by Odo Diekmann, Hans Heesterbeek, and Tom Britton.
I already had a very short announcement about this book. Now I had a chance to look through it and here are my two cents about this monograph.
The authors of this book made an attempt to unite two older books, first Mathematical Epidemiology of Infectious Diseases by the first two authors, and second Stochastic Epidemic Models and Their Statistical Analysis by Andersson and Britton. In the introduction the authors say that
The present book is based on these two earlier volumes, and in fact make them both obsolete. It replaces them with a textbook in the spirit of ‘Diekmann and Heesterbeek,’ and the result is, in our (admittedly biased, but humble) opinion, more valuable than the sum of its parts.
Unfortunately, I cannot agree with the cited statement. When reading for the first time the book by Diekmann and Heesterbeek, I could not help noticing that significant part of this book looks like the authors had to sacrifice the quality of exposition due to some time limitations (they actually say about lack of time in the book itself). This implies that the exposition was very uneven, when very thoughtful chapters alternate with rather sketchy ones. The same is even more pronounced for this new volume, with additional thing that notation is somewhat differ from chapter to chapter.
Without any doubt this new book is a must read for any one who works in mathematical epidemiology, however, two main points of my criticism are:
- this book does not replace two older ones (e.g., the stochastic treatment of epidemics in heterogeneous population is absent in this new text);
- the text looks like it was just merged together with some updates, again, probably, due to some time constraints. This means, e.g., that the early onset of epidemic and the corresponding branching process is treated twice, to give one example. My hope that the authors would carefully put together both texts did not materialize.
All this said, I would like to add that this text is definitely the best book today for those who would like to study mathematical modeling of epidemic spread from a theoretical point of view.
Mathematical Biology 