Buch, Englisch, Band 63, 300 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 482 g
A Modern Statistical Perspective
Buch, Englisch, Band 63, 300 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 482 g
Reihe: Statistics for Biology and Health
ISBN: 978-1-4899-8796-9
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Infektionskrankheiten
Weitere Infos & Material
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.