Aviso: para depositar documentos, por favor, inicia sesión e identifícate con tu cuenta de correo institucional de la UCM con el botón MI CUENTA UCM. No emplees la opción AUTENTICACIÓN CON CONTRASEÑA
 

A novel spatial and stochastic model to evaluate the within- and between-farm transmission of classical swine fever virus. I. General concepts and description of the model

Loading...
Thumbnail Image

Full text at PDC

Publication date

2011

Advisors (or tutors)

Editors

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier Science
Citations
Google Scholar

Citation

Abstract

A new stochastic and spatial model was developed to evaluate the potential spread of classical swine fever virus (CSFV) within- and between-farms, and considering the specific farm-to-farm contact network. Within-farm transmission was simulated using a modified SI model. Between-farm transmission was assumed to occur by direct contacts (i.e. animal movement) and indirect contacts (i.e. local spread, vehicle and person contacts) and considering the spatial location of farms. Control measures dictated by the European legislation (i.e. depopulation of infected farms, movement restriction, zoning, surveillance, contact tracing) were also implemented into the model. Model experimentation was performed using real data from Segovia, one of the provinces with highest density of pigs in Spain, and results were presented using the mean, 95% probability intervals [95% PI] and risk maps. The estimated mean [95% PI] number of infected, quarantined and depopulated farms were 3 [1,17], 23 [0,76] and 115 [0,318], respectively. The duration of the epidemic was 63 [26,177] days and the most important way of transmission was associated with local spread (61.4% of the infections). Results were consistent with the spread of previous CSFV introductions into the study region. The model and results presented here may be useful for the decision making process and for the improvement of the prevention and control programmes for CSFV.

Research Projects

Organizational Units

Journal Issue

Description

Keywords

Collections