Pigs are considered a “mixing vessel” that can produce new influenza strains through genetic reassortments, which threaten public health and cause economic losses worldwide. We performed surveillance of swine influenza virus (SIV) using 114,140 nasal swabs from 11,414 Korean farms from 2009 to 2022, and characterized their genetic evolution at each farm level. A total of 169 farms out of the 11,414 (1.48%) were SIV-positive. The positivity rate for the H1N2 subtype, which is most dominant in the pig population, was 37.87% (64/169). Through hemagglutinin (HA) gene analysis, 64 H1N2-positive farms were classified into Eurasian avian-like (46/64, 71.88%), triple-reassortant (14/64, 21.88%), pdm09 (3/64, 4.69%), and classical swine (1/64, 1.56%) groups. The estimated evolutionary rate of HA in H1N2 from 2009 to 2022 in Korea is 1.5309 × 10-3/site/year (95% HPD intervals from 1.0003 × 10-3 to 2.1735 × 10-3) with an estimated mean growth rate of 0.0114. Estimates of the relative genetic diversity of clades over time suggested that the HA of H1N2 exhibited an increase in population size. The results of this study showed that the Eurasian avian-like-HA of the H1N2 subtype was dominant in the pig population. The continued evolution of the HA of H1N2, which is critical for cell entry, might lead to genetic diversity and the loss of vaccine cross-protection. These results indicate that continus surveillance is imperative for monitoring the evolution of the swine influenza virus.

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.

Influenza A viruses (IAVs) are members of the family Orthomyxoviridae and genus Orthomyxovirus. Avian and mammalian species are the host of IAVs, which includes humans and dogs. Canine influenza virus (CIV) is an emerging pathogen that causes severe and acute respiratory diseases in dogs. This study monitored the antigen and antibody against CIV in dogs in the Republic of Korea (ROK) from 2016 to 2021. One thousand and seventy-two nasal swabs and 1,545 blood samples were collected from animal hospitals and animal shelters. Five nasal swabs in 2017 and seven in 2018 from stray dogs were positive for CIV according to RT-PCR. The prevalence of H3N2 CIV ranged from 9.5% to 24.8%, according to the hemagglutination inhibition (HI) assay. On the other hand, none of the serum samples from 2018 to 2021 showed seropositivity against the avian H5, H7, and H9 viruses. The HI titers for H3N2 ranged from 16 to 512. The distribution of HI titer 16–32 was 57.6% in seropositive samples. The pet dogs were vaccinated against CIV, but the stray and military dogs were unvaccinated. In 2017 and 2018, the seroprevalence of CIV in stray dogs was higher than in the other years, and viral RNA was detected in nasal swabs. It may mean previous exposure of stray dogs to CIV. With the increasing number of pet dogs and the close contact between humans and dogs, canines could serve as an intermediate host for transmitting IAVs to humans. Therefore, continuous surveillance of CIV is needed for public health and the potential emergence of novel zoonotic viruses.

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.

In this study, the near-complete genome sequence of the novel reassortant H1N2 influenza A virus strain A/swine/Korea/KS60/2016 is reported. Sequences of the hemagglutinin (HA), neuraminidase (NA), and polymerase basic 2 (PB2) genes were analyzed, revealing that the isolates contain segments from previous Korean swine H1N2 strains. Additionally, the remaining genes of this strain originated from human H1N1 strains in 2009.

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.

Influenza A virus (IAV) causes respiratory disease in birds and mammals, including pigs and humans. Infection by IAV in pigs increases not only economic losses in the swine industry but also the emergence of novel IAV variants via gene reassortment, which is important due to the susceptibility of both birds and humans to IAV. This study provides serological data obtained during a study to detect IAV infections in pigs in the Republic of Korea during 2018 and 2019. A total of 1,559 samples were collected from 74 domestic pig farms. Hemagglutination inhibition (HI) assays were performed using the A/Swine/Korea/25-13(H1N1), A/Swine/Korea/E102 (H1N2), and A/Swine/Korea/Cy10/2007 (H3N2) viruses as antigens. The HI assay results showed that 266 of the 1,559 samples were seropositive (17.0%). Among these, H1N1, H1N2, and H3N2 comprised 7.3% (114), 6.0% (93), and 8.8% (137) of the 1,559 samples, respectively. Co-infections of H1N1/H1N2, H1N1/H3N2, H1N2/H3N2 and H1N1/H1N2/H3N2 were observed in 2.1% (31), 1.5% (23), 1.5% (24), and 0.8% (13) of the 1,559 samples, respectively. Interestingly, IAV infections were detected in all nine provinces of the country.

In this study, antibody responses after vaccination against equine influenza were investigated among 1,591 horses in the Republic of Korea using the hemagglutination inhibition (HI) test. Equine influenza has not occurred since 2011 and a commercial vaccine against H3N8 has been used. The equine influenza virus, A/equine/South Africa/4/03 (H3N8), was used as the antigen in the HI assay. The mean seropositive rate was 90.5% in 2019. Except for stallion whose seropositive rate was 78.5%, all seropositive rates of other horse types were over 90%. Regionally, except for Gangwon-do and Jeju-do whose seropositive rates were 89.0% and 87.1%, all seropositive rates in other provinces were over 90%. In the future, more through vaccination against equine influenza needs to be done based on this investigation result.

Salmonella Enteritidis (SE) infection, one of a major foodborne disease remains considerable public health concerns globally. In this study, we have constructed that the genetically inactivated SE ghost vaccine candidate, JOL2220 (Δlon ΔcpxR Δasd), which express the immunogenic hemagglutinin portion (HA1) of H1N1 virus on the Salmonella surface. The lysis gene cassette, holin-endolysin system originated from double DNA bacteriophage λ was cloned into the ghost vector plasmid pJHL464, which activated under the control of the convergent promoter system. Scanning electronic microscopic examination revealed that transmembrane tunnels of JOL2220 was formed following the 48 hr of the lysis mediated by the holin-endolysin system. In vitro expression of HA1 antigenic protein was also determined by Western blot analysis. The Chickens immunized with JOL2220 ghost via intramuscular and oral routes showed significant increase in IgG level against both SE and HA1 antigen. Further, we observed markedly enhancement of lymphocyte proliferation and T-cell differentiation in the primed PBMC of the immunized chicken, compared to those in the control group. Collectively, the results indicated that the SE ghosts expressing HA1 antigen may have immunostimulatory properties against Salmonella and influenza infection where the chicken is the predominant reservoir.

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.

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.

Salvia miltiorrhiza (Danshen) is perennial plant and commonly used in traditional Chinese medicine to treat numerous diseases like cardiovascular and cerebrovascular diseases, coronary heart disease, myocardial infarction, stroke and some viral diseases. Nevertheless, no study has been conducted on the antiviral properties of crude extract of Salvia miltiorrhiza against Influenza virus. In an attempt to identify new potential anti-influenza virus agents, 200 natural oriental herbal medicines were screened and we found that Salvia miltiorrhiza has a potential anti-influenza effect. Therefore, in this study, we investigated the protective effect of aqueous extract from Salvia miltiorrhiza against divergent influenza A subtypes using murine model of influenza A infection. Effective dose of aqueous extracts of Salvia miltiorrhiza in BALB/c mice displayed higher survival rate and lower lung viral titers when challenged with lethal doses of influenza A subtypes ({A/Aquatic bird/Korea/ W81/2005(H5N2)}, {A/PR/8/34(H1N1)}, {A/Aquatic bird/Korea/W44/2005(H7N3)} and {A/Chicken/ Korea/116/2004(H9N2)}). In vivo results exhibited that Salvia miltiorrhiza induced prophylactic effect in BALB/c mice against Influenza virus by disrupting viral replication or preventing viral infection by creating an antiviral state in the lungs. Taken together, the use of aqueous extracts of Salvia miltiorrhiza as an orally active antiviral agent, will be potential candidates for prophylactic treatments against Influenza A virus for humans and animals.

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.