• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.275-277
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• 2017

본 논문에서는 GIS를 이용하여 국내 고병원성 조류인플루엔자(HPAI) 발생 농가를 대상으로 HPAI 감염 및 확산에 영향을 미치는 여러 인자와의 연관성을 분석한다. 인자는 크게 철새에 기인한 1차 감염과 사람에 기인한 2차 감염으로 나눈다. 전자는 철새 이동경로, 철새 도래지, 후자는 고속도로, HPAI 발생 농가 간 거리를 분석한다. 분석 시 거리는 500m(관리지역), 3km(보호지역), 10km(예찰지역)으로 설정하고, ArcGIS 프로그램을 사용하였다.

• The Journal of Bigdata
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• v.5 no.1
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• pp.1-9
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• 2020

The study was conducted with funding from the government (Ministry of Agriculture, Food and Rural Affairs) in 2018 with support from the Agricultural, Food, and Rural Affairs Agency, 318069-03-HD040, and in based on artificial intelligence-based HPAI spread analysis and patterning. The model that is actively used in time series and text mining recently is LSTM (Long Short-Term Memory Models) model utilizing deep learning model structure. The LSTM model is a model that emerged to resolve the Long-Term Dependency Problem that occurs during the Backpropagation Through Time (BPTT) process of RNN. LSTM models have resolved the problem of forecasting very well using variable sequence data, and are still widely used.In this paper study, we used the data of the Call Detailed Record (CDR) provided by KT to identify the migration path of people who are expected to be closely related to the virus. Introduce the results of predicting the path of movement by learning the LSTM model using the path of the person concerned. The results of this study could be used to predict the route of HPAI propagation and to select routes or areas to focus on quarantine and to reduce HPAI spread.

• Korean Journal of Poultry Science
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• v.46 no.4
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• pp.313-325
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• 2019

In most cases of HPAI (highly pathogenic avian influenza) outbreaks, stamping-out operations are initiated by officially designating the affected premise, which is subsequently followed by depopulation of infected flocks. The primary objective of this study was to develop an evaluation method that correlates the level of biosecurity and the risk of having an HPAI outbreak in domestic poultry farms. A total of eight farms were selected nationwide, including layer farms, broiler farms, and an animal welfare type farm. The biosecurity level of the chosen poultry farms was assessed based on a total scoring index of 183 divided into three categories, general management (51), quarantine management (106), and sanitation management (26). Conclusively, the five layer farms (JS, GE, CS, HS, OE), scored higher overall scores compared to the animal welfare farm (CH) and broiler farms (JG, LB). In terms of scoring, which adds up to a total of 183 points, most layer farms scored between 130 and 157, while the two broiler farms and the welfare farm scored 45, 75 and 70, respectively. Next, an independent HPAI risk assessment of the farms was carried out. Regarding the correlation between biosecurity levels and HPAI risks, in the farms that presented a higher overall score in terms of biosecurity and outweighed the risks of HPAI, they tended to earn more points in the quarantine management category. The results of this study suggest that a viable system for evaluating biosecurity levels can establish strong correlations with the risk of having HPAI.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Korean Journal of Poultry Science
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• v.46 no.3
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• pp.173-183
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• 2019

Based on their virulence, the avian influenza viruses (AIVs) are classified into two pathotypes: low pathogenic avian influenza (LPAI) virus and highly pathogenic avian influenza (HPAI) virus. Among the 16 HA subtypes of AIV, only the H5 and H7 subtypes are classified as HPAI. Some AIVs, including H5 and H7 viruses, can infect humans directly. Six H7 subtype isolates from wild birds of the H7N7 (n=4) and H7N1 (n=2) subtypes were characterized in this study. Phylogenetic analysis showed that eight viral genes (HA, NA, PB2, PB1, PA, NP, M, and NS) of the H7 isolates clustered in the Eurasian lineage, the genetic diversity of which is indicated by its division into several sublineages. The Korean H7 isolates had two motifs, PEIPKGR and PELPKGR, at the HA cleavage site, which have been associated with LPAI viruses. Six H7 isolates encoded glutamine (Q) and glycine (G) at positions 226 (H3 numbering) and 228 of HA, suggesting avian-type receptor-binding specificity. None of the Korean H7 isolates had the amino acid substitutions E627K in PB2 and I368V in PB1, which are critical for efficient replication in human cells. The Korean H7 isolates showed no deletions in the NA stalk region and in NS. These results suggest that the Korean H7 isolates from wild birds are different from the H7N9 influenza viruses isolated in China in 2013, which are capable of infecting humans.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.89-101
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• 2015

Outbreaks of highly pathogenic avian influenza(HPAI) subtype H5N8 have occurred in Korea, January 2014 and it continued more than a year until 2015. And more than 5 million heads of poultry hads been damaged in 196 farms until May 2014. So, we studied the spatial, temporal and spatio-temporal patterns of the HPAI epidemics for understanding the propagation and diffusion characteristics of the 2014 HPAI. The results are expressed using GIS. Throughout the study period three epidemic waves occurred over the time. And outbreaks made three clusters in space. First spatial cluster is adjacent areas of province of Chungcheongbuk-do, Chungcheongnam-do and Gyeonggi -do. Second is Jeonlabuk-do Gomso Bay area. And the last is Naju and Yeongam in Jeollanam-do. Also, most of spatio-temporal clusters were formed in spatially high clustered areas. Especially, in Gomso Bay area space density and spatio-temporal density were concurrent. It means that the effective prevention activity for HPAI was carried out. But there are some exceptional areas such as Chungcheongbuk-do, Chungcheongnam-do, Gyeonggi-do adjacent area. In these areas the outbreak density was high in space but the spatio-temporal cluster was not formed. It means that the HPAI virus was continuing inflow over a long period.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.186-198
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• 2016

HPAI(Highly Pathogenic Avian Influenza) is a contagious animal disease that spreads rapidly by diffusion after the first occurrence. The disease has brought tremendous social costs and economic losses. KAHIS (Korea Animal Health Information System) is the integrated system for supporting the task of preventing epidemics. They provide decision-support information, recording vehicle visiting times and facility location, etc., which is possible by enforcing registration of all livestock related facilities and vehicles. KAHIS has accumulated spatial and temporal information that enables effective tracing of potential disease trajectories and diffusion through vehicle movements. The contact network is created utilizing spatial and temporal information in KAHIS to inform facility connection via vehicle visitation. Based on the contact network, it is possible to infer spatial and temporal mechanism of disease spread and diffusion. The study objective is to empirically demonstrate how to utilize primary spatial and temporal information in KAHIS in the form of the contact network. Based on the contact network, facilities with the possibility of infection can be pinpointed within the potential spatial and temporal extent where the disease has spread and diffused. This aids the decision-making process in the task of preventing epidemics. By interpreting our demonstration results, policy implications were presented. Finally, some suggestions were made to comprehensively utilize the contact network to draw enhanced decision-support information.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.140-155
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• 2020

This study was conducted to identify the location characteristics of infected farms in the areas where livestock diseases were clustered(southern Gyeonggi-do and Chungcheong-do), analyze the probability of disease occurrence in poultry farms, find out the areas corresponding to the conditions, and use them as the basis for prevention of livestock diseases, selection of discriminatory prevention zones, and establishment of prevention strategies and as the basic data for complementary measures. The increase of one poultry farm within a radius of 3-kilometers increases the risk of HPAI infection by 10.9% compared to the previous situation. The increase of 1m in distance from major roads with two lanes or more reduces the probability of HPAI infection by 0.001% compared to the previous situation. If the distance of the poultry farm located with 15 kilometers from a major migratory bird habitat increases by 15 to 30 kilometers, the chance of infection with HPAI is reduced by 46.0%. And if the distance of the same poultry farm increase by more than 30 kilometers, the chances of HPAI infection are reduced by 88.5%. Based on the results of logistic regression, the predicted probability was generated and the actual area of the location condition with 'more than 15 poultry farms within 3km a radius of, within 1km distance from major roads, and within 30km distance from major migratory birds habitat was determined and the infection rate was measured. It is expected that the results of this study will be used as basic data for preparing the data and supplementary measures when the quarantine authorities establish discriminatory quarantine areas and prevention strategies, such as preventive measures for the target areas and farms, or control of vehicles, by identifying the areas where livestock diseases are likely to occur in the region.

• Journal of Microbiology and Biotechnology
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• v.24 no.5
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• pp.704-713
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• 2014

The highly pathogenic avian influenza A (HPAI) viruses of the H5N1 subtype infect poultry and have also been spreading to humans. Although new antiviral drugs and vaccinations can be effective, rapid detection would be more efficient to control the outbreak of infections. In this study, a phage-display library was applied to select antibody fragments for HPAI strain A/Hubei/1/2010. As a result, three clones were selected and sequenced. A hemagglutinin inhibition assay of the three scFvs revealed that none exhibited hemagglutination inhibition activity towards the H5N1 virus, yet they showed a higher binding affinity for several HPAI H5N1 strains compared with other influenza viruses. An ELISA confirmed that the HA protein was the target of the scFvs, and the results of a protein structure simulation showed that all the selected scFvs bound to the HA2 subunit of the HA protein. In conclusion, the three selected scFVs could be useful for developing a specific detection tool for the surveillance of HPAI epidemic strains.

• Journal of Veterinary Science
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• v.25 no.2
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• pp.20.1-20.15
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• 2024

Background: Avian influenza (AI) is a contagious disease that causes illness and death in poultry and humans. High pathogenicity AI (HPAI) H5N6 outbreaks commonly occur in Quang Ninh province bordering China. In June 2021, the first HPAI H5N8 outbreak occurred at a Quang Ninh chicken farm. Objectives: This study examined the risk factors associated with HPAI H5N6 and H5N8 outbreaks in Quang Ninh. Methods: A retrospective case-control study was conducted in Quang Ninh from Nov 2021 to Jan 2022. The cases were households with susceptible poultry with two or more clinical signs and tested positive by real-time reverse transcription polymerase chain reaction. The controls were households in the same village as the cases but did not show clinical symptoms of the disease. Logistic regression models were constructed to assess the risk factors associated with HPAI outbreaks at the household level. Results: There were 38 cases with H5N6 clade 2.3.4.4h viruses (n = 35) and H5N8 clade 2.3.4.4b viruses (n = 3). Compared to the 112 controls, raising poultry in uncovered or partially covered ponds (odds ratio [OR], 7.52; 95% confidence interval [CI], 1.44-39.27), poultry traders visiting the farm (OR, 8.66; 95% CI, 2.7-27.69), farms with 50-2,000 birds (OR, 3.00; 95% CI, 1.06-8-51), and farms with ≥ 2,000 birds (OR, 11.35; 95% CI, 3.07-41.94) were significantly associated with HPAI outbreaks. Conclusions: Combining biosecurity measures, such as restricting visitor entry and vaccination in farms with more than 50 birds, can enhance the control and prevention of HPAI in Quang Ninh and its spread across borders.