Description

The repertoire of quantitative analytical techniques in disciplines such as ecology, decision science, and evolutionary biology has grown, in part enabled by the development and increased availability of computational resources. Integration of cutting-edge, quantitative tools into veterinary epidemiology that have been borrowed from such disciplines has offered opportunities to advance the study of disease dynamics in animal populations, to improve and guide decision-making related to disease prevention, control, or eradication. Furthermore, the need to explore new analytical methods for veterinary epidemiology has been driven by the increasing availability and complexity of animal disease data. The objective of this e-book is to contribute to current methods in epidemiology by 1) presenting and discussing novel analytical tools that help advance our understanding of epidemiology; and 2) demonstrating how inferences emerging from the application of novel analytical tools can be incorporated into decision-making related to animal health. The e-book constitutes a collection of articles that explore the applications of a variety of analytical methods such as machine learning, Bayesian risk assessment and an advanced form of social network analysis in the modern epidemiologic study of animal diseases.