The book is a comprehensive, self-contained introduction to the mathematical modeling and analysis of disease transmission models. It includes (i) an introduction to the main concepts of compartmental models including models with heterogeneous mixing of individuals and models for vector-transmitted diseases, (ii) a detailed analysis of models for important specific diseases, including tuberculosis, HIV/AIDS, influenza, Ebola virus disease, malaria, dengue fever and the Zika virus, (iii) an introduction to more advanced mathematical topics, including age structure, spatial structure, and mobility, and (iv) some challenges and opportunities for the future.

There are exercises of varying degrees of difficulty, and projects leading to new research directions. For the benefit of public health professionals whose contact with mathematics may not be recent, there is an appendix covering the necessary mathematical background. There are indications which sections require a strong mathematical background so that the book can be useful for both mathematical modelers and public health professionals.

A modern description of many important areas of mathematical epidemiology Provides an introduction to the formation and analysis of disease transmission models Exercise sets and some projects included

Autorentext

Fred Brauer, Department of Mathematics, University of British Columbia, Canada; Carlos Castillo-Chavez, Mathematical, Computational and Modeling Sciences Center, Arizona State University, USA

Inhalt
Introduction; A prelude to mathematical epidemiology.- Simple compartmental models for disease transmission.- Endemic disease models.- Epidemic models.- Models with heterogeneous mixing.- Models for diseases transmitted by vectors.- models for tuberculosis.- Models for HIV?AIDS.- Models for influenza.- Models for Ebola.- Models for malaria.- Dengue fever and the Zika virus.- Disease transmission models withagedpendence.- Spatial structure in disease transmission models.- Epidemiological models incorporating mobility, behavior, and time scales.- Challenges, opportunities, and theoretical epidemiology.