Hens, N., Shkedy, Z., Aerts, M., Faes, C., Van Damme, P., Beutels, P.
2012, XVI, 300 p.
Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
Demonstrates the application of modern statistical methods and models to estimate infectious disease parameters
Provides the reader with software guidance and data
Uses valuable case studies
Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force of infection. The force of infection reflects the degree of contact with potential for transmission between infected and susceptible individuals. The mathematical relation between the force of infection and effective contact patterns is generally assumed to be subjected to the mass action principle, which yields the necessary information to estimate the basic reproduction number, another key parameter in infectious disease epidemiology.
It is within this context that the Center for Statistics (CenStat, I-Biostat, Hasselt University) and the Centre for the Evaluation of Vaccination and the Centre for Health Economic Research and Modelling Infectious Diseases (CEV, CHERMID, Vaccine and Infectious Disease Institute, University of Antwerp) have collaborated over the past 15 years. This book demonstrates the past and current research activities of these institutes and can be considered to be a milestone in this collaboration. This book is focused on the application of modern statistical methods and models to estimate infectious disease parameters. We want to provide the readers with software guidance, such as R packages, and with data, as far as they can be made publicly available.
Content Level »Research
Keywords »Contact Data - Epidemiology - Infectious Disease - Modeling - Serological Data
Mathematical models for infectious diesease.- The static model.- The dynamic model.- The stochastic model.- Implementation of models in MATLAB.- Data sources for modelling infectious diseases.- Estimation from serological data.- Parametric models for teh prevalence and the force of infection.- Non-parametric approaches to model the prevalence and force of infection.- Semi-parametric approaches to model the prevalence and force of infection.- A Bayesian approach.- Modelling the prevalence and the force of infection direction from antibody levels.- Modelling multivariate serological data.- Estimation from other data sources.- Estimating mixing patterns and Ro in a heterogenous population.- Modelling in a homogeneous population.- Modelling in a heterogeneous population.- Modelling AIDS outbreak data.- Modelling hepatitis C among injection drug users.- Modelling dengue.- Modelling bovine herpes virus in cattle.