• 한국빅데이터학회지
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• 제5권2호
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• pp.69-76
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• 2020

이 연구는 2019년도 정부(과학기술정보통신부)의 재원으로 정보통신기술진흥센터의 지원을 받아 수행된 연구이다. 고병원성조류인플루엔자(Highly Pathogenic Avian Influenza, HPAI)는 병원성이 높은 조류인플루엔자 바이러스 감염에 의하여 발생하는 조류의 급성 전염병으로 닭, 오리 등 가금류에서 피해가 심각하게 나타난다. 고병원성 조류인플루엔자(HPAI)는 연중으로 발생하기보다는 겨울철에 집중하여 발생되는 양상을 보이며, 특정 기간에는 아예 발생하지 않는 경우가 있다. 이와 같은 HPAI의 특성으로 인해 충분한 양의 실제 데이터가 축적되지 못하는 문제점이 있다. 본 논문 연구에서는 GAN 네트워크를 활용하여 결측치를 포함하고 있는 실제와 유사한 데이터를 생성하였으며 해당 과정을 소개한다. 본 연구 결과는 HPAI가 발생하지 않은 특정 시기에 대하여 실제와 유사한 시뮬레이션 데이터를 생성하여 위험도를 측정하는데 이용될 수 있다.

• 한국농공학회논문집
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• 제53권1호
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• pp.29-36
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• 2011

HPAI (High pathogenic avian influenza) which is a disease legally designated as an epidemic generally shows rapid spread of disease resulting in high mortality rate as well as severe economic damages. Because Korea is contiguous with China and southeast Asia where HPAI have occurred frequently, there is a high risk for HPAI outbreak. A prompt treatment against epidemics is most important for prevention of disease spread. The spread of HPAI should be considered by both direct and indirect contact as well as various spread factors including airborne spread. There are high risk of rapid propagation of HPAI flowing through the air because of collective farms mostly in Korea. Field experiments for the mechanism of disease spread have limitations such as unstable weather condition and difficulties in maintaining experimental conditions. In this study, therefore, computational fluid dynamics which has been actively used for mass transfer modeling were adapted. Korea has complex terrains and many livestock farms are located in the mountain regions. GIS numerical map was used to estimate spreads of virus attached aerosol by means of designing three dimensional complicated geometry including farm location, road network, related facilities. This can be used as back data in order to take preventive measures against HPAI occurrence and spread.

• 한국농공학회논문집
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• 제53권1호
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• pp.9-15
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• 2011

Highly pathogenic avian influenza could not be identified visually. It takes time to identify the symptoms by its incubation period. Without taking a quick step, the diffusion area of HPAI has dramatically increased, the extent of damage becomes bigger. In network research, the algorithm of finding the central node on the network applied to various diffusion of epidemic problems, was used in control system of tracing the diffusion path, blocking central nodes. This study tried to make the diffusion of HPAI network model for the crowded farms area, and reduce the diffusion rate to control the high-risk farms.

• Journal of Animal Science and Technology
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• 제65권4호
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• pp.838-855
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• 2023

The highly pathogenic avian influenza (HPAI) virus triggers infectious diseases, resulting in pulmonary damage and high mortality in domestic poultry worldwide. This study aimed to analyze miRNA expression profiles after infection with the HPAI H5N1 virus in resistant and susceptible lines of Ri chickens.For this purpose, resistant and susceptible lines of Vietnamese Ri chicken were used based on the A/G allele of Mx and BF2 genes. These genes are responsible for innate antiviral activity and were selected to determine differentially expressed (DE) miRNAs in HPAI-infected chicken lines using small RNA sequencing. A total of 44 miRNAs were DE after 3 days of infection with the H5N1 virus. Computational program analysis indicated the candidate target genes for DE miRNAs to possess significant functions related to cytokines, chemokines, MAPK signaling pathway, ErBb signaling pathway, and Wnt signaling pathway. Several DE miRNA-mRNA matches were suggested to play crucial roles in mediating immune functions against viral evasion. These results revealed the potential regulatory roles of miRNAs in the immune response of the two Ri chicken lines against HPAI H5N1 virus infection in the lungs.

• 한국임상수의학회지
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• 제34권2호
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• pp.146-151
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• 2017

Six major outbreaks of highly pathogenic avian influenza (HPAI) occurred from 2003 to 2016 in Korea. Epidemiological investigations of each outbreak revealed that migratory birds were the primary source of the HPAI virus. During the last five years, the geographic transmission pattern of domestic HPAI seems to have extended from local to nationwide; therefore, it is necessary to identify specific locations in which poultry farms are at elevated risk for HPAI outbreak to enable targeted surveillance and other mitigation strategies. Here, a geographical information system (GIS)-based analysis was used to identify geographic areas at high risk for future HPAI incidents in Korea based on historical outbreak data collected between December 2003 and April 2016. To accomplish this, seven criteria were used to identify areas at high-risk for HPAI occurrence. The first three criteria were based on defined spatial criteria buffering of 200 bird migration sites to some defined extents and the historical incidence of HPAI outbreaks at the buffering sites. The remaining criteria were based on combined attribute information such as number of birds or farms at district levels. Based on the criteria established for this study, the most-likely areas at higher risk for HPAI outbreak were located in Chungcheong, Jeolla, Gyeonggi, and Gyeongnam provinces, which are densely populated poultry regions considered major poultry-production areas that are located along bird migration sites. The proportion of areas at risk for HPAI occurrence ranged from 4.5% to 64.9%. For the worst criteria, all nine provinces, including Jeju Island, were found to be at risk of HPAI. The results of this study indicate that the number of poultry farms at risk for HPAI outbreaks is largely underestimated by current regulatory risk assessment procedures conducted for biosecurity authorization. The HPAI risk map generated in this study will enable easy use of information by policy makers to identify surveillance zones and employ targeted surveillance to reduce the impact of HPAI transmission.

• 한국임상수의학회지
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• 제36권1호
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• pp.15-22
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• 2019

Highly pathogenic avian influenza (HPAI) is among the top infectious disease priorities in Korea and the leading cause of economic loss in relevant poultry industry. An understanding of the spatial epidemiology of HPAI outbreak is essential in assessing and managing the risk of the infection. Though previous studies have reported the majority of outbreaks occurred clustered in what are preferred to as densely populated poultry regions, especially in southwest coast of Korea, little is known about the spatial distribution of risk areas vulnerable to HPAI occurrence based on geographic information system (GIS). The main aim of the present study was to develop a GIS-based risk index model for defining potential high-risk areas of HPAI outbreaks and to explore spatial distribution in relative risk index for each 252 Si-Gun-Gu (administrative unit) in Korea. The risk index was derived incorporating seven GIS database associated with risk factors of HPAI in a standardized five-score scale. Scale 1 and 5 for each database represent the lowest and the highest risk of HPAI respectively. Our model showed that Jeollabuk-do, Chungcheongnam-do, Jeollanam-do and Chungcheongbuk-do regions will have the highest relative risk from HPAI. Areas with risk index value over 4.0 were Naju, Jeongeup, Anseong, Cheonan, Kochang, Iksan, Kyeongju and Kimje, indicating that Korea is at risk of HPAI introduction. Management and control of HPAI becomes difficult once the virus are established in domestic poultry populations; therefore, early detection and development of nationwide monitoring system through targeted surveillance of high-risk spots are priorities for preventing the future outbreaks.

• 한국임상수의학회지
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• 제36권1호
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• pp.23-29
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• 2019

While research findings suggest that the highly pathogenic avian influenza (HPAI) is the leading cause of economic loss in Korean poultry industry with an estimated cumulative impact of $909 million since 2003, identifying the environmental and anthropogenic risk factors involved remains a challenge. The objective of this study was to identify areas at high risk for potential HPAI outbreaks according to the likelihood of HPAI virus detection in wild birds. This study integrates spatial information regarding HPAI surveillance with relevant demographic and environmental factors collected between 2003 and 2018. The Maximum Entropy (Maxent) species distribution modeling with presence-only data was used to model the spatial risk of HPAI virus. We used historical data on HPAI occurrence in wild birds during the period 2003-2018, collected by the National Quarantine Inspection Agency of Korea. The database contains a total of 1,065 HPAI cases (farms) tied to 168 unique locations for wild birds. Among the environmental variables, the most effective predictors of the potential distribution of HPAI in wild birds were (in order of importance) altitude, number of HPAI outbreaks at farm-level, daily amount of manure processed and number of wild birds migrated into Korea. The area under the receiver operating characteristic curve for the 10 Maxent replicate runs of the model with twelve variables was 0.855 with a standard deviation of 0.012 which indicates that the model performance was excellent. Results revealed that geographic area at risk of HPAI is heterogeneously distributed throughout the country with higher likelihood in the west and coastal areas. The results may help biosecurity authority to design risk-based surveillance and implementation of control interventions optimized for the areas at highest risk of HPAI outbreak potentials.

• 한국환경농학회:학술대회논문집
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• 한국환경농학회 2009년도 정기총회 및 국제심포지엄
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• pp.220-227
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• 2009

For last about 10 years, the Republic of Korea experienced 3 times of outbreaks of highly pathogenic avian influenza (HPAI) from 10 December 2003 to 30 April 2004 (a total number of 19 outbreaks), 22 November 2006 to 6 March 2007 (a total number of 7 outbreaks), and 1 April 2008 to 12 May 2008 (a total number of 33 outbreaks). Among the totally 59 outbreaks, the infected premises included 35 chicken farms, 17 duck farms, 1 quail farm, and 6 farms rearing mixed species. Control measures were applied according to the HPAI standard operation procedure including depopulation of all infected and suspected flocks, movement restrictions, and disinfection of the infected farms within a 500-meter radius. Including movement restrictions, stringent control measures were additionally applied to two designated zones: the protection zone was an area within a 3-kilometer radius of the outbreak farm, and the surveillance zone was an area between a 3- to 10-kilometer radius of the outbreak farm. Farms with dangerous contacts and/or all of poultry within the protection zone was subjected to preemptive culling. Epidemiological investigations were also carried out including trace-back and trace-forward investigations to identify possible sources of spread and dangerous contact farms. Investigation teams conducted on-site examination of farm premises and facilities, interview with farm owner and staff, and review of records. Genetic and pathogenic characteristics of the virus isolates, and the results of the various surveillance activities were also analyzed. HPAI surveillance conducted in Korea includes passive surveillance of investigating notified cases, and active surveillance of testing high risk groups and areas. HPAI is a notifiable disease in Korea and all suspect cases must be reported to the veterinary authorities. Cases reported for other poultry diseases that require differential diagnosis are also tested for HPAI. Active surveillance includes annual testing of breeder duck farms, broiler duck farms and wild bird surveillance, which is concentrated during the autumn and winter. Surveillance activities conducted prior to the outbreaks have shown no evidence of HPAI infection in Korea.

• 한국가금학회:학술대회논문집
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• 한국가금학회 2004년도 춘계 심포지움
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• pp.5-27
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• 2004

2003년 12월, 우리나라에서의 고병원성 가금인플루엔자(HPAI ： High Pathogenic Avian Influenza) 발생과 미국에서의 소해면상뇌증(BSE : Bovine Spongiform Encephalopathy) 발생이 매스컴을 통해 여과없이 발표되기 시작되자 닭고기와 쇠고기의 소비가 급격하게 줄어. 축산 생산기반마저 위협을 받는 위기에 처한 바가 있었다. (중략)

• 한국임상수의학회지
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• 제36권1호
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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.