본 연구는 생물음향 모니터링(Passive Acoustic Monitoring, PAM)을 통해 수집된 종 수준 조류 발성 데이터를 기반으로, Shannon 및 Simpson 지수를 활용한 조류 종다양성 정량 분석 체계를 제안하고, 이를 제주도에서 생태적으로 대비되는 두 보호지역인 동백동산과 1100고지 습지를 대상으로 실증하였다. 자동녹음장치(Song Meter SM4)를 설치하 여 2020년 1년간 매시간 1분씩 수집한 총 17,568개의 음향 자료를 분석하였으며, 청음 및 소노그램 판독을 통해 종을 식별하고, 종별 발성 탐지량()을 기반으로 상대 발성 빈도()를 산출하여 고전 생태학 지수에 적용하였다. 월 단위로 산출된 다양성 지수는 자기상관 함수 분석, 계층적 군집 분석, 변동계수(CV) 계산, 분산분석(ANOVA) 등의 통계 기법을 통해 시계열적 안정성, 계절 군집 전환, 서식지 간 구조 차이를 비교·해석하였다. 분석 결과, 동백동산 은 연중 다양성과 안정성이 유지된 반면, 1100고지 습지는 계절에 따른 다양성 급감과 군집 재편성이 반복되었다. 본 연구는 종 단위 식별을 기반으로 생물음향 자료를 정량 생태학 지표와 직접 연결할 수 있음을 확인하였다. 이를 통해 기존 음향지수 방식에서 나타나는 정보 부족 문제를 보완할 수 있으며, 음향 기반 자료도 종 구성의 변화를 해석하는 데 유용하게 활용될 수 있음을 보여주었다. 제안된 분석 체계는 생태계 변화의 구조적 추적, 보호지역 관리 효과 진단, 기계학습 기반 자동화 등 다양한 분야로 확장될 수 있어, 국내 조류 생물음향 연구의 이론적 기준점으로 기능할 수 있다.

Kimchi is a traditional Korean fermented vegetable food known to contain various bioactive compounds produced during fermentation. In this study, we investigated the antiviral effects of a fermented cabbage Kimchi extract (FCK extract) against avian influenza virus (AIV, H9N2) using chicken embryonic eggs and a murine model. The FCK extract markedly inhibited AIV replication in chicken embryos and significantly reduced viral hemagglutinin titers. In addition, FCK extract suppressed viral neuraminidase activity, an essential enzyme involved in the release of newly formed virus particles. To evaluate its protective efficacy in vivo, the FCK extract was orally administered to 6-week-old BALB/c mice once daily for 15 days, and mice were intranasally challenged with AIV two days after the initiation of administration. Mice treated with the FCK extract exhibited significantly improved survival rates and attenuated clinical symptoms compared with the virus control group and the non-fermented cabbage Kimchi (N-FCK) extract group. Histopathological analysis revealed that lung tissue damage was markedly reduced in the FCK extract -treated mice relative to the control group. These findings suggest that oral administration of fermented cabbage Kimchi extract confers protective effects against AIV infection and that fermentation-derived antiviral components in FCK extract may contribute to this activity.

This study evaluated the virucidal efficacy of a chlorine dioxide (ClO2) gas-generating fumigation disinfectant consisting of sodium chlorate solution (25% sodium chlorate) and reaction solution against avian influenza virus (AIV). After AIV suspensions had been deposited on stainless steel carriers, the 9 dried carriers were exposed to the fumigant (sodium chlorate solution: 8.5, 17, 34, 50, and 100 mL) in a 25-m³ test room for 2, 3, and 4 h, respectively. Thereafter, all carriers were submerged in a neutralizing solution (20% fetal bovine serum) to scrape off the surviving viruses, and the respective suspensions were diluted. Each diluent was inoculated into the allantoic membrane of five 10-day-old embryos. After incubation for 5 days at 37℃, AIV viability in the collected allantoic fluids was examined, and the egg infectious dose 50 (EID50) was calculated. When the carrier was exposed to ClO2 gas generated from reacting 34 mL of the fumigant for 3 h, the AIV titer reduced by more than 104.0 EID50/carrier compared to the control, which was exposed to the fumigant without inoculation of AIV suspension. In addition, the control was non-toxic to the embryos.

Wild birds, especially aquatic birds, are the natural reservoir of avian influenza virus (AIV), and many kinds of water body can be contaminated with feces of these birds. Seasonally, AIVs can be dissolved in the environmental water from the feces of the infected birds, and this water can be a target for viral detection and identification. In this study, we employed and tested three different filters for concentrating AIV, and it was shown that high concentration factor in terms of viral density could be achieved with viral samples diluted with natural water. Wild bird fecal samples containing low pathogenicity H5 AIVs were successfully concentrated with the adsorption and elution method using mixed cellulose esters membrane; the recovery rate of virus was 35.5 % and the concentration factor was about 50 on average. For the larger volume of water sample, we proved that an inline disposable filter with high surface area, 300 cm2, has a comparable concentration factor to the adsorption and elution method and the filter could be used in the field conveniently by being plugged into peristaltic pump. These validated methods for water sampling may be used as a supplementary for virological surveillance on wild migratory birds or during the epidemiological investigation on the environment near affected premises by AIV.

The epidemiological associations between poultry farm biosecurity measures and the 2016/18 highly pathogenic avian influenza (HPAI) epidemics were evaluated using a multivariate logistic model. In the model, 11 biosecurity measures were used as independent variables in the model: a security fence to keep wild birds out of the farm, a security gate on the farm, a farm signboard, number of footbaths for disinfecting footwear, number of anterooms, U-shaped disinfection farm gate, a tunnel-shaped disinfection farm gate, a high-pressure disinfectant fogging farm gate, disinfectant booth for farm workers and visitors, high-pressure disinfectant sprayer in the farm, and personnel disinfectant sprayer in the farm. Two hundred and eighty-eight poultry farms (144 HPAI-confirmed and 144 non-confirmed) were used as the dependent variable. The numbers of footbaths and anterooms were converted to a categorical measurement format using a general additive model. The likelihood of an HPAI outbreak in a poultry farm with a fence to prevent contact between wild birds and domestic fowl was less than that of farms without a fence (OR: 0.54, P value: 0.01). The Akaike information criterion score of the multivariate model (370.91) was less than that of the univariate logistic model for each biosecurity measure. From an HPAI control perspective, it is recommended for poultry farmers to construct a wild bird-proof fence to decrease the HPAI outbreak risk.

The mallard and spot-billed duck are representative migratory bird species wintering in the Republic of Korea. They can be a highly pathogenic avian influenza (HPAI) virus carrier during their wintering movement. From September 2014 to June 2015, 162 poultry farms were confirmed to have a HPAI infection. The current study estimated the home range of the mallard and spot-billed duck during the 2014/15 HPAI epidemics to explore the relationship between the wintering site of the migratory birds and the geographical locations of HPAI-infected farms. A Brownian bridge movement model was applied to estimate the home ranges of 13 mallards and three spot-billed ducks. As a result, 22 HPAI-infected poultry farms were located geographically in the 99% cumulative probability contour of the home range of the mallard, but no HPAI-infected poultry farm was found in spot-billed duck’s home range. In the case of one spot-billed duck, however, it has two wintering sites: Chungcheongnam-do and Jeollanam-do. Considering that migratory birds can be a major driven factor in HPAI virus transmission from wild birds to poultry farms, it is recommended for poultry farms located within the home range of migratory birds to increase their biosecurity level during wintering season of migratory birds.

The current study explored the epidemiological associations between the 2016/18 highly pathogenic avian influenza (HPAI) epidemics and spatial factors, including the distance from a poultry farm to the closest groundwater source, migratory bird habitat, eco-natural area, and poultry farm altitude. We included 14 spatial factors as independent variables. The variables were used in the original continuous measurement format. In total, 288 poultry farms (144 HPAI-confirmed and 144 non-confirmed) were used as the dependent variable. In addition, the variables’ continuous measurement was converted to a categorical measurement format by using a general additive model. For risk factor analysis based on the continuous measurements of spatial factors, the non-graded eco-natural area distance (odds ratio [OR]: 1.00) and the grade one eco-natural area distance (OR: 0.99) were statistically significant independent variables. However, in the risk factor analysis based on the categorical measurement format of the spatial factors, the non-graded eco-natural area distance (OR: 0.08) and poultry farm altitude (OR: 0.44) were statistically significant independent variables in both a univariate and multiple logistic regression model. In other words, when a poultry farm was located far from the non-graded eco-natural area or in a highland area, the likelihood of an HPAI epidemic would decrease. From an HPAI control perspective, it is recommended that the government apply increased levels of biosecurity measures, such as bird-nets, fences, intensive disinfection of equipment, and regular bird health monitoring, for poultry farms located near non-graded eco-natural areas or in a lowland area.

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.

Avian pathogenic Escherichia coli (APEC) is an agent associated with colibacillosis and an important primary pathogen with responsible for significant economic losses in chickens. This study investigated the molecular characteristics including virulence and antimicrobial resistance of serotype O78 APEC isolates, the predominant serotype, in Korea. Among 16 O78 APEC isolates, 13 isolates carried the genes conferring resistance to ß-lactam (blaTEM), aminoglycoside [aac(3)-II], plasmid-mediated quinolone (qnrA), tetracycline (tetA and tetB), sulfonamide (sul1 and sul2), or chloramphenicol (catA1). Three isolates showed resistance to gentamicin and carried aminoglycoside-modifying enzyme gene, aac(3)-II, simultaneously. Ten O78 APEC isolates showed resistance to nalidixic acid, but only qnrA gene among plasmid-mediated quinolone resistance genes was detected in one isolate. The tetA and tetB genes were also detected in nine and two isolates, respectively. In distribution of phylogenetic groups, four O78 APEC isolates only belonged to group D. But all isolates carried three to five essential virulence genes regardless of phylogenetic groups. Virulence factors and antimicrobial resistance of the most predominant serotype, O78, in chickens tested in this study can be significant role in persistence of APEC in Korea.

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.

The goal of the current study was to explore the relationship between vehicle movement frequency and a disease outbreak by using the example of the highly pathogenic avian influenza (HPAI) outbreak in 2014 in the Republic of Korea. To explore the relationship between the HPAI outbreak status of Korean provinces and vehicle movements, both an ordinary least square model (OLS) and a maximum entropy model (MaxEnt) were built. The HPAI outbreak status of each province was used as a dependent variable. The number of poultry farm vehicle movements within the province (within variable), the number of poultry farm vehicle movements 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 models as independent variables. Results of the OLS model were as follows: the estimated coefficient of the log-transformed within variable was -0.30, that of the log-transformed outbound variable was 0.71, that of the log-transformed inbound variable was -0.30, and that of the number of poultry farms was 0.07; however, only the number of poultry farms per province was statistically significant. Results of the MaxEnt model were as follows: the median relative contribution of the log-transformed outbound variable was 52.0 (range: 12.2–83.9), that of the log-transformed inbound variable was 34.4 (range: 8.8–83.4), that of the log-transformed within variable was 3.7 (range: 1.8–7.3), and that of the number of poultry farms per province was 0.7 (range: 0.0–11.7). The area under the receiver operating characteristics curve was 0.683. The results of current study should be helpful for planning a national HPAI surveillance program to locate surveillance resources with the consideration of risk level of provinces.

To attenuate and control the spread of infectious disease, a body of research has been conducted to generate safe vaccines and to continue national-level surveillance. However, understanding on viability and persistence of avian influenza virus (AIV) in infected carcasses, and effective disposal approaches are still limited up to date. Here, using HA test and RT-PCR, we assessed active status of AIV and degradation of viral RNA in collected specimens at different sites and time points. First, AIV infectivity was recovered until day 2, and viral nucleic acids persisted to day 14 and 21 in inorganic and organic samples, respectively, in sealed vials incubated at room temperature. Second, AIV was totally inactivated in all examined specimens, and viral RNA was not detectable at all time points tested at least one month post-infection in AIV-inoculated carcasses buried directly in soil or fiber reinforced plastic (FRP) bin. Lastly, among different burial sites in South Korea, 6 out of 17 sampling sites in Jeonbuk province showed the presence of viral genetic materials, while the rest of the field samples displayed neither the presence of infective AIV nor detectable viral RNA. This study showed a linear relation between time and degradation degree of viral RNA in buried samples suggesting that burial disposal method is effective for the control or at least attenuation of spread of AI infection in infected animals although consistent monitoring is required to verify safety of disposal.

Epidemiological research to investigate the spatial characteristics of poultry farms confirmed with avian influenza (AI) infection can help increase the efficacy of AI surveillance as well as AI control strategies. The spatial characteristics of poultry farms confirmed with AI infection can provide insights on effective AI-surveillance and AI-control strategies to policymakers by providing a visualization of the geographical pattern of AI distribution. The goal of the current study was to investigate the spatial characteristics of the risk of a farm being AI-positive by using data from routine AI-surveillance performed during the period 2014–2015. To achieve this goal, we applied a spatial model because it improves the estimation of the relative risk by taking into account spatial dependence between epidemiological units. The results revealed there was a lack of dependency between districts in the risk of a farm being AI-positive. The estimates for the spatial autocorrelation coefficient in the spatial model for chicken farms were 0.006 in 2014 (p = 0.9496) and -0.064 in 2015 (p = 0.6052) and for duck farms were -0.066 in 2014 (p = 0.4380) and 0.047 in 2015. Likewise, Moran’s I statistic estimates for chicken farms were 0.0243 in 2014 (p = 0.3183) and -0.0174 in 2015 (p = 0.5657) and for duck farms were -0.0342 in 2014 (p = 0.6678) and -0.0230 in 2015.

Epizootic HPAIV, H5N6, and H5N8 infections produced severe loss in poultry and wild birds in the Republic of Korea from 2016 to 2017. But pathological lesions and antigen distribution of the novel HPAIV H5N6 clade 2.3.4.4 in natural cases have been rarely reported. Herein, we describe the pathological lesions and antigen localization in chickens (layer and Korean native), ducks, and Japanese quail naturally infected by HPAIV H5N6. Grossly, severe reddening, swelling, and some necrotic foci, which were similar to septicemia or viremia, were observed in skin and many visceral organs including trachea, lung, liver, spleen, and pancreas. Histopathologically, pulmonary congestion and edema, as well as necrotizing hepatitis, splenitis, pancreatitis, myocarditis, and encephalitis were observed. Immunohistochemically, numerous HPAIV antigens were detected in necrotic parenchymal cells and in blood vessels of the respiratory, lymphoid, digestive, urinary, nervous, and cardiovascular systems. The results indicate that HPAIV H5N6 spread to the entire body via blood and caused severe damage throughout the entire body. The HPAI H5N6 clade 2.3.4.4 virus was isolated from samples of all four cases.

Highly pathogenic avian influenza virus (HPAIV) damages vital organs and tissues, frequently leading to death in birds, and causes serious economic losses in the poultry industry. In addition, HPAIV can infect humans and other mammals, often with fatal outcomes. In this study, the virucidal efficacy of Clean-Zone®, which contains citric acid, malic acid and phosphoric acid, against avian influenza virus (AIV, H9N2) was investigated. Virucidal efficacy was determined by examining the viability of AIV after contact with the disinfectant in the allantoic membrane of chicken embryos. The disinfectant and AIV were reacted under hard water (HW) and organic matter suspension (OM) condition. AIV was inactivated with 200- and 50-fold dilutions of the disinfectant under HW and OM conditions, respectively. As the disinfectant, Clean-Zone®, has a virucidal efficacy against AIV, it can be used to prevent the spread of animal viral diseases.

In this paper, a mathematical model of regionalization based on graph theory to investigate the patterns induced by movements of livestock vehicles in cities under outbreaks of highly pathogenic avian influenza (HPAI) is proposed. We then compare the results of simulation from the regionalization model to actual HPAI outbreaks in 2016/2017 to evaluate the validity of the model. Specifically, we (1) configured a complex network structure with analytic tools and properties in graph theory to abstract the paths among farms and livestock facilities; (2) employed statistical methods to estimate the possibility of propagation between two clusters; (3) applied the developed method to an actual HPAI outbreak in Korea in 2016 and conducted a simulation to determine if the proposed modeling for regionalization is an effective prediction measure. The clustered regions proposed by the simulation correctly reflected the regional clustering of actual cases, while simultaneously contain the cities exposed to potential damage when separated. Based on these findings, we conclude that our proposed regionalization model is suitable for making policy judgments to establish a preemptive biosecurity system.

An understanding of the geographic distribution of highly pathogenic avian influenza (HPAI) is essential to assessing and managing the risk of introduction of HPAI virus (HPAIV). However, to date, local spatial clustering patterns of HPAI outbreaks in Korea has not been explicitly investigated. We compiled HPAI outbreak data (n=622 cases) from December 2003 to February 2016. Each reported case was geocoded and linked to a digital map of Korea according to its onset location using the geographic information system (GIS). Kernel density estimation was used to explore global patterns of the HPAI outbreaks. We also applied the Getis-Ord G local spatial statistic to identify significant hot spots of high and low abundance by calculating Z-scores. Hot spot analysis revealed that HPAI cases are likely to be distinct clusters of HPAI outbreaks, with the highest risk being in the southwest of the country, specifically in Jeonnam and Jeonbuk provinces, where there are high density poultry populations. More than 16 Si-Gun-Gu (administrative province unit with bandwidth of 30 km) were involved in these high risk areas, indicating that there is likely to be a spatial heterogeneity of HPAI outbreaks within the country. Because of the existence of apparent hot spots, particularly in western regions, along with the increased number of migratory birds in these areas, Korea is at high risk of HPAIV introduction. Taking this challenge into consideration, preemptive and effective targeted surveillance programs for wild birds and poultry farms are highly recommended. Future research should look at the risk factors related to the socio-economic, human and natural environments and the poultry production systems to explain the spatial heterogeneity of HPAI outbreaks.