Modeling Infectious Diseases in Humans and Animals

ISBN-10: 0691116172
ISBN-13: 9780691116174
Edition: 2008
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Description: For epidemiologists, evolutionary biologists, and health-care professionals, real-time and predictive modeling of infectious disease is of growing importance. This book provides a timely and comprehensive introduction to the modeling of infectious  More...

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Book details

Copyright year: 2008
Publisher: Princeton University Press
Publication date: 10/28/2007
Binding: Hardcover
Pages: 408
Size: 7.25" wide x 10.25" long x 1.25" tall
Weight: 1.562
Language: English

For epidemiologists, evolutionary biologists, and health-care professionals, real-time and predictive modeling of infectious disease is of growing importance. This book provides a timely and comprehensive introduction to the modeling of infectious diseases in humans and animals, focusing on recent developments as well as more traditional approaches. Matt Keeling and Pejman Rohani move from modeling with simple differential equations to more recent, complex models, where spatial structure, seasonal "forcing," or stochasticity influence the dynamics, and where computer simulation needs to be used to generate theory. In each of the eight chapters, they deal with a specific modeling approach or set of techniques designed to capture a particular biological factor. They illustrate the methodology used with examples from recent research literature on human and infectious disease modeling, showing how such techniques can be used in practice. Diseases considered include BSE, foot-and-mouth, HIV, measles, rubella, smallpox, and West Nile virus, among others. Particular attention is given throughout the book to the development of practical models, useful both as predictive tools and as a means to understand fundamental epidemiological processes. To emphasize this approach, the last chapter is dedicated to modeling and understanding the control of diseases through vaccination, quarantine, or culling. Comprehensive, practical introduction to infectious disease modeling Builds from simple to complex predictive models Models and methodology fully supported by examples drawn from research literature Practical models aid students' understanding of fundamental epidemiological processes For many of the models presented, the authors provide accompanying programs written in Java, C, Fortran, and MATLAB In-depth treatment of role of modeling in understanding disease control

Acknowledgments
Introduction
Types of Disease
Characterization of Diseases
Control of Infectious Diseases
What Are Mathematical Models?
What Models Can Do
What Models Cannot Do
What Is a Good Model?
Layout of This Book
What Else Should You Know?
Introduction to Simple Epidemic Models
Formulating the Deterministic SIR Model
The SIR Model Without Demography
The Threshold Phenomenon
Epidemic Burnout
Worked Example: Influenza in a Boarding School
The SIR Model With Demography
The Equilibrium State
Stability Properties
Oscillatory Dynamics
Mean Age at Infection
Infection-Induced Mortality and SI Models
Mortality Throughout Infection
Density-Dependent Transmission
Frequency Dependent Transmission
Mortality Late in Infection
Fatal Infections
Without Immunity: The SIS Model
Waning Immunity: The SIRS Model
Adding a Latent Period: The SEIR Model
Infections with a Carrier State
Discrete-Time Models
Parameterization
Estimating R0 from Reported Cases
Estimating R0 from Seroprevalence Data
Estimating Parameters in General
Summary
Host Heterogeneities
Risk-Structure: Sexually Transmitted Infections
Modeling Risk Structure
High-Risk and Low-Risk Groups
Initial Dynamics
Equilibrium Prevalence
Targeted Control
Generalizing the Model
Parameterization
Two Applications of Risk Structure
Early Dynamics of HIV
Chlamydia Infections in Koalas
Other Types of Risk Structure
Age-Structure: Childhood Infections
Basic Methodology
Initial Dynamics
Equilibrium Prevalence
Control by Vaccination
Parameterization
Applications of Age Structure
Dynamics of Measles
Spread and Control of BSE
Dependence on Time Since Infection
SEIR and Multi-Compartment Models
Models with Memory
Application: SARS
Future Directions
Summary
Multi-Pathogen/Multi-Host Models
Multiple Pathogens
Complete Cross-Immunity
Evolutionary Implications
No Cross-Immunity
Application: The Interaction of Measles and Whooping Cough
Application: Multiple Malaria Strains
Enhanced Susceptibility
Partial Cross-Immunity
Evolutionary Implications
Oscillations Driven by Cross-Immunity
A General Framework
Multiple Hosts
Shared Hosts
Application: Transmission of Foot-and-Mouth Disease
Application: Parapoxvirus and the Decline of the Red Squirrel
Vectored Transmission
Mosquito Vectors
Sessile Vectors
Zoonoses
Directly Transmitted Zoonoses
Vector-Borne Zoonoses: West Nile Virus
Future Directions
Summary
Temporally Forced Models
Historical Background
Seasonality in Other Systems
Modeling Forcing in Childhood Infectious Diseases: Measles
Dynamical Consequences of Seasonality: Harmonic and Subharmonic Resonance
Mechanisms of Multi-Annual Cycles
Bifurcation Diagrams
Multiple Attractors and Their Basins
Which Forcing Function?
Dynamical Trasitions

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