors provide guidance on how to overcome common challenges and make the most of available data and resources, ensuring that the research conducted is rigorous and reliable. This aspect of the book is particularly valuable for researchers working in low- and middle-income countries, where global health research is of utmost importance.

In addition to its practical value, the book is also a valuable resource for advancing biostatistical theories and methods. The authors present cutting-edge research and introduce new approaches that have the potential to shape the future of biostatistics. By highlighting recent advances and discussing their implications, the book serves as a catalyst for further research and innovation in the field.

The book is well-structured and organized, making it easy to navigate and comprehend. Each chapter begins with an introduction and overview of the topic, followed by a detailed discussion of the underlying concepts and methods. The authors use clear and concise language, making complex statistical concepts accessible to readers with varying levels of statistical expertise. The inclusion of practical examples and case studies further enhances understanding and facilitates application.

In conclusion, “Emerging Topics in Biostatistical Theories and Methods for Evidence-Based Global Health Research” is a comprehensive and insightful resource for anyone interested in biostatistical theories and their application in global health research. It provides a thorough overview of the latest advancements in the field and offers practical guidance on how to apply these methods in real-world settings. Whether you are a seasoned biostatistician, a health researcher, or a student, this book is a valuable addition to your library.

Order your copy today and take your biostatistical research to the next level!