Statistical Aspects of BSE and vCJD: Models for Epidemics
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Summary
Bovine Spongiform Encephalopathy (BSE) or "mad cow disease," first diagnosed in late 1986, is transmitted through feed, indirect horizontal transmission, apparently maternally and possibly horizontally, through cattle-to-cattle contact or a contaminated environment. With no ante-mortem test yet developed, the only information available about BSE is from case surveillance and a limited number of experiments. Only through careful and rigorous modeling and analysis can reliable estimates of past infection and predictions of future cases be made. The modeling developed for BSE utilizes a range of techniques from statistics, ecology, and demography that is of interest both as a case study and for providing tools for other modeling projects. Statistical Aspects of BSE and vCJD: Models for Epidemics presents the general methodology required for thorough analysis and modeling of novel long incubation diseases with largely unknown etiology. BSE in British cattle is the primary example system presented, but application to other diseases, particularly the transmissible spongiform encephalopathies (e.g., Scrapie in sheep and nvCJD in humans) are also highlighted. The book concentrates on presenting an exposition of the "state-of-the-art" rather than introductory material on the mathematical/statistical modeling of infectious diseases.
Table of Contents
INTRODUCTION
Background and Aims
Overview of the Book
BSE AND vCJD
Transmissible Spongiform Encephalopathies
Transmission Routes
Incubation Period Distributions
The Genetics of TSEs
The Nature of the Aetiological Agent of BSE
Conclusion
SOURCES OF DATA
Introduction
BSE Case Databases
Demography of British Cattle
The Maternal Cohort Study
Data on Confirmed vCJD Cases
POPULATION MODELS: FORMULATION
Introduction
The Simple Epidemic Process
Introducing Demography
Age-Dependent Susceptibility/Exposure
The Inclusion of Different Transmission Routes
R0 for Systems with Multiple Transmission Routes
Solving the Model
Heterogeneity in Susceptibility
Incidence of Disease
Maximum Likelihood Methods for Back-Calculation
Model Goodness-of-Fit
Confidence and Prediction Intervals
POPULATION MODELS: RESULTS AND SENSITIVITY ANALYSES
Introduction
Distributional Forms
Model Results
Cross-Validation of Disease Parameters
Predictions
Maternal Transmission
Horizontal Transmission
Under-Reporting
Conclusions
INDIVIDUAL SURVIVAL MODELS
Introduction
Maternal Risk Enhancement Models
Analysis of the Maternal Cohort Study
Dam-Calf Pairs from the GB Case Database
Conclusions
MATERNAL RISK ENHANCEMENT MODELS: RESULTS
Introduction
Maternal Cohort Study
The Dam-Calf Pair Data in the GB Case Database
Suckler Calf Data
Conclusions
SPATIO-TEMPORAL CORRELATION AND DISEASE CLUSTERING
Introduction
Spatial Structure of the BSE Epidemic
Clustering of Cases in Holding
At Risk Holdings Model
Probabilistic Clustering Models
Culling Policy Design
Conclusions
Metapopulation Models
Introduction
Holding-Level Survival Models
Stochastic Simulation Models of the BSE Epidemic
Conclusions
PREDICTIONS AND SCENARIO ANALYSIS FOR vCJD
Introduction
Survival Model
Estimation/Scenario Analysis
Determinants of Epidemic Size
Minimum Incubation Period
Epidemic Predictability
Application to UAT Programme Design
Conclusions
FUTURE DIRECTIONS
Updated Back-Calculation Analysis of BSE in GB
vCJD Epidemic Prediction
Scrapie Epidemiology
Conclusion
REFERENCES
Editorial Reviews
"In addition to the obvious value from the assessment of the particular diseases in this book, the authors have laid out a nice template for anyone who is doing a similarly thorough assessment of a complex epidemiological system. For the most part, the book is easily readable by either statisticians or biologists…"
-Technometrics, May 2001
"The book is well written and interesting to read…authors claim that they aim to unify biostatistical and mathematical biology approaches and I think that they meet this aim fairly well."
--David Greenhalgh, University of Strathclyde, Glasgow
"In their 'must-read' book, Donnelly and Ferguson espouse that models of complex disease transmission dynamics should be placed in proper statistical context to ensure robust parameter estimation and sensitivity analysis, and to disallow over-exact fitting to observed data… This well-proofed book has significant appeal for statisticians interested in dynamical modelling of transmission mechanisms, mathematical modellers wanting to employ more rigorous statistical methods, and biological/medical/veterinary scientists who seek a quantitative understanding of BSE and vCJD."
Biometrics, Vol. 56, No. 4, December 2000
"A timely book such as this, which is thought-provoking and challenging at different levels, is an excellent addition [number 84] to the series of Monographs on Statistics and Applied Probability."
Biometrics, Vol. 56, No. 4, December 2000
"The book provides a comprehensive view of BSE modeling as seen from the backroom."
-Nature, January 2000
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