Surveillance of ASF-infected pig farms from September to October 2019 in South Korea

Cho, Ki-Hyun; Kim, Hyun Joo; Kim, Da Young; Yoo, Dae-Sung; Nah, Jin Ju; Kim, Yong Joo; Kang, Hyung-Lyun

doi:10.4142/jvs.2021.22.e26

Cited by 9 publications

(14 citation statements)

References 8 publications

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“…No trace of ASFV genomic DNA was detected by laboratory analysis. This result may reflect the effects of immediate control measures following the detection of farms with ASF outbreaks in the early phase of infection in Korea (Cho et al., 2021; Kim et al., 2021; Yoon et al., 2020). The possibility of ASFV detection in arthropods collected from the farms with ASF outbreak cannot be ruled out if these were delayed.…”

Section: Discussionmentioning

confidence: 99%

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Arthropods as potential vectors of African swine fever virus outbreaks in pig farms in the Republic of Korea

Yoon

Hong

Lee

et al. 2021

Veterinary Medicine & Sci

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The seasonality of African swine fever (ASF) in the summers and outbreaks in farms with high biosecurity levels suggest that the ASF virus (ASFV) may be transmitted by arthropod vectors. Arthropods were collected in this study from 14 pig farms with ASF outbreaks in Korea in 2019 to explore the role of arthropods as potential ASFV vectors. A total of 28,729 arthropods, including 28,508 (99.2%) Diptera, were collected using blacklight traps, insect nets and yellow sticky strips. All arthropod samples were negative for ASFV genomic DNA according to laboratory tests using real‐time polymerase chain reaction. This result may reflect the effects of immediate control measures following the detection of farms with ASF outbreaks in the early phase of infection in Korea.

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Section: Discussionmentioning

confidence: 99%

“…ASFV genomic DNA was detected from one tube, a pool of swabs of faeces and feed on an individual cage at a backyard farm (data unpublished). This reflected that the environment of the farms with ASF has not been extensively contaminated (Cho et al., 2021). Thus, a little possibility for arthropods to be exposed to ASFV was noted.…”

Section: Discussionmentioning

confidence: 99%

Arthropods as potential vectors of African swine fever virus outbreaks in pig farms in the Republic of Korea

Yoon

Hong

Lee

et al. 2021

Veterinary Medicine & Sci

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“…As such, although the final goal of our study application focuses primarily on livestock tracking, human detection was also implemented and tested in livestock farms. Detection and tracking of farm staff/workers, guests or intruders/outsiders may offer early evidence in active surveillance for ASF at farms [ 17 ]. Greater attention to TADs which are both zoonotic and non-zoonotic (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…Here, the disease is still causing great concern, with transmission from ASF-infected wild boars to domestic pigs highly probable [ 4 ]. The first outbreak of ASF in South Korea was reported in September 2019, following an outbreak in North Korea, as well as dramatic spread in China and other Asian countries [ 5 ]. ASF has been reported in at least 60 countries around the globe [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

“…For this reason, early detection of TADs such as ASF in the field followed by rapid laboratory diagnosis is critical to its prompt eradication. Passive surveillance based on reports from farmers is highly recommended for the early detection of ASF, ensuring the effective prevention of further spread and significant minimization of insurmountable damages as well as huge socio-economic consequences in the country [ 1 3 5 6 ].…”

Section: Introductionmentioning

confidence: 99%

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Object detection and tracking using a high-performance artificial intelligence-based 3D depth camera: towards early detection of African swine fever

Ryu

Tai

2022

J Vet Sci

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Background Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

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Prevalence of porcine circovirus type 2 and type 3 in slaughtered pigs and wild boars in Korea

Park,

Kim,

Jeong

et al. 2023

Veterinary Medicine & Sci

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BackgroundPorcine circovirus, a non‐enveloped single‐stranded DNA virus belonging to the genus Circovirus of the family Circoviridae, is a major pathogen of porcine circovirus‐associated disease. Porcine circovirus 3, a novel porcine circovirus, has been identified in individuals with clinical symptoms.ObjectivesThe prevalence of porcine circovirus 2 and porcine circovirus 3 and the confirmation of diagnosis of this emerging viral disease have not been fully studied yet. Therefore, the objective of the present study was to investigate the prevalence of porcine circovirus 2 and porcine circovirus 3 in slaughtered pigs and wild boars in Korea between 2018 and 2019.MethodsLungs and hilar lymph nodes of healthy pigs slaughtered in slaughterhouses and captured wild pigs were collected, and viruses were detected by multiplex quantitative polymerase chain reaction and two staining methods (in situ hybridization and immunohistochemistry) to confirm the presence of porcine circovirus 2 and porcine circovirus 3.ResultsPositive rates of porcine circovirus 2 in lungs and hilar lymph nodes were 78.1% (75/96) and 89.5% (86/96) in slaughtered pigs, respectively. They were 18.0% (30/167) and 46.3% (24/55) in wild boars, respectively. Positive rates of porcine circovirus 3 in lungs and hilar lymph nodes were 30.2% (29/96) and 13.5% (13/96) in slaughtered pigs, respectively. They were 4.2% (7/167) and 5.5% (3/55) in wild boars, respectively. At the farm level, positive rates of porcine circovirus 2 and porcine circovirus 3 were 97.9% (47/48) and 54.2% (26/48), respectively. Positive rates of porcine circovirus 2 and porcine circovirus 3 decreased in spring. Immunohistochemistry and in situ hybridization confirmed the presence of porcine circovirus 2 and porcine circovirus 3 in lungs, but not porcine circovirus 3 in the hilar lymph nodes.ConclusionThese results suggest that the prevalence of porcine circovirus 2 and porcine circovirus 3 might vary depending on the season and the type of sample. Wild boars might play a role in the epidemiology of porcine circovirus 2 and porcine circovirus 3 in South Korea. Continuous surveillance and further study are needed for this emerging disease.

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Surveillance of ASF-infected pig farms from September to October 2019 in South Korea

Cited by 9 publications

References 8 publications

Arthropods as potential vectors of African swine fever virus outbreaks in pig farms in the Republic of Korea

Arthropods as potential vectors of African swine fever virus outbreaks in pig farms in the Republic of Korea

Object detection and tracking using a high-performance artificial intelligence-based 3D depth camera: towards early detection of African swine fever

Prevalence of porcine circovirus type 2 and type 3 in slaughtered pigs and wild boars in Korea

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