Modeling Infectious Disease Parameters Based on Serological and Social Contact Data (eBook)
XVI, 300 Seiten
Springer New York (Verlag)
978-1-4614-4072-7 (ISBN)
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.
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.
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.
| Erscheint lt. Verlag | 24.10.2012 |
|---|---|
| Reihe/Serie | Statistics for Biology and Health | Statistics for Biology and Health |
| Zusatzinfo | XVI, 300 p. |
| Verlagsort | New York |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Medizin / Pharmazie ► Allgemeines / Lexika | |
| Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie | |
| Studium ► Querschnittsbereiche ► Infektiologie / Immunologie | |
| Technik | |
| Schlagworte | Contact Data • epidemiology • infectious disease • Modeling • Serological Data |
| ISBN-10 | 1-4614-4072-6 / 1461440726 |
| ISBN-13 | 978-1-4614-4072-7 / 9781461440727 |
| Haben Sie eine Frage zum Produkt? |
PDF (Wasserzeichen)Größe: 9,2 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich
