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A Temporal Network Model for Livestock Trade Systems.
Ansari, Sara; Heitzig, Jobst; Brzoska, Laura; Lentz, Hartmut H K; Mihatsch, Jakob; Fritzemeier, Jörg; Moosavi, Mohammad R.
Afiliação
  • Ansari S; Department of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
  • Heitzig J; Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
  • Brzoska L; Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
  • Lentz HHK; Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
  • Mihatsch J; Institute of Epidemiology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
  • Fritzemeier J; Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
  • Moosavi MR; Landkreis Osnabrück, Veterinärdienst für Stadt und Landkreis Osnabrück, Osnabruck, Germany.
Front Vet Sci ; 8: 766547, 2021.
Article em En | MEDLINE | ID: mdl-34966806
ABSTRACT
The movements of animals between farms and other livestock holdings for trading activities form a complex livestock trade network. These movements play an important role in the spread of infectious diseases among premises. For studying the disease spreading among animal holdings, it is of great importance to understand the structure and dynamics of the trade system. In this paper, we propose a temporal network model for animal trade systems. Furthermore, a novel measure of node centrality important for disease spreading is introduced. The experimental results show that the model can reasonably well describe these spreading-related properties of the network and it can generate crucial data for research in the field of the livestock trade system.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Vet Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Irã

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Vet Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Irã