Since the first HPAI epidemics in 2003, there has been little epidemiological research on the association between HPAI epidemics and vehicle movements around poultry farms. This study examined the relationship between vehicle movements around poultry farms and the 2014/15 HPAI epidemics in the Republic of Korea using two methods: a boosted regression trees (BRT) model and logistic regression of a generalized linear model (GLM). The BRT model considers the non-linearity association between the frequency of vehicle movements around poultry farms and the HPAI outbreak status per province using a machine learning technique. In contrast, a GLM assesses the relationship based on the traditional frequentist method. Among the three types of vehicle movements (outbound, inbound, and within), only the outbound was found to be a risk factor of the 2014/15 HPAI epidemics according to both the BRT model and multivariate logistic regression of GLM. In the BRT model results, the median relative contribution of the log-transformed outbound variable was 53.68 (range: 39.99 – 67.58) in the 2014 epidemics and 49.79 (range: 33.90 – 56.38) in the 2015 epidemics. In the GLM results, the odds ratio of the log-transformed outbound variable was 1.22 for the 2014 HPAI epidemics (p < 0.001) and 2.48 for the 2015 HPAI epidemics (p < 0.001), respectively. The results indicated that intensive disinfection measures on outbound movement were needed to reduce the risk of HPAI spread. The current BRT models are suitable for risk analysis because the median area under the receiver operating characteristic curve was 0.83 (range: 0.74 – 0.91) and 0.85 (range: 0.73 – 0.87) for the 2014 and 2015 epidemics models, respectively. The Akaike information criterion scores for the multivariate logistic regression of GLM were 150.27 and 78.21 for the 2014 and 2015 epidemics models, respectively. These scores were relatively lower than those from the univariate logistic regression of GLM.

The goal of the current study was to estimate the contribution of poultry farm vehicle movement frequency to the 2014 highly pathogenic avian influenza (HPAI) epidemic using both global and local regression models. On one hand, the global model did not consider the hypothesis that a relationship between predictors and the outcome variable might vary across the country (spatially homogeneous), while on the other hand, the local model considered that there was spatial heterogeneity within the country. The HPAI outbreak status in each province was used as a dependent variable and the number of poultry farm vehicle movements within each province (within variable), the number of poultry farm vehicle movement from one province to another province (outbound variable), the number of poultry farm vehicle movements from other provinces to one province (inbound variable), and the number of poultry farms in each province were included in the model as independent variables. The results of a global model were as follows: estimated coefficient of the log-transformed within variable was 0.73, that of the log-transformed outbound variable was 2.04, that of the log-transformed inbound variable was 0.74, and that of the number of poultry farms was 1.08. Only the number of poultry farms was a statistically significant variable (p-value < 0.001). The AIC score of the global model was 1397.5. The results of the local model were as follows: estimated median coefficient of the log-transformed within variable was 0.75, that of the log-transformed outbound variable was 2.54, that of the log-transformed inbound variable was 0.60, and that of the number of poultry farms was 0.07. The local model’s AIC score was 1382.2. The results of our study indicate that a local model would provide a better understanding of the relationship between HPAI outbreak status and poultry farm vehicle movements than that provided by a global model.

본 연구는 안전한 육계 및 계란 생산에 기반이 되는 닭 농장의 HACCP 심사의 객관성을 높이기 위하여 현행 심사항목 점수부여 체계의 문제점에 대한 개선방안을 도출하기 위한 목적으로 실시하였다. 기존 닭 농장 HACCP심사항목은 중요도 수준의 구분 없이 동일한 점수(5점)를 부여하고 있으나 본 연구에서는 최근 3년간 지적비율, 위해의 심각도 수준 등 을 고려하여 심사항목별로 중요도 수준을 도출하였고 그 결과에 따라 심사항목의 점수를 차등 부여하도록 하였다. 닭 농장의 선행요건 분야 심사항목(60개)은 중요도에 따라 최대 5 점에서 최소 2점의 점수체계를 구축하여 총 점수가 200점이 되도록 하였으며, HACCP 관 리 분야 심사항목(15개)은 최대 10점에서 최소 5점 체계를 구축하여 총 점수가 100점이 되 도록 개발하였다. 본 연구결과를 현장에 적용할 경우 심사의 객관성을 높여 더욱 안전하고 위생적인 육계 및 계란 생산이 가능할 것으로 예상된다. 이는 나아가 닭 농장 HACCP 제도 의 활성화와 소비자에게 보다 안전한 축산물을 공급할 수 있을 것으로 판단된다.