Disease Course of Korean African Swine Fever Virus in Domestic Pigs Exposed Intraorally, Intranasally, Intramuscularly, and by Direct Contact with Infected Pigs.

African swine fever (ASF) is a fatal contagious disease affecting swine. The first Korean ASF virus (ASFV) isolate (Korea/Pig/Paju1/2019) was used to compare the disease course of ASFV in pigs inoculated via the four routes. In the challenge experiment, domestic pigs were infected via the intraoral (IO) and intranasal (IN) routes with a 106 50% hemadsorbing dose (HAD50) and an intramuscular (IM) injection of 103 HAD50. In the direct contact (DC) group, five naïve pigs were brought into direct contact with two IM-ASFV-infected pigs. IO-, IN-, and IM-inoculated pigs showed similar disease courses, whereas DC pigs had comparable ASF syndrome after a 7-day latent period. The disease course in the DC route, one of the most common routes of infection, was not significantly different from that in the IO and IN routes. IM and DC groups differed in terms of the severity of fever and hemorrhagic lesions in the lymph nodes and spleen, indicating that the IM route, suitable for early vaccine development trials, is not appropriate for studying the ASFV infection mechanism, including early stage of infection, and IO and IN challenges with a designated dose can be alternatives in trials for assessing ASFV pathogenicity and vaccine efficacy investigations.

Tick Diversity and Pathogen Transmission in Daejeon, Korea: Implications from Companion Animals and Walking Trails.

With the ongoing global warming-induced climate change, there has been a surge in vector-borne diseases, particularly tick-borne diseases (TBDs). As the population of companion animals grows, there is growing concern from a One Health perspective about the potential for these animals to spread TBDs. In this study, ticks were collected from companion animals and the surrounding environment in Daejeon Metropolitan City, Korea, using flagging and dragging, and CO2 trap methods. These ticks were then subjected to conventional (nested) PCR for severe fever with thrombocytopenia syndrome virus (SFTSV), Anaplasma spp., Ehrlichia spp., and Borrelia spp. We identified a total of 29,176 ticks, consisting of three genera and four species: H. longicornis, H. flava, I. nipponensis, and A. testudinarium. Notably, H. longicornis was the predominant species. The presence of A. testudinarium suggested that the species traditionally found in southern regions are migrating northward, likely as a result of climate change. Our PCR results confirmed the presence of all four pathogens in both companion animals and the surrounding environment, underscoring the potential for the indirect transmission of tick-borne pathogens to humans through companion animals. These findings emphasize the importance of the ongoing surveillance of companion animals in the management and control of TBDs.

Identification of Pre-Emptive Biosecurity Zone Areas for Highly Pathogenic Avian Influenza Based on Machine Learning-Driven Risk Analysis.

Over the last decade, highly pathogenic avian influenza (HPAI) has severely affected poultry production systems across the globe. In particular, massive pre-emptive depopulation of all poultry within a certain distance has raised concerns regarding animal welfare and food security. Thus, alternative approaches to reducing unnecessary depopulation, such as risk-based depopulation, are highly demanded. This paper proposes a data-driven method to generate a rule table and risk score for each farm to identify preventive measures against HPAI. To evaluate the proposed method, 105 cases of HPAI occurring in a total of 381 farms in Jeollanam-do from 2014 to 2023 were evaluated. The accuracy of preventive measure identification was assessed for each case using both the conventional culling method and the proposed data-driven method. The evaluation showed that the proposed method achieved an accuracy of 84.19%, significantly surpassing the previous 10.37%. The result was attributed to the proposed method reducing the false-positive rate by 83.61% compared with the conventional method, thereby enhancing the reliability of identification. The proposed method is expected to be utilized in selecting farms for monitoring and management of HPAI.

Ecological drivers for poultry farms predisposed to highly pathogenic avian influenza virus infection during the initial phase of the six outbreaks between 2010-2021: a nationwide study in South Korea.

Background: Highly pathogenic avian influenza (HPAI) has caused substantial economic losses worldwide. An understanding of the environmental drivers that contribute to spillover transmission from wild birds to poultry farms is important for predicting areas at risk of introduction and developing risk-based surveillance strategies. We conducted an epidemiological study using data from six HPAI outbreak events in South Korea. Materials and methods: An aggregate-level study design was implemented using third-level administrative units in South Korea. Only regions with high natural reservoir suitability were included. The incidence of HPAI at chicken and duck farms during the initial phase (30 and 45 days after the first case) of each outbreak event was used as the outcome variable, assuming that cross-species transmission from wild birds was the dominant exposure leading to infection. Candidate environmental drivers were meteorological factors, including temperature, precipitation, humidity, and altitude, as well as the proportion of protected area, farm density, deforestation level, and predator species richness. Logistic regression models were implemented; conditional autoregression models were used in cases of spatial autocorrelation of residuals. Results: Lower temperature, higher farm density, and lower predator species richness were significantly associated with a higher risk of HPAI infection on chicken farms. Lower temperature, higher proportion of protected area, and lower predator species richness were significantly associated with a higher risk of HPAI infection on duck farms. Conclusion: The predicted dominant transmission routes on chicken and duck farms were horizontal and spillover, respectively. These results reveal a potential protective effect of predator species richness against HPAI outbreaks. Further studies are required to confirm a causal relationship.

Demonstration of SARS-CoV-2 Exposure in Korean Native Cattle and Korean Native Black Goats in Korea.

The COVID-19 pandemic is caused by the zoonotic SARS-CoV-2 virus. A wide range of animals that interact with humans have been investigated to identify potential infections. As the extent of infection became more apparent, extensive animal monitoring became necessary to assess their susceptibility. This study analyzed nasal swabs and blood samples collected from randomly selected Korean native cattle and Korean native black goats. The tests conducted included real-time qPCR to detect SARS-CoV-2 antigens, an ELISA to detect antibodies, and a plaque reduction neutralization test (PRNT) to determine the presence of neutralizing antibodies. Among the 1798 animals tested (consisting of 1174 Korean native cattle and 624 Korean native black goats), SARS-CoV-2 viral RNA was detected in one Korean native cattle and one Korean native black goat. ELISA testing revealed positive results for antibodies in 54 Korean native cattle (4.60%) and 16 Korean native black goats (2.56%), while PRNTs yielded positive results in 51 Korean native cattle (4.34%) and 14 Korean native black goats (2.24%). The presence of SARS-CoV-2 antigens and/or antibodies was identified in animals on farms where farmworkers were already infected. It is challenging to completely rule out the possibility of reverse zoonotic transmission from humans to livestock in Korea, although the transmission is not to the same extent as it is in highly susceptible animal species like minks, cats, and dogs. This is due to the limited geographical area and the dense, intensive farming practices implemented in these regions. In conclusion, continuous viral circulation between humans and animals is inevitable, necessitating ongoing animal monitoring to ensure public health and safety.

Effect of a Mismatched Vaccine against the Outbreak of a Novel FMD Strain in a Pig Population.

In December 2014, a novel foot and mouth disease (FMD) virus was introduced to a pig farm in South Korea, despite the animals being vaccinated. A marginal antigenic matching between the novel and vaccine strains potentially led to the infection of the vaccinated animals. To understand the impact of using an FMD vaccine on the transmission dynamics of an unmatched field strain, simulation models were employed using daily reported data on clinical cases from the farm. The results of this study indicated that immunisation with the FMD vaccine reduced the shedding of the novel FMD virus in pigs. However, there was no evidence to suggest that the immunisation had a significant effect in reducing the development of clinical signs. These findings highlight that the use of an unmatched FMD vaccine can confound the outbreak by altering the disease dynamics of the novel virus. Based on this study, we emphasise the importance of continuous testing to ensure antigenic matching between the circulating strains and the vaccine pool.

Pathogenicity and Pathological Characteristics of African Swine Fever Virus Strains from Pig Farms in South Korea from 2022 to January 2023.

Since the first African swine fever (ASF) outbreak occurred at a pig farm in South Korea in September 2019, as of 31 January 2023, 31 ASF cases have occurred at pig farms, while 2799 ASF virus (ASFV)-infected wild boars have been identified. The circulation of ASFV in wild boar populations poses a high risk of spillover to pig farms in the country. However, information on the changes in the pathogenicity of Korean ASFV strains from wild boars is not available. Investigating the pathogenicity of ASFV strains from pig farms is the only way to predict their alterations. In a previous study, no changes in the pathogenicity of ASFV strains circulating during 2019-2021 were identified through animal experiments. In this study, we chose two ASFV strains with potentially reduced pathogenicity among ten viruses obtained from pig premises from 2022 to January 2023 and estimated their pathogenicities and pathological characteristics. All the inoculated pigs died 8-10 days post-inoculation after showing pyrexia, depression, anorexia, and recumbency together with the common pathological lesions of enlarged hemorrhagic lymph nodes and splenomegaly with infarction. These results support that the pathogenicity among ASFV isolates in South Korea still remained unchanged during the study period.

Genetic Profile of African Swine Fever Viruses Circulating at Pig Farms in South Korea during the Outbreaks between 2022 and April 2023.

Fifteen pig farms were affected by African swine fever (ASF) in South Korea during the outbreaks between 2022 and April 2023. The ASF virus (ASFV) genome was directly extracted from the blood and tissue samples of 15 ASFV-positive pig farms to analyze the genetic characteristics. Phylogenetic analysis revealed that the 15 strains belonged to p72 genotype II and CD2v serogroup 8, which were the central variable region (CVR) I variants of the B602L gene. Fourteen strains were intergenic region (IGR) II variants, containing an additional tandem repeat sequence (TRS), between I73L and I329R, with the exception of one strain from an ASFV-infected pig farm reported on 22 January 2023, which was an IGR I variant. In addition, a single-nucleotide polymorphism (SNP) was detected at position 107 from the start of the IGR between A179L and A137R in six isolates. The findings of this study suggest that the sources of the virus at the pig farms from which these variants originated differed from those of other pig farms.

Data-driven risk assessment of the incursion of African swine fever virus via pig products brought illegally into South Korea by travelers based on the temporal relationship between outbreaks in China.

Since 2018, Asian countries have been affected by the African swine fever (ASF) virus, with major socioeconomic consequences. Moreover, the number of people traveling in Asian countries has been increasing, leading to an inevitable increase in the risk of ASF spread through livestock products carried by travelers. China and South Korea have close geo-economic ties and numerous international travelers. After the ASF outbreak in China in 2018, many illegally imported pig products (IIPPs) that were confiscated from travelers from China at the port of entry in South Korea tested positive for ASF. The detection of ASF virus (ASFV)-positive IIPPs highlights the need to further assess the risk of incursion by travelers and review the existing prevention strategies. Here, we investigated the temporal relationship between ASF outbreaks in China and the detection of ASFV-positive IIPPs in randomly confiscated samples from all ports of entry, such as flights and ships to South Korea, from 2018 to 2019 using a cross-correlation analysis. Based on the significantly correlated temporal lags between the bivariate time-series data, a risk assessment model, using the Bayesian framework, was built to estimate the distribution of the parameters for the risk assessment model and the monthly probability of ASF being introduced via IIPPs from China to South Korea. ASF outbreaks in China were significantly associated with the detection of ASFV-positive IIPPs in South Korea 5 months later. Hence, the monthly probability of ASFV-infected pig products imported from China via a traveler to South Korea was estimated to be 2.00 × 10-5, corresponding to a 0.98 mean monthly probability of at least one ASF-infected pig product arriving at ports of entry via travelers, from 2018 to 2019. To our knowledge, this study is the first attempt to estimate the risk of ASF introduction via pig products carried by international travelers to all ports from neighboring countries in the Asian region using commonly exchanged observed data. The data presented in this study can be used to refine the intervention strategies to combat the spread of transboundary animal diseases.

Health behaviors and the risk of COVID-19 incidence: A Bayesian hierarchical spatial analysis.

OBJECTIVES: Effective infection control measures, based on a sound understanding of geographical community-specific health behavioral characteristics, should be implemented from the early stage of disease transmission. However, few studies have explored health behaviors as a possible contributor to COVID-19 infection in the spatial context. We investigated health behaviors as potential factors of COVID-19 incidence in the early phase of transmission in the spatial context. METHODS: We extracted COVID-19 cumulative case data as of February 25, 2021-one day prior to nationwide COVID-19 vaccination commencement-regarding health behaviors and covariates, including health condition and socio-economic factors, at the municipal level from publicly available datasets. The spatial autocorrelation of incidence was analyzed using Global Moran's I statistics. The associations between health behaviors and COVID-19 incidence were examined using Besag-York-Mollie models to deal with spatial autocorrelation of residuals. RESULTS: The COVID-19 incidence had positive spatial autocorrelation across South Korea (I = 0.584, p = 0.001). The results suggest that individuals vaccinated against influenza in the preceding year had a negative association with COVID-19 incidence (relative risk=0.913, 95 % Credible Interval=0.838-0.997), even after adjusting for covariates. CONCLUSIONS: Our ecological study suggests an association between COVID-19 infection and health behaviors, especially influenza vaccination, in the early stage of COVID-19 transmission at the municipal level.

Epidemiology and Transmission Dynamics of Infectious Diseases and Control Measures.

The epidemiology and transmission dynamics of infectious diseases must be understood at the individual and community levels to improve public health decision-making for real-time and integrated community-based control strategies. Herein, we explore the epidemiological characteristics for assessing the impact of public health interventions in the community setting and their applications. Computational statistical methods could advance research on infectious disease epidemiology and accumulate scientific evidence of the potential impacts of pharmaceutical/nonpharmaceutical measures to mitigate or control infectious diseases in the community. Novel public health threats from emerging zoonotic infectious diseases are urgent issues. Given these direct and indirect mitigating impacts at various levels to different infectious diseases and their burdens, we must consider an integrated assessment approach, 'One Health', to understand the dynamics and control of infectious diseases.

Dynamics of the Emerging Genogroup of Infectious Bursal Disease Virus Infection in Broiler Farms in South Korea: A Nationwide Study.

Infectious bursal disease (IBD), caused by IBD virus (IBDV), threatens the health of the poultry industry. Recently, a subtype of genogroup (G) 2 IBDV named G2d has brought a new threat to the poultry industry. To determine the current status of IBDV prevalence in South Korea, active IBDV surveillance on 167 randomly selected broiler farms in South Korea from August 2020 to July 2021 was conducted. The bursas of Fabricius from five chickens from each farm were independently pooled and screened for IBDV using virus-specific RT-PCR. As a result, 86 farms were found to be infected with the G2d variant, 13 farms with G2b, and 2 farms with G3. Current prevalence estimation of IBDV infection in South Korea was determined as 17.8% at the animal level using pooled sampling methods. G2d IBDV was predominant compared to other genogroups, with a potentially high-risk G2d infection area in southwestern South Korea. The impact of IBDV infection on poultry productivity or Escherichia coli infection susceptibility was also confirmed. A comparative pathogenicity test indicated that G2d IBDV caused severe and persistent damage to infected chickens compared with G2b. This study highlights the importance of implementation of regular surveillance programs and poses challenges for the comprehensive prevention of IBDV infections.

Risk Prediction of Three Different Subtypes of Highly Pathogenic Avian Influenza Outbreaks in Poultry Farms: Based on Spatial Characteristics of Infected Premises in South Korea.

From 2003 to 2017, highly pathogenic avian influenza (HPAI) epidemics, particularly H5N1, H5N8, and H5N6 infections in poultry farms, increased in South Korea. More recently, these subtypes of HPAI virus resurged and spread nationwide, heavily impacting the entire poultry production and supply system. Most outbreaks in poultry holdings were concentrated in the southwestern part of the country, accounting for 58.3% of the total occurrences. This geographically persistent occurrence demanded the investigation of spatial risk factors related to the HPAI outbreak and the prediction of the risk of emerging HPAI outbreaks. Therefore, we investigated 12 spatial variables for the three subtypes of HPAI virus-infected premises [(IPs), 88 H5N1, 339 H5N8, and 335 H5N6 IPs]. Then, two prediction models using statistical and machine learning algorithm approaches were built from a case-control study on HPAI H5N8 epidemic, the most prolonged outbreak, in 339 IPs and 626 non-IPs. Finally, we predicted the risk of HPAI H5N1 and H5N6 occurrence at poultry farms using a Bayesian logistic regression and machine learning algorithm model [extreme gradient boosting (XGBoost) model] built on the case-control study. Several spatial variables showed similar distribution between two subtypes of IPs, although there were distinct heterogeneous distributions of spatial variables among the three IP subtypes. The case-control study indicated that the density of domestic duck farms and the minimum distance to live bird markets were leading risk factors for HPAI outbreaks. The two prediction models showed high predictive performance for H5N1 and H5N6 occurrences [an area under the curve (AUC) of receiver operating characteristic of Bayesian model > 0.82 and XGBoost model > 0.97]. This finding emphasizes that spatial characteristics of the poultry farm play a vital role in the occurrence and forecast of HPAI outbreaks. Therefore, this finding is expected to contributing to developing prevention and control strategies.

Impact of inland waters on highly pathogenic avian influenza outbreaks in neighboring poultry farms in South Korea.

BACKGROUND: Since 2003, the H5 highly pathogenic avian influenza (HPAI) subtype has caused massive economic losses in the poultry industry in South Korea. The role of inland water bodies in avian influenza (AI) outbreaks has not been investigated. Identifying water bodies that facilitate risk pathways leading to the incursion of the HPAI virus (HPAIV) into poultry farms is essential for implementing specific precautionary measures to prevent viral transmission. OBJECTIVES: This matched case-control study (1:4) examined whether inland waters were associated with a higher risk of AI outbreaks in the neighboring poultry farms. METHODS: Rivers, irrigation canals, lakes, and ponds were considered inland water bodies. The cases and controls were chosen based on the matching criteria. The nearest possible farms located within a radius of 3 km of the case farms were chosen as the control farms. The poultry farms were selected randomly, and two HPAI epidemics (H5N8 [2014-2016] and H5N6 [2016-2017]) were studied. Conditional logistic regression analysis was applied. RESULTS: Statistical analysis revealed that inland waters near poultry farms were significant risk factors for AI outbreaks. The study speculated that freely wandering wild waterfowl and small animals contaminate areas surrounding poultry farms. CONCLUSIONS: Pet birds and animals raised alongside poultry birds on farm premises may wander easily to nearby waters, potentially increasing the risk of AI infection in poultry farms. Mechanical transmission of the AI virus occurs when poultry farm workers or visitors come into contact with infected water bodies or their surroundings. To prevent AI outbreaks in the future, poultry farms should adopt strict precautions to avoid contact with nearby water bodies and their surroundings.

Detection of African Swine Fever at an Abattoir in South Korea, 2020.

In October 2020, a suspect case of African swine fever (ASF) was detected at an abattoir located in the north-central border region of South Korea. The farm of origin was traced and confirmed positive for ASF. This recurrence was following a period of absence of outbreaks in domestic pigs after the first incursion in 2019, during which a total of 14 domestic pig farms were confirmed between September and October 2019. In 2020, a total of two farms were confirmed, and the molecular characterization of key regions of the genome showed that the two isolates from 2020 were identical with the previous isolates from South Korea in 2019. The continued spread and circulation of ASF in the wild boar population represents an increased risk of spill-over outbreaks in domestic pigs, and, therefore, additional control measures should be implemented for farms in these regions, including a heightened level of surveillance. This was the case for the index farm, which was required to send pigs only to the designated abattoir at which the suspect case was quickly detected. The improvement of biosecurity in pig farms, particularly at the wild boar-domestic pig interface, will be key to the successful control of ASF in the region.

Spatial Variation in Risk for Highly Pathogenic Avian Influenza Subtype H5N6 Viral Infections in South Korea: Poultry Population-Based Case-Control Study.

Given the substantial economic damage caused by the continual circulation of highly pathogenic avian influenza (HPAI) outbreaks since 2003, identifying high-risk locations associated with HPAI infections is essential. In this study, using affected and unaffected poultry farms' locations during an HPAI H5N6 epidemic in South Korea, we identified places where clusters of HPAI cases were found. Hotspots were defined as regions having clusters of HPAI cases. With the help of the statistical computer program R, a kernel density estimate and a spatial scan statistic were employed for this purpose. A kernel density estimate and detection of significant clusters through a spatial scan statistic both showed that districts in the Chungcheongbuk-do, Jeollabuk-do, and Jeollanam-do provinces are more vulnerable to HPAI outbreaks. Prior to the migration season, high-risk districts should implement particular biosecurity measures. High biosecurity measures, as well as improving the cleanliness of the poultry environment, would undoubtedly aid in the prevention of HPAIV transmission to poultry farms in these high-risk regions of South Korea.

Socioeconomic Inequalities in COVID-19 Incidence During Different Epidemic Phases in South Korea.

Objective: Area-level socioeconomic status (SES) is associated with coronavirus disease 2019 (COVID-19) incidence. However, the underlying mechanism of the association is context-specific, and the choice of measure is still important. We aimed to evaluate the socioeconomic gradient regarding COVID-19 incidence in Korea based on several area-level SES measures. Methods: COVID-19 incidence and area-level SES measures across 229 Korean municipalities were derived from various administrative regional data collected between 2015 and 2020. The Bayesian negative binomial model with a spatial autocorrelation term was used to estimate the incidence rate ratio (IRR) and relative index of inequality (RII) of each SES factor, with adjustment for covariates. The magnitude of association was compared between two epidemic phases: a low phase (<100 daily cases, from May 6 to August 14, 2020) and a rebound phase (>100 daily cases, from August 15 to December 31, 2020). Results: Area-level socioeconomic inequalities in COVID-19 incidence between the most disadvantaged region and the least disadvantaged region were observed for nonemployment rates [RII = 1.40, 95% credible interval (Crl) = 1.01-1.95] and basic livelihood security recipients (RII = 2.66, 95% Crl = 1.12-5.97), but were not observed for other measures in the low phase. However, the magnitude of the inequalities of these SES variables diminished in the rebound phase. A higher area-level mobility showed a higher risk of COVID-19 incidence in both the low (IRR = 1.67, 95% Crl = 1.26-2.17) and rebound phases (IRR = 1.28, 95% Crl = 1.14-1.44). When SES and mobility measures were simultaneously adjusted, the association of SES with COVID-19 incidence remained significant but only in the low phase, indicating they were mutually independent in the low phase. Conclusion: The level of basic livelihood benefit recipients and nonemployment rate showed social stratification of COVID-19 incidence in Korea. Explanation of area-level inequalities in COVID-19 incidence may not be derived only from mobility differences in Korea but, instead, from the country's own context.

Bridging the Local Persistence and Long-Range Dispersal of Highly Pathogenic Avian Influenza Virus (HPAIv): A Case Study of HPAIv-Infected Sedentary and Migratory Wildfowls Inhabiting Infected Premises.

The past two decades have seen the emergence of highly pathogenic avian influenza (HPAI) infections that are characterized as extremely contagious, with a high fatality rate in chickens, and humans; this has sparked considerable concerns for global health. Generally, the new variant of the HPAI virus crossed into various countries through wild bird migration, and persisted in the local environment through the interactions between wild and farmed birds. Nevertheless, no studies have found informative cases associated with connecting local persistence and long-range dispersal. During the 2016-2017 HPAI H5N6 epidemic in South Korea, we observed several waterfowls with avian influenza infection under telemetric monitoring. Based on the telemetry records and surveillance data, we conducted a case study to test hypotheses related to the transmission pathway between wild birds and poultry. One sedentary wildfowl naturally infected with HPAI H5N6, which overlapped with the home range of one migratory bird with H5-specific antibody-positive, showed itself to be phylogenetically close to the isolates from a chicken farm located within its habitat. Our study is the first observational study that provides scientific evidence supporting the hypothesis that the HPAI spillover into poultry farms is caused by local persistence in sedentary birds, in addition to its long-range dispersal by sympatric migratory birds.

Spatiotemporal risk assessment for avian influenza outbreak based on the dynamics of habitat suitability for wild birds.

Highly pathogenic avian influenza (HPAI) has predominantly damaged the poultry industry worldwide. The fundamental prevention and control strategy for HPAI includes early detection and timely intervention enforcement through a systematic surveillance system for wild birds based on the ecological understanding of the dynamics of wild birds' movements. Our study aimed to develop a spatiotemporal risk assessment model for avian influenza (AI) infection in wild birds to empower surveillance information for a contingency strategy. For this purpose, first, we predicted the monthly habitat suitability of seven waterfowl species, using 227,671 Global Positioning System (GPS) tracking records of 562 birds from 2014 to 2018 in the Republic of Korea (ROK). Then, that predicted habitat suitability and 421 coordinates of AI detection sites in wild birds were used to build the risk assessment model. Subsequently, we compared the monthly predicted risk of avian influenza virus (AIv) identification in wild birds between case and non-case poultry farms with HPAI H5N6 outbreak in the ROK between 2016 and 2017. The results reported considerable variation of monthly habitat suitability of seven waterfowls and the impact of predicting AI occurrences in wild birds. The high habitat suitability for spot-billed ducks (contribution rate in November = 40.9%) and mallards (contribution rate in January = 34.3%) significantly contributed to predicting the average risk of AIv identification in wild birds, with high predictive performance [the monthly mean of area under the curve (AUC) = 0.978]. Moreover, our model showed that the averaged risk of identification AI in wild birds was significantly higher in HPAI infected premises, with infected domestic duck holdings exhibiting a significantly higher risk than the chicken farms in November. This study suggests that animal health authority establishes a risk-based HPAI surveillance system grounded on the ecological nature of wild birds to improve the effectiveness of prevention and preparedness of emerging epidemics.

Understanding the transmission of African swine fever in wild boars of South Korea: A simulation study for parameter estimation.

Since the introduction of African swine fever (ASF) to Georgia in 2007, the disease has spread to many other countries including South Korea. Initial detection of ASF from wild boars (WB) in South Korea was reported in early October 2019. Since then, more than a thousand WB samples collected from the northern part of the country have been confirmed as ASF positive (2.9% of ASF positivity among WB samples collected until June 2020), indicating that the disease is endemic in the WB populations. To control the disease, multiple layers of fence-lines have been erected. Nevertheless, outbreaks continuously occurred across the fence, requiring a better understanding of the spatial transmission mechanism of ASF in WBs. Hence, we developed a novel ASF transmission model to estimate ecological and epidemiological parameters related to the spread of the disease in the WB population of South Korea. The results showed that roads and rivers were effective to prevent the spread, reducing the transmission rate to approximately 37% on average. Only a limited level of reduction was indicated via fence-lines, implying erection of fences might be considered as a temporary measure to delay the spread. This study also revealed that the probability of ASF transmission to adjacent habitats considerably decreased with increasing distance, supporting the slow spatial transmission speed reported from other European countries. Considering that elucidation of ASF dynamics in WB is crucial to mitigate the impact of the disease, we believe this study provides some useful ecological and epidemiological implications to control the disease in future.