African swine fever (ASF) is a hemorrhagic viral disease of pigs requiring laboratory diagnosis for confirmation. Though tissue and blood samples are considered optimal for ASF diagnosis, collection of these samples can be laborious, time-consuming, and pose a risk of contaminating the environment. Here, we suggest an alternative non-invasive sampling method, hair plucking, for ASF diagnosis. ASF virus was detected in plucked hair samples from experimentally infected pigs. Although the sensitivity was inferior to whole blood, the results suggest that hair plucking can be an alternative method that can also improve animal welfare.

In this paper, a mathematical model of regionalization based on graph theory to investigate the patterns induced by movements of livestock vehicles in cities under outbreaks of highly pathogenic avian influenza (HPAI) is proposed. We then compare the results of simulation from the regionalization model to actual HPAI outbreaks in 2016/2017 to evaluate the validity of the model. Specifically, we (1) configured a complex network structure with analytic tools and properties in graph theory to abstract the paths among farms and livestock facilities; (2) employed statistical methods to estimate the possibility of propagation between two clusters; (3) applied the developed method to an actual HPAI outbreak in Korea in 2016 and conducted a simulation to determine if the proposed modeling for regionalization is an effective prediction measure. The clustered regions proposed by the simulation correctly reflected the regional clustering of actual cases, while simultaneously contain the cities exposed to potential damage when separated. Based on these findings, we conclude that our proposed regionalization model is suitable for making policy judgments to establish a preemptive biosecurity system.