This text deals with the mathematical and statistical techniques underlying the models used to understand the population dynamics of not only HIV/AIDS, but also of other infectious diseases. Attention is given to the development of strategies for the prevention and control of the international epidemic within the frameworks of the models. The text incorporates stochastic and deterministic formulations within a unifying conceptual framework.

AIDS (autoimmune deficiency syndrome) is a devastating human disease cause by HIV, a human immunodeficiency virus, which may be transmitted by either sexual or other contacts in which body fluids are exchanged. Cases of AIDS have been reported in a majority of countries throughout the world, indicating that the HIV/AIDS epidemic is international in scope. This book deals with the mathematical and statistical techniques underlying the models used to understand the population dynamics of not only HIV/AIDS but also other infectious diseases. Attention is given to the development strategies for the prevention and control of the international epidemic within the frameworks of the models. Two distinguishing features of the book are the incorporation of stochastic and deterministic formulations within a unifying conceptual framework and the discussion of issues related to the mathematical designs of models, which are necessary for the rigorous utilization of computer-intensive methods. The book will be of value to applied mathematicians, biomathematicians, biostatisticians, epidemiologists and other scientists interested in applying mathematics and computers to not only the HIV/AIDS epidemic but also other fields of epidemiology.

This collection of papers gives a representative cross-selectional view of recent developments in the field. After a survey paper by C. Lefèvre, 17 other research papers look at stochastic modeling of epidemics, both from a theoretical and a statistical point of view. Some look more specifically at a particular disease such as AIDS, malaria, schistosomiasis and diabetes.

Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.

Based on lecture notes of two summer schools with a mixed audience from mathematical sciences, epidemiology and public health, this volume offers a comprehensive introduction to basic ideas and techniques in modeling infectious diseases, for the comparison of strategies to plan for an anticipated epidemic or pandemic, and to deal with a disease outbreak in real time. It covers detailed case studies for diseases including pandemic influenza, West Nile virus, and childhood diseases. Models for other diseases including Severe Acute Respiratory Syndrome, fox rabies, and sexually transmitted infections are included as applications. Its chapters are coherent and complementary independent units. In order to accustom students to look at the current literature and to experience different perspectives, no attempt has been made to achieve united writing style or unified notation. Notes on some mathematical background (calculus, matrix algebra, differential equations, and probability) have been prepared and may be downloaded at the web site of the Centre for Disease Modeling (www.cdm.yorku.ca).