Home \ Research \ Scientific publications \


Prediction of Pig Trade Movements in Different European Production Systems Using Exponential Random Graph Models

Investigation article published in Frontiers in veterinary science

March 3rd, 2017

In most European countries, data regarding movements of live animals are routinely collected and can greatly aid predictive epidemic modeling. However, the use of complete movements’ dataset to conduct policy-relevant predictions has been so far limited by the massive amount of data that have to be processed (e.g., in intensive commercial systems) or the restricted availability of timely and updated records on animal movements (e.g., in areas where small-scale or extensive production is predominant). The aim of this study was to use exponential random graph models (ERGMs) to reproduce, understand, and predict pig trade networks in different European production systems. Three trade networks were built by aggregating movements of pig batches among premises (farms and trade operators) over 2011 in Bulgaria, Extremadura (Spain), and Côtes-d’Armor (France), where small-scale, extensive, and intensive pig production are predominant, respectively. Three ERGMs were fitted to each network with various demographic and geographic attributes of the nodes as well as six internal network configurations. Several statistical and graphical diagnostic methods were applied to assess the goodness of fit of the models. For all systems, both exogenous (attribute-based) and endogenous (network-based) processes appeared to govern the structure of pig trade network, and neither alone were capable of capturing all aspects of the network structure. Geographic mixing patterns strongly structured pig trade organization in the small-scale production system, whereas belonging to the same company or keeping pigs in the same housing system appeared to be key drivers of pig trade, in intensive and extensive production systems, respectively. Heterogeneous mixing between types of production also explained a part of network structure, whichever production system considered. Limited information is thus needed to capture most of the global structure of pig trade networks. Such findings will be useful to simplify trade networks analysis and better inform European policy makers on risk-based and more cost-effective prevention and control against swine diseases such as African swine fever, classical swine fever, or porcine reproductive and respiratory syndrome




Relun A., Grosbois V., Alexandrov T., Sanchez-Vizcaino JM., Waret-Szkuta A., Molia S., Charles-Etter EM. and Martinez-Lopez B.




See this article
Prediction of Pig Trade Movements in Different European Production Systems Using Exponential Random Graph Models

See it on NLM PubMed
Prediction of Pig Trade Movements in Different European Production Systems Using Exponential Random Graph Models



Participants:

University of California-DavisUniversity of California-Davis (UCDAVIS).

Centre de Cooperation International en Recherche Agronomique pour le DeveloppementCentre de Cooperation International en Recherche Agronomique pour le Developpement (CIRAD).

Bulgarian Food Safety AgencyBulgarian Food Safety Agency (BFSA).

Universidad ComplutenseServicio de Inmunología Viral y Medicina Preventiva (SUAT). Centro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM).

Universidad ComplutenseDepartamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM).

Instituto Nacional de Investigación Agronómica de FranciaInstituto Nacional de Investigación Agronómica de Francia (INRA).







Frontiers in veterinary science
FACTOR YEAR Q
N/A

NLMID: 101666658

PMID: 28316972

ISSN: 2297-1769



TITLE: Prediction of Pig Trade Movements in Different European Production Systems Using Exponential Random Graph Models


JOURNAL: Front Vet Sci


NUMERACIÓN: 4(27):1-12


AÑO: 2017


PUBLISHER: Lausanne : Frontiers Media S.A


AUTHORS: Relun A., Grosbois V., Alexandrov T., Sanchez-Vizcaino JM., Waret-Szkuta A., Molia S., Charles-Etter EM. and Martinez-Lopez B.


VISAVET PARTICIPANTS


José Manuel Sánchez-Vizcaíno Rodríguez

DOI: https://doi.org/10.3389/fvets.2017.00027


CITE THIS PUBLICATION:

Relun A., Grosbois V., Alexandrov T., Sanchez-Vizcaino JM., Waret-Szkuta A., Molia S., Charles-Etter EM. and Martinez-Lopez B. Prediction of Pig Trade Movements in Different European Production Systems Using Exponential Random Graph Models. Frontiers in veterinary science. 4(27):1-12. 2017. (A). ISSN: 2297-1769. DOI: 10.3389/fvets.2017.00027


UNITS: