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Epidemic Modelling
  • Cited by 300
  • D. J. Daley, Australian National University, Canberra, J. Gani, Australian National University, Canberra
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Book description

This general introduction to the ideas and techniques required for the mathematical modelling of diseases begins with an outline of some disease statistics dating from Daniel Bernoulli's 1760 smallpox data. The authors then describe simple deterministic and stochastic models in continuous and discrete time for epidemics taking place in either homogeneous or stratified (non-homogeneous) populations. Several techniques for constructing and analysing models are provided, mostly in the context of viral and bacterial diseases of human populations. These models are contrasted with models for rumours and vector-borne diseases like malaria. Questions of fitting data to models, and their use in understanding methods for controlling the spread of infection, are discussed. Exercises and complementary results at the end of each chapter extend the scope of the text, which will be useful for students taking courses in mathematical biology who have some basic knowledge of probability and statistics.


‘… It gives an excellent general introduction to epidemic modelling, starting with an interesting historical account and then describing the most important and useful models which can be used.’

Robert MacMillan Source: Mathematical Gazette

‘The book will be accessible … and its study highly rewarding, to anyone with an interest in epidemic models…’

V. S. Isham Source: Short Book Reviews

‘Daley and Gani’s monograph is a concise and useful presentation of a variety of epidemiological models.’

Daniel Haydon Source: Trends in Ecology and Evolution

‘… gives an excellent general introduction to epidemic modelling … should certainly be available to undergraduates.’

Robert MacMillan Source: The Mathematical Gazette

‘This book had us hooked … [it] remains an important reference in our library and is frequently consulted for advice on how to think about modelling in related contexts.’

Darfiana Nur and Kerrie L. Mengersen Source: The Australian and New Zealand Journal of Statistics

‘… the book is clear and well written … could serve as course literature for graduate, or possibly last year undergraduate, course in epidemic modelling.’

Source: Statistics in Medicine

‘I found the book very clear, concise and useful … I recommend the book very strongly as a teaching tool and as a research tool to academics and scientists who are interested in epidemic modeling. I also strongly recommend the book to applied mathematicians who are intetrested in stochastic models in general.’

Source: Mathematics Today

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