DESCRIPTION
Classical and Bayesian Statistical Approaches in Infectious Disease Data Analysis is a methodological monograph that tackles the specific statistical challenges posed by infectious disease data, such as under‑reporting, dependence over time, and heterogeneous transmission patterns.
It introduces and compares a range of classical (frequentist) and Bayesian techniques for modelling incidence, estimating key quantities like the reproduction number, and analysing surveillance and outbreak datasets, with an emphasis on how modelling choices affect scientific and public‑health conclusions.
The authors combine theoretical exposition with worked case studies and practical guidance, making the book suitable both for statisticians entering infectious‑disease epidemiology and for applied researchers looking to deepen their toolkit for real‑world data analysis.
ABOUT
