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Zoning is crucial for controlling animal infectious diseases and movement plays a major role in disease transmission. However, movement-based zoning has received little research attention. This study aimed to identify biosecurity zones divided by administrative unit, based on communities detected in movement network. We used vehicle entry data from November 2013 to January 2017. We split the data to analyze changes in networks over time and seasons (3 summer and 4 winter). The HN algorithm for mega-scale networks was used to detect communities. We identified biosecurity zones based on the geographical concentration of facilities belonging to the same communities. Jenks Natural Breaks Method was used to determine whether facilities were agglomerated. The zone classifications derived for seven seasons were overlaid to identify an integrated zone classification. The number of significant communities declined from 10 to 7 over time, from which we inferred that separated communities tended to aggregate. Therefore, biosecurity zones that were separate in the past merged and the number of zones decreased. From the overlay, seven biosecurity zones were derived. These zones are different from the conventional control zones, which do not consider movement. Therefore, these biosecurity zones can be used as an alternative control zone to complement existing zoning systems in Korea.

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Movement-Based Biosecurity Zones for Control of Highly Infectious Animal Diseases: Application of Community Detection Analysis to a Livestock Vehicle Movement Network