Population Genetics of Viruses: Evolutionary Dynamics and Genomic Inference

This book is dedicated to the computer models of microevolution and their applications in virology and biomedicine. Its content is based on courses taught by the author at Peter the Great St. Petersburg Polytechnic University. Several viruses, including HIV, hepatitis C virus (HCV), influenza viruses, and coronaviruses, evolve rapidly within human populations and consequently exhibit extensive genetic diversity. In the case of HIV and HCV, viruses persisting in their hosts, substantial genetic variation can also arise within individual hosts. Rapid evolution enables viruses to evade immune responses, reduce vaccine effectiveness, and develop resistance to antiviral therapies. Mathematical models make it possible to predict viral evolutionary dynamics in a probabilistic framework, providing insights that are essential for optimizing vaccine design and antiviral treatment strategies. The book is intended for undergraduate and graduate students in the biological and medical sciences, as well as for early-career researchers. Although it focuses on mathematical models, it avoids mathematical notation and instead relies on diagrams, graphs, and conceptual explanations, making the subject accessible to readers without an advanced mathematical background.