Mathematical Tools for Understanding Infectious Disease Dynamics

Forsideomslag
Princeton University Press, 2013 - 502 sider

Mathematical modeling is critical to our understanding of how infectious diseases spread at the individual and population levels. This book gives readers the necessary skills to correctly formulate and analyze mathematical models in infectious disease epidemiology, and is the first treatment of the subject to integrate deterministic and stochastic models and methods.

Mathematical Tools for Understanding Infectious Disease Dynamics fully explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology. This comprehensive and accessible book also features numerous detailed exercises throughout; full elaborations to all exercises are provided.

  • Covers the latest research in mathematical modeling of infectious disease epidemiology
  • Integrates deterministic and stochastic approaches
  • Teaches skills in model construction, analysis, inference, and interpretation
  • Features numerous exercises and their detailed elaborations
  • Motivated by real-world applications throughout

 

Indhold

The epidemic in a closed population
3
The art of averaging
33
The impact of chance
45
Dynamics at the demographic time scale
73
CONTENTS
127
The concept of state
153
The basic reproduction number
161
Other indicators of severity
205
CONTENTS ix
249
What is contact?
265
Estimators of R0 derived from mechanistic models
309
Datadriven modeling of hospital infections
325
A brief guide to computer intensive statistics
337
Elaborations for Part I
349
CONTENTS
407
Elaborations for Part III
483

Age structure
227
Spatial spread
239
Index
497
Copyright

Almindelige termer og sætninger

approximation assume assumption asymptotic basic reproduction number become infected branching process CHAPTER colonized compute consider constant contact process contact rate corresponding defined demographic denote density depends derive described deterministic differential equations disease dominant eigenvalue dynamics eigenvalue eigenvector ELABORATIONS endemic equals estimate example Exercise expected number exponentially distributed expression factor final final-size force of infection formula fraction function given graph growth h-state hence host population immune infected individual infectious agent infectious period initial integral interval latency period linear macroparasites major outbreak Markov chain martingale mean Note number of contacts number of infected observed obtain pair parameters parasites patients Poisson distribution probability per unit quantity random variable result Section Show situation solution specific spectral radius state-at-infection stochastic epidemic model susceptible transmission vaccination vector zero

Bibliografiske oplysninger

TitelMathematical Tools for Understanding Infectious Disease Dynamics
EBSCO ebook academic collection
Bind 7 af Princeton Series in Theoretical and Computational Biology
ForfattereOdo Diekmann, Hans Heesterbeek, Tom Britton
Udgaveillustreret
UdgiverPrinceton University Press, 2013
ISBN0691155399, 9780691155395
Længde502 sider
  
Eksporter henvisningBiBTeX EndNote RefMan