Sterchi, Martin

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Martin
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Sterchi, Martin

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20192
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Autor:in: Berezowski, John ×

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  • Vorschaubild
    Publikation
    The pig transport network in Switzerland. Structure, patterns, and implications for the transmission of infectious diseases between animal holdings
    (Public Library of Science, 2019) Sterchi, Martin; Faverjon, Céline; Sarasua, Cristina; Vargas, Maria Elena; Berezowski, John; Bernstein, Abraham; Grütter, Rolf; Nathues, Heiko [in: PLOS ONE]
    The topology of animal transport networks contributes substantially to how fast and to what extent a disease can transmit between animal holdings. Therefore, public authorities in many countries mandate livestock holdings to report all movements of animals. However, the reported data often does not contain information about the exact sequence of transports, making it impossible to assess the effect of truck sharing and truck contamination on disease transmission. The aim of this study was to analyze the topology of the Swiss pig transport network by means of social network analysis and to assess the implications for disease transmission between animal holdings. In particular, we studied how additional information about transport sequences changes the topology of the contact network. The study is based on the official animal movement database in Switzerland and a sample of transport data from one transport company. The results show that the Swiss pig transport network is highly fragmented, which mitigates the
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    A transdisciplinary approach supporting the implementation of a big data project in livestock production: an example from the Swiss pig production industry
    (Frontiers Research Foundation, 2019) Faverjon, Céline; Bernstein, Abraham; Grütter, Rolf; Nathues, Christina; Nathues, Heiko; Sarasua, Cristina; Sterchi, Martin; Vargas, Maria Elena; Berezowski, John [in: Frontiers in Veterinary Science]
    Big Data approaches offer potential benefits for improving animal health, but they have not been broadly implemented in livestock production systems. Privacy issues, the large number of stakeholders, and the competitive environment all make data sharing, and integration a challenge in livestock production systems. The Swiss pig production industry illustrates these and other Big Data issues. It is a highly decentralized and fragmented complex network made up of a large number of small independent actors collecting a large amount of heterogeneous data. Transdisciplinary approaches hold promise for overcoming some of the barriers to implementing Big Data approaches in livestock production systems. The purpose of our paper is to describe the use of a transdisciplinary approach in a Big Data research project in the Swiss pig industry. We provide a brief overview of the research project named “Pig Data,” describing the structure of the project, the tools developed for collaboration and knowledge transfer, the data received, and some of the challenges. Our experience provides insight and direction for researchers looking to use similar approaches in livestock production system research.
    01A - Beitrag in wissenschaftlicher Zeitschrift