Header

UZH-Logo

Maintenance Infos

Assessing the impact of a movement network on the spatiotemporal spread of infectious diseases


Schrödle, B; Held, L; Rue, H (2012). Assessing the impact of a movement network on the spatiotemporal spread of infectious diseases. Biometrics, 68(3):736-744.

Abstract

Linking information on a movement network with space-time data on disease incidence is one of the key challenges in infectious disease epidemiology. In this article, we propose and compare two statistical frameworks for this purpose, namely, parameter-driven (PD) and observation-driven (OD) models. Bayesian inference in PD models is done using integrated nested Laplace approximations, while OD models can be easily fitted with existing software using maximum likelihood. The predictive performance of both formulations is assessed using proper scoring rules. As a case study, the impact of cattle trade on the spatiotemporal spread of Coxiellosis in Swiss cows, 2004-2009, is finally investigated.

Abstract

Linking information on a movement network with space-time data on disease incidence is one of the key challenges in infectious disease epidemiology. In this article, we propose and compare two statistical frameworks for this purpose, namely, parameter-driven (PD) and observation-driven (OD) models. Bayesian inference in PD models is done using integrated nested Laplace approximations, while OD models can be easily fitted with existing software using maximum likelihood. The predictive performance of both formulations is assessed using proper scoring rules. As a case study, the impact of cattle trade on the spatiotemporal spread of Coxiellosis in Swiss cows, 2004-2009, is finally investigated.

Statistics

Citations

13 citations in Web of Science®
13 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

0 downloads since deposited on 11 Jan 2012
0 downloads since 12 months

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2012
Deposited On:11 Jan 2012 13:20
Last Modified:07 Dec 2017 10:43
Publisher:Wiley-Blackwell
ISSN:0006-341X
Publisher DOI:https://doi.org/10.1111/j.1541-0420.2011.01717.x
PubMed ID:22171626

Download