Cocker spaniel 견에서 발생한 전신성 아밀로이드증

박선일 ( Son Il Park ),김두 ( Doo Kim ),한정희 ( Jeong Hee Han ) 한국임상수의학회 2006 한국임상수의학회지 Vol.23 No.2

가축질병 방역활동 지원을 위한 국가동물방역통합시스템 시공간 정보 활용

박선일 ( Son-il Park ),박홍식 ( Hong-sik Park ),정우석 ( Woo-seog Jeong ),이경주 ( Gyoung-ju Lee ) 한국지리정보학회 2016 한국지리정보학회지 Vol.19 No.4

고병원성 조류인플루엔자(Highly Pathogenic Avian Influenza: HPAI)는 전염력이 매우 높아 발병 시 전국적으로 확산되어 막대한 사회경제적 피해를 유발하는 제1종 법정가축전염병이다. 국가동물방역통합시스템(Korea Animal Health Integrated System: KAHIS)은 축산차량등록제를 통하여 축산관련차량의 축산관련시설 출입정보를 실시간으로 기록함으로써 가축질병 발생 시 신속한 방역업무를 지원하기 위하여 구축한 통합시스템이다. KAHIS는 가축질병 발생 시 차량이동에 의한 확산경로를 효과적으로 추적하기 위한 시공간 정보를 포함한다. 이러한 시공간 정보를 바탕으로 시설들 간 연결 관계를 나타내는 접촉 네트워크를 구축할 경우 가축질병의 시공간 확산과정추론에 유용하게 활용할 수 있다. 본 연구의 목적은 가축질병 방역활동 지원을 위하여 KAHIS에 내재된 시공간 정보를 접촉 네트워크로 구축하여 일차적 활용방안을 실증적으로 제시하는 것이다. 구축한 접촉 네트워크를 토대로 가축질병의 확산이 이루어지는 잠재적 시공간적 권역을 추정함으로써 차단·방역 관련 의사결정을 돕기 위한 분석정보를 도출하고 해석을 통하여 정책적 함의를 제시하였다. 아울러 좀 더 고도화된 의사결정 지원정보 도출을 위한 접촉 네트워크의 심층적 활용방안을 제시하였다. 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.

국내 고속도로 로드킬 발생의 공간적 군집지역 탐색 방법론 구축 및 실증 적용 연구

박선일(Park, Son-Il),이경주(Lee, Gyoung-Ju) 대한국토·도시계획학회 2015 國土計劃 Vol.50 No.3

산란계의 전염성 기관지염을 예측하기 위한 인공신경망 모형의 개발

박선일 ( Son Il Park ),권혁무 ( Hyuk Moo Kwon ) 한국임상수의학회 2006 한국임상수의학회지 Vol.23 No.2

추백리-가금티푸스의 혈청학적 모니터링 계획수립을 위한 표본크기

박선일,박최규,Pak, Son-Il,Park, Choi-Kyu 대한수의학회 2008 大韓獸醫學會誌 Vol.48 No.4

The objective of this study was to determine appropriate sample size that simulated different assumptions for diagnostic test characteristics and true prevalences when designing serological surveillance plan for pullorum disease and fowl typhoid in domestic poultry production. The number of flocks and total number of chickens to be sampled was obtained to provide 95% confidence of detecting at least one infected flock, taking imperfect diagnostic tests into account. Due to lack of reliable data, within infected flock prevalence (WFP) was assumed to follow minimum 1%, most likely 5% and maximum 9% and true flock prevalence of 0.1%, 0.5% and 1% in order. Sensitivity were modeled using the Pert distribution: minimum 75%, most likely 80% and maximum 90% for plate agglutination test and 80%, 85%, and 90% for ELISA test. Similarly, the specificity was modeled 85%, 90%, 95% for plate agglutination test and 90%, 95%, 99% for ELISA test. In accordance with the current regulation, flock-level test characteristics calculated assuming that 30 samples are taken from per flock. The model showed that the current 112,000 annual number of testing plan which is based on random selection of flocks is far beyond the sample size estimated in this study. The sample size was further reduced with increased sensitivity and specificity of the test and decreased WFP. The effect of increasing samples per flock on total sample size to be sampled and optimal combination of sensitivity and specificity of the test for the purpose of the surveillance is discussed regarding cost.

부분예산분석을 이용한 오제스키병 발생 농가의 경제적 손실 추정

박선일,박최규,문운경,윤하정,이병용,이상진,Pak, Son-Il,Park, Choi-Kyu,Moon, Oun-Kyong,Yoon, Hachung,Lee, Byeong-Yong,Lee, Sang-Jin 대한수의학회 2009 大韓獸醫學會誌 Vol.49 No.4

Aujeszky's disease (AD) is a respiratory, infectious viral illness associated with high mortality, especially in neonatal piglets and has frequently been considered an economically important disease in many endemic countries. Although AD is still occurring in a geographically defined region in Korea, little attention has been paid to the economics of AD. In this study, partial budget technique was used to develop a simulation model to measure financial losses following the disease epidemic in a swine operation utilizing stochastic or deterministic parameters from the literatures and the index case herd of AD occurred in 2005, where available and applicable. For the infected case herd with a 12500-pig, the total economic loss for this operation was estimated to be about 199 million Korean won (95% confidence interval [CI] 148,645,000-250,741,000). Given net loss due to death of a pig at sow level was 119,000 won, total loss for the case herd with 1200 sows accounted for 143 million won (95% CI 92,599,000-193,729,000). The net loss of the death of one pig at growing and fattening level resulted in loss of 46,000 won (95% CI 40,000-53,000) and 126,000 won (95% CI 122,000-131,000), respectively. Taking into account for the number of pigs raised in the case herd, total loss amounted to 8 million won (95% CI 7,167,000-9,347,000) and 12 million won (95% CI 11,959,000-12,891,000), for growers and fatteners, respectively, assuming 63% of saved feed intake when a pig dies halfway through the respective period. Under the model's assumptions, suckling pig mortality was the major factors of loss in estimating the economic consequences (approximately 71.8% of the total loss). The high economic losses of a herd infected with AD suggest that the effective and region-specific control measures should be implemented in disease endemic foci.

확률모형을 이용한 오제스키병 혈청학적 모니터링 프로그램 평가

장기윤,박선일,박최규,이경기,주이석,Chang, Ki-Yoon,Pak, Son-Il,Park, Choi-Kyu,Lee, Kyoung-Ki,Joo, Yi-Seok 대한수의학회 2009 大韓獸醫學會誌 Vol.49 No.2

The objective of this study was to analyze data from the planned national serological monitoring program for Aujeszky's disease (AD) using a simulation model to evaluate probable outcomes expected in the sample derived from the simulated herds at predefined within-herd prevalence and herd prevalence. Additionally, prevalence at animal- and herd-level estimated by the stochastic simulation model based on the distributions of the proportion of infected herds and test-positive animals was compared with those of data from a national serological survey in 2006, in which 106,762 fattening pigs from 5,325 herds were tested for AD using a commercial ELISA kit. A fixed value of 95% was used for test sensitivity, and the specificity was modeled with a minimum, most likely and maximum of 95, 97 and 99%, respectively. The within-herd prevalence and herd prevalence was modeled using Pert and Triang distributions, respectively with a minimum, most likely and maximum point values. In all calculations, population size of 1,000 was used due to lack of representative information. The mean number of infected herds and true test-positives was estimated to be 27 herds (median = 25; 95% percentile 44) and 214 pigs (median = 196; 95% percentile 423), respectively. When testing 20 pigs (mean of 2006 survey) in each herd, there was a 3.3% probability that the potential for false-positive reactions due to less than 100% specificity of the ELISA test would be detected. It was found that the model showed prevalence of 0.21% (99% percentile 0.50%) and 0.5% (99% percentile 0.99%) at animal- and herd-level, respectively. These rates were much similar to data from the 2006 survey (0.62% versus 0.83%). The overall mean herd-level sensitivity of the 2006 survey for fattening pigs was 99.9%, with only a 0.2% probability of failing to detect at least one infected herd.

국내 돼지오제스키병의 혈청학적 감시활동(surveillance)을 위한 표본크기

김으뜸,박선일,박최규,권창희,Kim, Eu-Tteum,Pak, Son-Il,Park, Choi-Kyu,Kweon, Chang-Hee 대한수의학회 2007 大韓獸醫學會誌 Vol.47 No.4

Serological surveillance programs in animal populations are becoming increasingly important to estimate prevalence of a specific disease and subsequently to document disease-free status in a region or a country. For these purposes, the programs need to be based on both theoretical and economical aspects from the designing phase. From Aujeszky's disease (AD)-eradication program point of view, group of animals (aggregates, herds) not individual animal is the more important sampling unit of concern. In this study the authors therefore attempted to compute an appropriate sample size tailored to a current surveillance program against AD, assuming that the goal of this program is either herd-level prevalence estimation or documentation of AD-freedom. For prevalence estimation, assuming a finite population with imperfect sensitivity (Se) and specificity (Sp) of ELISA kit for AD diagnosis, the number of herds present, expected herd prevalence, and desired accuracy for a certain level of confidence, sample size was estimated at herd-level in the first stage and individual animal-level in the second stage. A two-stage sampling design was used to calculate a sample size to indicate AD-freedom. In this instance, the computation was based on the possible detection of a predetermined prevalence at a certain herd-level Se and Sp. This study indicated that the sample size varied with predetermined confidence, tolerance, Se and Sp at herd- and animal-level, and within- and among-herd prevalence. In general, smaller sample size was required to estimate AD prevalence than to document of AD-freedom. Compared to individual-based samples, two-stage sampling strategy requires a larger sample size to show disease-freedom. Statistical considerations including herd-level test characteristics when designing surveillance program also are further discussed.

사회연결망 분석을 통한 축산시설 차량이동 네크워크의 허브시설 도출

이경주(Gyoung-Ju Lee),박선일(Son-Il Park),이광녕(Kwang-Nyeong Lee),김한이(Han-Yee Kim),박진호(Jin-Ho Park),홍성조(Sungjo Hong) 한국산학기술학회 2018 한국산학기술학회논문지 Vol.19 No.6

축산시설 사이의 차량이동은 국내에서 가축전염병 확산의 주요 원인이다. 이 같은 상황에서 본 연구는 축산시설의 차량이동 네트워크에서 주요한 위치를 차지하는 허브시설을 도출하고, 그 특성을 분석하는 것을 목적으로 한다. 이를 위하여 본 연구는 농림축산검역본부의 KAHIS(Korea Animal Health Intergrated System)에서 제공하는 축산시설의 차량 진출입자료를 활용하였다. 허브시설의 도출에는 사회연결망 분석의 대표적인 중심성 지표인 연결정도 중심성과 매개 중심성 지표를 활용하였다. 본 연구의 분석결과를 요약하면 다음과 같다. 첫째, 축산시설의 차량이동 네트워크에는 다른 시설에 비하여 매우 높은 중심성 지표 값을 가지는 소수의 허브 시설이 존재한다. 둘째, 연결정도 중심성 기준의 허브시설은 사료공장, 집유장, 도축장, 도계장, 가축시장이다. 셋째, 매개 중심성 기준의 허브시설은 가축시장, 사료공장, 도축장이다. 넷째. 연결정도 중심성에 기반한 허브시설은 특정지역에 집중되어 입지하고 있으나, 매개 중심성에 따른 허브시설을 상대적으로 고르게 분포하고 있다. 다섯째, 중심성 지표에 따른 허브시설은 시간이 지나도 상당히 안정적으로 유지된다. 본 연구는 축산시설 사이의 차량이동이 가축 전염병 전파의 주요 원인으로 지목되는 상황에서, 방대한 진출입 자료를 활용하여, 허브시설을 도출하였다는 점에서 그 의의가 있다. The purpose of this study was to derive and analyze the hub facilities that occupy major positions in the vehicle movement networks of livestock facilities. For this purpose, this study used the KAHIS data provided by Animal and Plant Quarantine Agency. The hub facilities were derived from the degree centrality & betweenness centrality. The analysis results are summarized as follows. First, in a livestock facility"s vehicle movement network, there are a small number of hub facilities with very high centrality indicator values compared to other facilities. Second, the hub facilities based on the degree centrality are the feed factory, the milk collecting center, slaughterhouse, slaughterhouse for chicken, and livestock markets. Third, the hub facilities based on the betweenness centrality are the livestock markets, the feed factory, and slaughterhouse. Fourth, hub facilities based on the degree centrality are concentrated in a particular area, but the hub facilities based on betweenness centrality are distributed relatively evenly.

차량이동 네트워크에서의 축산시설 연결중심성과 가축 전염병 발생 사이의 관계

이경주(Gyoung-Ju Lee),박선일(Son-Il Pak),이광녕(Kwang-Nyeong Lee),김한이(Han-Yee Kim),박진호(Jin-Ho Park),홍성조(Sungjo Hong) 한국산학기술학회 2018 한국산학기술학회논문지 Vol.19 No.12

주기적으로 발생하는 가축전염병으로 인한 국가적 손실이 매우 크다. 또한 우리나라에서 차량이동이 가축전염병의 주요 원인인 것으로 알려져 있다. 이 같은 상황에서, 본 연구는 축산차량의 이동 네트워크에서 축산시설의 구조적 위치와 전염병의 발생 사이의 관계를 실증분석하였다. 이를 위하여 KAHIS에서 제공하는 축산차량의 시설 진입 데이터를 활용하여 축산차량 이동 네트워크를 구축하였다. 구축된 네트워크에서 시설별로 중심성 지표를 도출하고, 전염병이 발생한 시설과 비발생 시설의 지표 평균을 비교하였다. 분석결과 첫번째 가설인 “전염병 발생시설의 연결정도 중심성은 비발생 시설보다 크다.”는 옳은 것으로 나타났다. 전체시점과 시점별 분석을 실시한 결과 대부분의 자료에서 가축전염병이 발생한 시설의 연결정도 중심성이 비발생 시설에 비하여 통계적으로 크게 나타났다. 두 번째 가설인 “HPAI에서 발생시설과 비발생시설 사이의 연결중심성 차이가 FMD에서의 차이보다 작다.”는 전체시점 자료에서 옳은 것으로 나타났다. 반면에 시점을 나누어서 분석한 결과에서는 뚜렷한 차이를 찾을 수 없었다. 연구의결과에 따른 정책적 시사점은다음과 같다. 첫 번째, 연결정도 중심성에 기반한 시설의 사전 관리가 필요하다. 두 번째, 우제류 농가의 경우 연결중심성에 기반한 관리정책의 도입이 보다 시급하다. The national loss caused by the periodic livestock epidemic is very large. In addition, vehicle movement is the main cause of livestock epidemics in Korea. In this context, this study analyzed the relationship between the degree centrality of livestock facilities and the outbreak of infectious diseases. For this purpose, a livestock vehicle movement network was constructed using the facility entrance data provided by KAHIS. Afterwards, the centrality index was derived for each facility in the vehicle movement network and the mean centrality index of the epidemic and non-epidemic facilities were compared. The analysis results are summarized as follows. First, the degree centrality of epidemic facilities is significantly greater than non-epidemic facilities. As a result of the analysis of the entire period data and the period-based data, in most data, the degree centrality of facilities where livestock infectious diseases occurred was significantly greater than most non-occurrence facilities. Second, in the entire period data, the difference in degree centrality between the epidemic and non-epidemic facilities was smaller for HPAI than for FMD. On the other hand, no significant difference was found in the results of the analysis according to the divided period. The policy implications of the results are as follows. First, proactive management of facilities based on centrality is needed. Second, in the case of cloven-hoofed animal facilities, it is more urgent to introduce a management policy based on the degree centrality.