Literature DB >> 21159393

Evaluation of risk and vulnerability using a Disease Flow Centrality measure in dynamic cattle trade networks.

Fabrizio Natale1, Lara Savini, Armando Giovannini, Paolo Calistri, Luca Candeloro, Gianluca Fiore.   

Abstract

A new method for the calculation of a centrality measure (Disease Flow Centrality, DFC), which takes into account temporal dynamics of livestock movement networks, is proposed. The method is based on a network traversal algorithm which represents an epidemic process more realistically compared with traditional graph traversal algorithms used in the calculation of centrality measures on static networks. The new approach was tested on networks generated from all the registered movements of cattle in Italy in the years 2007, 2008 and 2009 and the results were compared to those obtained by classical centrality measures. The results show that DFC values often differ substantially from those of other centrality measures and that these DFC values tend to be more unstable in time. The DFC offers several advantages for assessing risk and vulnerability of specific holdings and of an entire network, using recent movement data from national livestock databases. Some examples also indicate how the basic approach in the DFC calculation could be expanded into a more complex epidemic model by incorporating weights and how it could be combined with a geo-spatial perspective. Copyright Â
© 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 21159393     DOI: 10.1016/j.prevetmed.2010.11.013

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  14 in total

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Journal:  J R Soc Interface       Date:  2012-06-22       Impact factor: 4.118

2.  Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies.

Authors:  G L Chaters; P C D Johnson; S Cleaveland; J Crispell; W A de Glanville; T Doherty; L Matthews; S Mohr; O M Nyasebwa; G Rossi; L C M Salvador; E Swai; R R Kao
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-07-08       Impact factor: 6.237

3.  Dynamical patterns of cattle trade movements.

Authors:  Paolo Bajardi; Alain Barrat; Fabrizio Natale; Lara Savini; Vittoria Colizza
Journal:  PLoS One       Date:  2011-05-18       Impact factor: 3.240

4.  Suboptimal herd performance amplifies the spread of infectious disease in the cattle industry.

Authors:  M Carolyn Gates; Mark E J Woolhouse
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

5.  Network epidemiology and plant trade networks.

Authors:  Marco Pautasso; Mike J Jeger
Journal:  AoB Plants       Date:  2014-04-29       Impact factor: 3.276

6.  Disease Spread through Animal Movements: A Static and Temporal Network Analysis of Pig Trade in Germany.

Authors:  Hartmut H K Lentz; Andreas Koher; Philipp Hövel; Jörn Gethmann; Carola Sauter-Louis; Thomas Selhorst; Franz J Conraths
Journal:  PLoS One       Date:  2016-05-06       Impact factor: 3.240

7.  Development of a forecasting model for brucellosis spreading in the Italian cattle trade network aimed to prioritise the field interventions.

Authors:  L Savini; L Candeloro; A Conte; F De Massis; A Giovannini
Journal:  PLoS One       Date:  2017-06-27       Impact factor: 3.240

8.  Dynamic network measures reveal the impact of cattle markets and alpine summering on the risk of epidemic outbreaks in the Swiss cattle population.

Authors:  Beatriz Vidondo; Bernhard Voelkl
Journal:  BMC Vet Res       Date:  2018-03-13       Impact factor: 2.741

9.  On the robustness of in- and out-components in a temporal network.

Authors:  Mario Konschake; Hartmut H K Lentz; Franz J Conraths; Philipp Hövel; Thomas Selhorst
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

10.  Predicting epidemic risk from past temporal contact data.

Authors:  Eugenio Valdano; Chiara Poletto; Armando Giovannini; Diana Palma; Lara Savini; Vittoria Colizza
Journal:  PLoS Comput Biol       Date:  2015-03-12       Impact factor: 4.475

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