• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.60-74
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• 2017

To facilitate prevention of highly pathogenic avian influenza (HPAI), a GIS is widely used for monitoring, investigating epidemics, managing HPAI-infected farms, and eradicating the disease. After the outbreak of foot-and-mouth disease in 2010 and 2011, the government of the Republic of Korea (ROK) established the GIS-based Korean Animal Health Integrated System (KAHIS) to avert livestock epidemics, including HPAI. However, the KAHIS is not sufficient for controlling HPAI outbreaks due to lack of responsibility in fieldwork, such as sterilization of HPAI-infected poultry farms and regions, control of infected animal movement, and implementation of an eradication strategy. An outbreak prediction model to support efficient HPAI control in the ROK is proposed here, constructed via analysis of HPAI outbreak patterns in the ROK. The results show that 82% of HPAI outbreaks occurred in Jeolla and Chungcheong Provinces. The density of poultry farms in these regions were $2.2{\pm}1.1/km^2$ and $4.2{\pm}5.6/km^2$, respectively. In addition, reared animal numbers ranged between 6,537 and 24,250 individuals in poultry farms located in HPAI outbreak regions. Following identification of poultry farms in HPAI outbreak regions, an HPAI outbreak prediction model was designed using factors such as the habitat range for migratory birds(HMB), freshwater system characteristics, and local road networks. Using these factors, poultry farms which reared 6,500-25,000 individuals were filtered and compared with number of farms actually affected by HPAI outbreaks in the ROK. The HPAI prediction model shows that 90.0% of the number of poultry farms and 54.8% of the locations of poultry farms overlapped between an actual HPAI outbreak poultry farms reported in 2014 and poultry farms estimated by HPAI outbreak prediction model in the present study. These results clearly show that the HPAI outbreak prediction model is applicable for estimating HPAI outbreak regions in ROK.

• Monthly Duck's Village
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• s.211
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• pp.12-31
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• 2021

2003년 12월 10일 국내 최초로 고병원성조류인플루엔자(HPAI)가 발생된 이후 이 바이러스는 오리업계를 지긋지긋하게 괴롭히고 있다. 갈수록 강력해지고 있으며 피해 규모도 더욱 커지고 있을 뿐만 아니라 오리산업을 위협하는 가장 강력한 변수로 자리 잡고 있을 정도로 20여년에 가까운 시간 동안 HPAI와의 전쟁을 벌이고 있다. 특히 HPAI는 인수공통전염병으로 이종간 변이 바이러스를 통해 사람으로의 전파 가능성이 있어 세계는 물론 우리나라도 HPAI 종식을 위해 노력하고 있다. 그럼에도 불구하고 철새는 감염되더라도 무증상인 경우가 있어 주요 전파 요인인 철새에 대한 근본적인 대책이 나오지 않는 이상 완전히 박멸하기란 사실상 불가능하기 때문에 철새를 통한 유입을 막는 것이 최선일 것이다. 우리나라에서 그 동안 발생한 HPAI의 경우 인근 발생국으로부터 축산물 등을 통해 유입될 가능성이 제기되기도 했지만 철새를 통한 전파가 가장 유력한 원인으로 지적되고 있다. 올해도 2020년 11월 부터 시작된 HPAI가 오리업계를 괴롭히고 있다. 이에 그 동안 HPAI 발생 현황과 오리산업에 미친 영향 등을 살펴봤다.

• Journal of Veterinary Clinics
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• v.34 no.2
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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.

• Journal of Veterinary Clinics
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• v.36 no.1
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.114-126
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• 2016

Domestic risk factors that are thought to be correlated with highly pathogenic avian influenza (HPAI) outbreak are migratory birds and moving objects such as poultry farm vehicles. In particular, the commercial vehicles that routinely circulate the local and/or remote poultry farms produce are thought to be major HPAI risk factors in South Korea. In this study, the driving histories of the vehicles belonging to poultry farms and/or commercial companies registered in the Korea Animal Integrated System (KAHIS) were analyzed using statistical and social networking tools in a Geographic Information System (GIS) in order to understand the pattern of the HPAI (H5N8) outbreak that occurred in 2014 in South Korea. Based on the 2014 HPAI outbreak patterns, HPAI-infected poultry farms were categorized according to geological features. The HPAI-infected poultry farms were categorized as 'regional-accumulation', 'regional-distribution', 'metropolitan-accumulation', 'metropolitan-distribution' and 'national-distribution' in endemic or non-endemic regions. We were able to categorize most HPAI-infected poultry farms into the five proposed categories, but further studies are required to categorize all such farms. Based on this categorization system, we propose efficient but economical prevention boundaries in South Korea. We strongly believe that our research could hugely impact government decisions to estimate the prevention area.

• The Journal of Bigdata
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• v.5 no.2
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• pp.69-76
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• 2020

This study was conducted with the support of the Information and Communication Technology Promotion Center, funded by the government (Ministry of Science and ICT) in 2019. Highly pathogenic avian influenza (HPAI) is an acute infectious disease of birds caused by highly pathogenic avian influenza virus infection, causing serious damage to poultry such as chickens and ducks. High pathogenic avian influenza (HPAI) is caused by focusing on winter rather than year-round, and sometimes does not occur at all during a certain period of time. Due to these characteristics of HPAI, there is a problem that does not accumulate enough actual data. In this paper study, GAN network was utilized to generate actual similar data containing missing values and the process is introduced. The results of this study can be used to measure risk by generating realistic simulation data for certain times when HPAI did not occur.

• 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.

• Journal of Veterinary Clinics
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• v.36 no.1
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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.

• Journal of Korean Society of Rural Planning
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• v.18 no.4
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• pp.79-89
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• 2012

농가를 방문하는 가금관련업체의 관계자 및 차량은 HPAI 질병 확산의 매개체가 된다. 농가들의 가금관련업체 이용 정보를 이용하면 농가간의 연결을 확인할 수 있고 HPAI 확산 가중 네트워크를 구성할 수 있다. 네트워크 분석중 중심성 측정은 질병에 취약하거나 타 농가에 영향력이 큰 역할을 하는 농가를 분석하는 방법으로 HPAI 초기 확산을 통제하는 방법으로 이용된다. 단, HPAI 바이러스는 네트워크의 연결선 가중치에 따라서 확산 경로가 달라질 수 있다. 기존의 분석 방법은 확산 경로에 있어 대치되는 연결선의 강도와 연결선의 수 중 하나만을 고려하기 때문에 질병 확산을 정확히 모의하는데 한계가 있다. 그래서 본 연구에서는 2008년 발병한 한국 김제 지역의 39개 농가를 대상으로 가금관련업체 이용자료를 적용한 HPAI 확산 네트워크에 연결선의 가중치에 지수를 적용하는 방법으로 기존의 방법과 결과를 비교했다. 이 자료는 가금 산업 네트워크의 한국 지역 농가 적용성을 평가 할 수 있을뿐만 아니라 추후 잠재적인 질병 발병 차단을 위한 정보 제공에 중요한 역할을 할 것이다.

• Journal of the korean veterinary medical association
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• v.44 no.11
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• pp.1025-1033
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• 2008

이번 고병원성조류인플루엔자(이하 HPAI로 기술)는 2008년 4월 1일 우리 전라북도 김제시 용지면 산란계 밀집 사육지역에서 시작하여 5월 12일 경북 경산시 토종닭 농장을 끝으로 11개 시 도 19개 시 군 구에서 총 33건이 발생되어 2,6410억원의 경제적 피해가 발생하였다. 우리 전라북도는 최초 발생농가를 포함 4개 시 군(익산, 정읍, 김제, 순창)에서 17건(닭13, 오리 4)이 발생하여 전국에서 HPAI발생이 가장 많았던 도로 남는 불명예를 안게 되었다. 이에 막대한 경제적 피해가 다시 발생하지 않도록 HPAI의 현장 방역에 대해 나름대로 경험한 것과 느꼈던 것들을 사례별로 기술하고자 한다.