Applications of Information Theory to Epidemiology

In Applications of Information Theory to Epidemiology, author Gareth Hughes gathers together epidemiological applications of information theory and presents them in a manner that makes them accessible to plant disease epidemiologists and others in the field of plant pathology. He provides a summary of basic concepts, methods, and results that is not only understandable to newcomers to the topic but is also immediately useful and applicable for those using data for making diagnostic determinations.


This is the first book written on applications of information theory explicitly for plant disease epidemiology. Few if any plant disease epidemiologists have closely followed the epidemiological applications of information theory, in part because such applications have been devised almost exclusively by clinical epidemiologists. The author’s key methodologies related to diagnostic decision making as it relates to plant disease are drawn from his career work, which includes the epidemiology and modeling of diseases. Dr. Hughes has been honored for his work using real-world disease problems in fruit crops as model systems for the development of methodologies for basic research in epidemiology and plant disease losses. The breakthrough results of these basic studies have provided new and innovative approaches for managing diseases and have made a substantial impact on our knowledge in this area of science.


Applications of Information Theory to Epidemiology uses original clinical epidemiology examples, as well as phytopathological applications, to illustrate theory, citing a wide range of literature. Doing so permits the examples in the book to be used by many diverse groups of scientists. This book is ideally suited for plant pathologists and others with an interest in the quantitative basis for diagnostic decision making. Epidemiologists (botanical, clinical, and veterinary) will find it useful, as well. Those who have enjoyed Larry Madden’s The Study of Plant Disease Epidemics will welcome this title as a continuation of the applied knowledge in this area. 


Applications of Information Theory to Epidemiology includes a helpful glossary of terms for those new to the nomenclature.