This book is intended as a primary resource for graduate students and researchers working in the field of infectious disease epidemiology. This collection of contributions presents deterministic and stochastic approaches for epidemic modelling and statistical inference of epidemiological parameters including the real time assessment of the transmission potential of infectious diseases, issues related to the sensitivity of model assumptions, the use of historical archives as valuable sources of epidemiological information, modeling of vaccination programs and relapse, statistical challenges in bio surveillance, approaches for the spatial and temporal analysis of disease time series, quantification of parameter uncertainty and methodologies for sensitivity analysis. Methods and tools are illustrated with simulated and real datasets such as the 1918 influenza pandemic in Winnipeg, Canada, the 1968 influenza pandemic in US cities, Severe Acute Respiratory Syndrome (SARS), the 2005 Marburg fever outbreak in Angola, rubella epidemics in Peru, rotavirus in Mexico and pneumococcal disease in Australia.