The Basic Reproduction Number of Infectious Diseases: Computation and Estimation Using Compartmental Epidemic Models -- Stochastic Epidemic Modeling -- Two Critical Issues in Quantitative Modeling of Communicable Diseases: Inference of Unobservables and Dependent Happening -- The Chain of Infection, Contacts, and Model Parametrization -- The Effective Reproduction Number as a Prelude to Statistical Estimation of Time-Dependent Epidemic Trends -- Sensitivity of Model-Based Epidemiological Parameter Estimation to Model Assumptions -- An Ensemble Trajectory Method for Real-Time Modeling and Prediction of Unfolding Epidemics: Analysis of the 2005 Marburg Fever Outbreak in Angola -- Statistical Challenges in BioSurveillance -- Death Records from Historical Archives: A Valuable Source of Epidemiological Information -- Sensitivity Analysis for Uncertainty Quantification in Mathematical Models -- An Inverse Problem Statistical Methodology Summary -- The Epidemiological Impact of Rotavirus Vaccination Programs in the United States and Mexico -- Spatial and Temporal Dynamics of Rubella in Peru, 1997–2006: Geographic Patterns, Age at Infection and Estimation of Transmissibility -- The Role of Nonlinear Relapse on Contagion Amongst Drinking Communities.

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.