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Network Analysis of Swine Farms and Slaughters: Based on Automobile GPS Data

  • Journal of the Korean Cartographic Association
  • Abbr : JKCA
  • 2019, 19(1), pp.69-79
  • DOI : 10.16879/jkca.2019.19.1.069
  • Publisher : The Korean Cartographic Association
  • Research Area : Social Science > Geography > Geography in general > Cartography
  • Received : March 4, 2019
  • Accepted : April 16, 2019
  • Published : April 30, 2019

Minje Jeong 1,  Ik-Hoon Jang 2,  Youngchan Choe 2

1서울대학교 농경제사회학부
2서울대학교

Accredited

ABSTRACT

This study is to conduct a network analysis between hog farms and slaughters using GPS based vehiclemovement data. In order to cope with foot and mouth disease, early response and preemptive prevention ofepidemics can be crucial role. Analysis of vehicle movement that is a major agent for disease spread andrelationship between slaughters and hog farms needs to be conducted for the above strategies. This studyconducted network analysis between slaughters and swine farms with vehicle movement data from KAHIS (Korea Animal Health Integrated System). For this analysis, we constructed binary matrix data between slaughters andswine farms. We applied ‘Rasch Model’ to estimate risk scores for each slaughters and swine farms. After that,we also used ‘Latent Class Analysis (LCA)’ to cluster swine farms. Results from ‘Rasch Model’ said that farmsin Jeollabuk-do Province and Gyeonggi-do Province have high level risk scores which indicates high risks fordisease spread. Results from LCA said that the proper number of clusters is seven. Considering the risk scoresfrom ‘Rasch Model’, which indicates level of relationship with diverse slaughters, government agency needs toconcentrate upon clustering group 4, followed by cluster group 1, 3, 5, 6. In the case of cluster group 2, 7, whichhave low scores, they have relatively lower risks for disease spread. The results considered, it can be a betterstrategy that government agency restricts only a few paths in Jeollabuk-do Province and Chungcheongnam-doProvince instead of all paths in the outbreak of disease.

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