Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how
the Bayesian approach can be used to analyze the evolutionary behavior
of infectious diseases, including the coronavirus pandemic. The book
describes the foundation of Bayesian statistics while explicating the
biology and evolutionary behavior of infectious diseases, including
viral and bacterial manifestations of the contagion. The book discusses
the application of Markov Chains to contagious diseases, previews data
analysis models, the epidemic threshold theorem, and basic properties of
the infection process. Also described are the chain binomial model for
the evolution of epidemics.
Features:
Represents the first book on infectious disease from a Bayesian
perspective.
Employs WinBUGS and R to generate observations that follow the course of
contagious maladies.
Includes discussion of the coronavirus pandemic as well as many examples
from the past, including the flu epidemic of 1918-1919.
Compares standard non-Bayesian and Bayesian inferences.
Offers the R and WinBUGS code on at www.routledge.com/9780367633868