Biology

Immunology and Evolution of Infectious Disease

Steven A. Frank

An author-authorized free synthesis of immunity and pathogen evolution, connecting molecular recognition with infection dynamics and population-level variation.

Prerequisites

University immunology or cell biology, genetics and evolutionary biology. Basic probability, differential equations and population dynamics help with the modelling arguments; review unfamiliar immune mechanisms before interpreting a model.

Publication Year
2002
Difficulty Level
Advanced
Academic Level
Graduate
immunologyantigenic variationpathogen evolution

01 / Reading Guide

Reading Guide

Who this book is for

For advanced undergraduates and graduate students interested in evolutionary immunology. The book brings molecular and population perspectives into the same argument, making it useful for readers who know the components of an immune response but want to understand how recognition, variation and selection interact. It is a synthesis after foundational courses rather than a comprehensive first immunology textbook.

Prerequisites

University immunology or cell biology, genetics and evolutionary biology. Basic probability, differential equations and population dynamics help with the modelling arguments; review unfamiliar immune mechanisms before interpreting a model.

What it covers

The discussion links vertebrate immunity, molecular recognition, antigenic variation, the dynamics of infection within hosts and the genetic structure of pathogen populations. Mathematical models are used to organize biological reasoning about persistence and escape. Different scales of analysis make explicit why a mechanism within one host can have consequences for patterns across many infections.

How to use it

Draw the sequence from a molecular change to altered recognition, infection dynamics and selection. For a model, identify the state variables, biological assumptions and the timescales being combined. Test an extreme parameter case before accepting a general conclusion. Compare the prediction with the type of experiment or population observation needed to evaluate it. Keep mechanistic possibility separate from evidence that a process explains a particular infection, and use recent literature to update historical examples.

Edition and sources

The author’s book page explicitly provides the complete Princeton University Press book, published July 2002, as a PDF and through NCBI Bookshelf. This is authorized free reading, with copyright retained, rather than an inferred Creative Commons licence. Older empirical and clinical context requires later sources.

Open the official resource