African Swine Fever Transmission Research Articles

Semiquantitative Risk Evaluation Reveals Drivers of African Swine Fever Virus Transmission in Smallholder Pig Farms and Gaps in Biosecurity, Tanzania.

African swine fever (ASF) has remained persistent in Tanzania since the early 2000s. Between 2020 and 2021, pig farms in twelve districts in Tanzania were infected with ASF, and ≥4,804 pigs reportedly died directly due to the disease with disruption to livelihoods. We conducted semiquantitative field investigations and rapid risk assessment (RRA) to understand the risk factors and drivers of ASF virus (ASFV) amplification and transmission in smallholder pig farms, and determine the gaps in biosecurity through hazard profiling, focus group discussions and expert opinion. Outbreaks were connected by road and aligned along the pig product value chain and reported in the northern, central, and southern parts of Tanzania. The patterns of outbreaks and impacts differed among districts, but cases of ASF appeared to be self-limiting following significant mortality of pigs in farms. Movement of infected pigs, movement of contaminated pig products, and fomites associated with service providers, vehicles, and equipment, as well as the inadvertent risks associated with movements of animal health practitioners, visitors, and scavengers were the riskiest pathways to introduce ASFV into smallholder pig farms. Identified drivers and facilitators of risk of ASFV infection in smallholder pig farms were traders in whole pigs, middlemen, pig farmers, transporters, unauthorized animal health service providers, and traders in pork. All identified pig groups were susceptible to ASFV, particularly shared adult boars, pregnant and lactating sows, and other adult females. The risk of ASF for smallholder pig farms in Tanzania remains very high based on a systematic risk classification. The majority of the farms had poor biosecurity and no single farm implemented all identified biosecurity measures. Risky practices and breaches of biosecurity in the pig value chain in Tanzania are profit driven and are extremely difficult to change. Behavioural change communication must target identified drivers of infections, attitudes, and practices.

African swine fever in wild boar: investigating model assumptions and structure

African swine fever (ASF) is a highly virulent viral disease that affects domestic pigs and wild boar. Current ASF transmission in Europe is in part driven by wild boar populations, which act as a disease reservoir. Wild boar are abundant throughout Europe and are highly social animals with complex social organization. Despite the known importance of wild boar in ASF spread and persistence, knowledge gaps remain surrounding wild boar transmission. We developed a wild boar modelling framework to investigate the influence of contact-density functions and wild boar social structure on disease dynamics. The framework included an ordinary differential equation model, a homogeneous stochastic model and various network-based stochastic models that explicitly included wild boar social grouping. We found that power-law functions (transmission ∝ density 0.5 ) and frequency-based contact-density functions were best able to reproduce recent Baltic outbreaks; however, power-law function models predicted considerable carcass transmission, while frequency-based models had negligible carcass transmission. Furthermore, increased model heterogeneity caused a decrease in the relative importance of carcass-based transmission. The transmission pathways predicted by each model type affected the efficacy of idealized interventions, which highlights the importance of evaluating model type and structure when modelling systems with significant uncertainties.

Spatial and temporal analysis of African swine fever front-wave velocity in wild boar: implications for surveillance and control strategies.

The front-wave velocity of African swine fever (ASF) virus spread is depicted through a retrospective spatial and temporal analyses of wild boar outbreaks from Jan. 2014 to Jan. 2022 in Estonia, Latvia, Lithuania and Eastern Poland-regions responsible for more than 50% of all wild boar cases in the EU. The study uses empirical semivariograms in a universal kriging model to assess spatial autocorrelation in notification dates and identifies a discernable large-scale spatial trend. The critical parameter of ASF front-wave velocity was identified (Mean = 66.33 km/month, SD = 163.24) in the whole study area, and explored the variations across countries, wild boar habitat suitability, seasons, and the study period. Statistical differences in front-wave velocity values among countries and temporal clusters are explored, shedding light on potential factors influencing ASF transmission dynamics. The implications of these findings for surveillance and control strategies are discussed.

Predicting Disparity between ASF-Managed Areas and Wild Boar Habitats: A Case of South Korea.

African swine fever (ASF) is a highly contagious viral disease affecting both domestic and wild boars. Since its first outbreak in South Korea in 2019, substantial efforts have been made to prevent ASF transmission by reducing the wild boar population and eliminating infected carcasses; however, the persistence of ASF transmission has posed challenges to these efforts. To improve ASF management strategies, the limitations of current management strategies must be identified by considering disparities between wild boar habitats and ASF-managed areas with environmental and anthropogenic characteristics of wild boars and their management strategies. Here, ensemble species distribution models were used to estimate wild boar habitats and potential ASF-managed areas, with elevation, distance to urban areas, and Normalized Difference Vegetation Index as important variables. Binary maps of wild boar habitats and potential ASF-managed areas were generated using the maxSSS as the threshold criterion. Disparity areas of ASF management were identified by overlying regions evaluated as wild boar habitats with those not classified as ASF-managed areas. Dense forests near urban regions like Chungcheongbuk-do, Gyeongsangbuk-do, and Gyeongsangnam-do were evaluated as disparity areas having high risk of ASF transmission. These findings hold significant potential for refining ASF management strategies and establishing proactive control measures.

Pig Farm Management and Its Contribution to The African Swine Fever Incidences in Kupang, Indonesia

This study evaluated the husbandry and management practices adopted by the pig farmers and the potential of African Swine Fever (ASF) in Kupang, East Nusa Tenggara, Indonesia. Husbandry and management practices evaluated include educational background, main occupation, livestock pens, animal feed and drinking water systems, reproductive management, and pig body condition. Data were collected from 300 pig farmers using interviews and questionnaires. This study was conducted in the districts of Kupang Timor and Amabi Oefeto from June to October 2022. This study reported several factors that could potentially affect the ASF transmission. These practices can be improved to prevent the potential of ASF transmission. The educational background of pig farmers, primary occupation, caging management, swill feeding, and reproductive management may have potentially contributed to the ASF transmission in Kupang during the outbreak period.

Estimating the effectiveness of control actions on African swine fever transmission in commercial swine populations in the United States.

Given the proximity of African swine fever (ASF) to the U.S., there is an urgent need to better understand the possible dissemination pathways of the virus within the U.S. swine industry and to evaluate mitigation strategies. Here, we extended PigSpread, a farm-level spatially-explicit stochastic compartmental transmission model incorporating six transmission routes including between-farm swine movements, vehicle movements, and local spread, to model the dissemination of ASF. We then examined the effectiveness of control actions similar to the ASF national response plan. The average number of secondary infections during the first 60 days of the outbreak was 49 finisher farms, 17 nursery farms, 5 sow farms, and less than one farm in other production types. The between-farm movements of swine were the predominant route of ASF transmission with an average contribution of 71.1%, while local spread and movement of vehicles were less critical with average contributions of 14.6% and 14.4%. We demonstrated that the combination of quarantine, depopulation, movement restrictions, contact tracing, and enhanced surveillance, was the most effective mitigation strategy, resulting in an average reduction of 79.0% of secondary cases by day 140 of the outbreak. Implementing these control actions led to a median of 495,619 depopulated animals, 357,789 diagnostic tests, and 54,522 movement permits. Our results suggest that the successful elimination of an ASF outbreak is likely to require the deployment of all control actions listed in the ASF national response plan for more than 140 days, as well as estimating the resources needed for depopulation, testing, and movement permits under these controls.

Predicting Suitable Areas for African Swine Fever Outbreaks in Wild Boars in South Korea and Their Implications for Managing High-Risk Pig Farms.

African swine fever (ASF) is a highly contagious disease affecting domestic pigs and wild boars, with no effective vaccine or treatment available. In South Korea, extensive measures have been implemented to prevent ASF transmission between wild boars and ASF spillover from wild boars to pig farm sectors, including the search for ASF-infected carcasses in mountainous forests and the installation of fences across wide areas of these forests. To determine the priority search range for infected carcasses and establish pig farm-centered quarantine measures, it is necessary to predict the specific path of ASF outbreaks in wild boars and identify pig farms at high risk of ASF spillover from wild boars. Here, we aimed to predict suitable areas and geographical paths for ASF outbreaks in wild boars using the MaxEnt model and shortest-path betweenness centrality analysis. The analysis identified a high frequency of ASF outbreaks in areas with a suitability value ≥0.4 on the suitability map and in areas within a 1.8 km range from the path on the shortest-path map, indicating these areas were high-risk zones for ASF outbreaks. Among the 5063 pig farms analyzed, 37 were in the high-risk zone on the suitability map, 499 were in the high-risk zone on the shortest-path map, and 9 were in both risk zones. Of the 51 pig farm sectors with a dense distribution of pig farms (kernel density ≥ 8), 25 sectors were in contact with or partially overlapped the high risk zone on the suitability map, 18 sectors were located within the high risk zone on the shortest-path map, and 14 sectors were located within both risk zones. These findings aided in determining the priority range for searches for wild boar carcasses and enabled the establishment of preemptive ASF prevention measures around the pig farming sectors that are at risk of ASF spillover from wild boars.

Risk Factor Impact on African Swine Fever Transmission in Different Extensive Pig Production Settings in Serbia.

The first case of ASF in a domestic pig population in Serbia was confirmed in 2019 in a backyard population. Today, outbreaks in wild boar and, more importantly, in domestic pigs are still occurring, although the government measures for ASF prevention are in place. The aim of this study was to determine critical risk factors and identify the possible reasons for ASF introduction into different extensive pig farms. The study was conducted on 26 extensive pig farms with confirmed ASF outbreaks, with data collected from beginning of 2020 to the end of 2022. Collected epidemiological data were divided into 21 main categories. After identifying specific values of variables as critical for ASF transmission, we identified nine important ASF transmission indicators as those variables for which at least 2/3 of the observed farms reported values critical for ASF transmission. Among them were type of holding, distance to hunting ground, farm/yard fencing, and home slaughtering; however, the hunting activity of pig holders, swill feeding, and feeding with mowed green mass were not included. We represented the data in the form of contingency tables to study associations between pairs of variables using Fisher's exact test. All pairs of variables in the group including type of holding, farm/yard fencing, domestic pig-wild boar contact, and hunting activity were significantly related; hunting activity of pig holders, holding pigs in backyards, unfenced yards, and domestic pig-wild boar contact were observed on the same farms. Free-range pig farming led to observed domestic pig-wild boar contact on all farms. The identified critical risk factors need to be strictly addressed to prevent the further spread of ASF to extensive farms and backyards in Serbia and elsewhere.

Fuzzy model for quantitative assessment of the epidemic risk of African Swine Fever within Australia.

African Swine Fever (ASF) has spread rapidly across different continents since 2007 and caused huge biosecurity threats and economic losses. Establishing an effective risk assessment model is of great importance for ASF prevention, especially for those ASF-free countries such as Australia. With a vast territory and an economy heavily relying on primary industry, Australia faces a threat from the spread of ASF. Although ordinary quarantine measures have been well-performed throughout Australia, there is still a need to develop an effective risk assessment model to understand the spread of ASF due to the strong transmission ability of ASF. In this paper, via a comprehensive literature review, and analyzing the transmission factors of ASF, we provide a fuzzy model to assess the epidemic risk of Australian states and territories, under the assumption that ASF has entered Australia. As demonstrated in this work, although the pandemic risk of ASF in Australia is relatively low, there is a risk of irregular and scattered outbreaks, with Victoria (VIC) and New South Wales (NSW) - Australia Capital Territory (NSW-ACT) showed the highest risk. The reliability of this model was also systematically tested by a conjoint analysis model. To our knowledge, this is the first study to comprehensively analyze the ASF epidemic risk in a country using fuzzy modeling. This work can provide an understanding of the risk ASF transmission within Australia based on the fuzzy modeling, the same methodology can also provide insights and useful information for the establishment of fuzzy models to perform the ASF risk assessment for other countries.

Complete genome analysis of African swine fever virus genotypes II, IX and XV from domestic pigs in Tanzania

African swine fever (ASF) caused by ASF virus (ASFV) is an infectious transboundary animal disease notifiable to the World Organization for Animal Health causing high mortality in domestic pigs and wild boars threatening the global domestic pig industry. To date, twenty-four ASFV genotypes have been described and currently genotypes II, IX, X, XV and XVI are known to be circulating in Tanzania. Despite the endemic status of ASF in Tanzania, only one complete genome of ASFV from the country has been described. This study describes the first complete genome sequence of ASFV genotype XV. In addition, the first Tanzanian complete genome of ASFV genotype IX and three ASFV strains belonging to genotype II collected during ASF outbreaks in domestic pigs in Tanzania were determined in this study using Illumina sequencing and comparative genomics analysis. The generated ASFV complete genome sequences ranged from 171,004 to 184,521 base pairs in length with an average GC content of 38.53% and encoded 152 to 187 open reading frames. The results of this study provide insights into the genomic structure of ASFV and can be used to monitor changes within the ASFV genome and improve our understanding of ASF transmission dynamics.

Epidemiological drivers and control strategies for African swine fever transmission cycles at a wildlife-livestock interface

Increasing reported outbreaks of African swine fever (ASF) at wildlife-livestock interfaces (where wild pigs and/or ticks interact with domestic pigs) have led to an increased interest in understanding the transmission dynamics and effective control strategies of the disease in these places. In such areas, the transmission cycles of ASF include a domestic pig cycle, a tick-domestic pig cycle, and a wild pig-tick-domestic pig cycle. A model that captures these cycles is used to explore the key parameters and control strategies (vaccination, isolation, and/or the use of an acaricide) for disease transmission. Using Latin hypercube sampling, the tick mortality and recruitment rates are found to be the key parameters for the spread of ASF. Numerical results show that early isolation of infected domestic pigs can be effective in controlling transmission only in the domestic pig cycle, whereas the use of an acaricide applied as a single strategy is not effective for any cycle. On the other hand, a strategy that combines these two strategies is effective in controlling transmission for all cycles, but its effectiveness is lower than that of the vaccination strategy. Thus, at a wildlife-livestock interface, vaccination is the best strategy, but where the vaccines are not yet available or affordable, a strategy that combines isolation and the use of an acaricide can be applied to control ASF transmission.

Inferring ASF transmission in domestic pigs and wild boars using a paired model iterative approach

The rapid spread of African swine fever (ASF) in recent years has once again raised awareness of the need to improve our preparedness in preventing and managing outbreaks, for which modelling-based forecasts can play an important role. This is even more important in the case of a disease such as ASF, involving several types of hosts, characterised by a high case-fatality rate and for which there is currently no treatment or vaccine. Within the framework of the ASF challenge, we proposed a modelling approach based on a stochastic mechanistic model and an inference procedure to estimate key transmission parameters from provided data (incomplete and noisy) and generate forecasts for unobserved time horizons. The model is partly data driven and composed of two modules, corresponding to epidemic and demographic dynamics in domestic pig and wild boar (WB) populations, interconnected through the networks of animal trade and/or spatial proximity. The inference consists in an iterative procedure, alternating between the two models and based on a criterion optimisation. Estimates of transmission and detection parameters appeared to be of similar magnitude for each of the three periods of the challenge, except for the transmission rates in WB population through contact with infectious individuals and carcasses, higher during the first period. The predicted number of infected domestic pig farms was in overall agreement with the data. The proportion of positive tested WB was overestimated, but with a trend close to that observed in the data. Comparison of the spatial simulated and observed distributions of detected cases also showed an overestimation of the spread of the pathogen within WB metapopulation. Beyond the quantitative results and the inherent difficulties of real-time forecasting, we built a modelling framework that is flexible enough to accommodate changes in transmission processes and control measures that may occur during an epidemic emergency.

Mechanistic modelling for African swine fever transmission in the Republic of Korea.

Under the current African swine fever (ASF) epidemic situation, a science-based ASF-control strategy is required. An ASF transmission mechanistic model can be used to understand the disease transmission dynamics among susceptible epidemiological units and evaluate the effectiveness of an ASF-control strategy by simulating disease spread results with different control options. The force of infection, which is the probability that a susceptible epidemiological unit becomes infected, could be estimated by applying an ASF transmission mechanistic model. The government needs to plan an ASF-control strategy based on an ASF transmission mechanistic model.

AFRICAN SWINE FEVER: A BIOSECURITY CHALLENGE FOR DOMESTIC PIG PRODUCTION IN SERBIA

African swine fever (ASF) is currently the most important challenge for domestic pig production worldwide. The virus reached Eurasia in 2007, and is today affecting more than half of European Union member countries. Among Western Balkan countries, Serbia suffered the first case of ASF in a backyard holding in 2019. Since then, numerous outbreaks in domestic pigs and wild boar have been reported throughout the country despite the efforts of the veterinary authorities to control the disease. The lack of an effective vaccine is one of the main constraints, and the only currently available option to prevent further ASF infections is the application of strict biosecurity measures. Regarding biosecurity, backyard pig producers and smallholding farmers in Serbia have substantial gaps in the knowledge and fail to comply with safe production behaviour that favours the spread of ASF virus. In the currently prevailing smallholder and backyards farming systems, farm biosecurity is largely non-existent. The aim of this review was to identify specific ASF-risks factors in the current pig production system and gaps in biosecurity measures related to the human activities recognised as social and cultural identity in Serbia. Moreover, the main risk factors for ASF spreading and transmission at the domestic/wild boar interface, biosecurity practices in different production systems, and possible future control measures and awareness campaigns are discussed.

REVIEW: MENINGKATKAN POPULASI TERNAK BABI MELALUI TEKNOLOGI REPRODUKSI PASCA AFRICAN SWINE FEVER

The purpose of writing this review is to determine the role of reproductive technology in increasing the population of pigs after the African Swine Fever (ASF) outbreak. The method used in writing this review is to search for published research articles using Google search and Science direct with the keywords African swine fever and Artificial Insemination (AI). The results of this review show that ASF can reduce the population due to the high mortality rate, ASF can be transmitted through the reproductive organs but this can be overcome by utilizing IB reproductive technology. In addition, AI reproductive technology is also one of the reproductive technologies that can be used to increase the livestock population after the ASF outbreak. Based on the review, it can be ensured that artificial insemination reproductive technology is able to prevent ASF transmission and increase livestock populations after the ASF outbreak.

Estimation of R0 for the Spread of the First ASF Epidemic in Italy from Fresh Carcasses.

After fifty years of spread in the European continent, the African swine fever (ASF) virus was detected for the first time in the north of Italy (Piedmont) in a wild boar carcass in December, 2021. During the first six months of the epidemic, the central role of wild boars in disease transmission was confirmed by more than 200 outbreaks, which occurred in two different areas declared as infected. The virus entered a domestic pig farm in the second temporal cluster identified in the center of the country (Lazio). Understanding ASF dynamics in wild boars is a prerequisite for preventing the spread, and for designing and applying effective surveillance and control plans. The aim of this work was to describe and evaluate the data collected during the first six months of the ASF epidemic in Italy, and to estimate the basic reproduction number (R0) in order to quantify the extent of disease spread. The R0 estimates were significantly different for the two spatio-temporal clusters of ASF in Italy, and they identified the two infected areas based on the time necessary for the number of cases to double (td) and on an exponential decay model. These results (R0 = 1.41 in Piedmont and 1.66 in Lazio) provide quantitative knowledge on the epidemiology of ASF in Italy. These parameters could represent a fundamental tool for modeling country-specific ASF transmission and for monitoring both the spread and sampling effort needed to detect the disease early.

Effects of habitat fragmentation and hunting activities on African swine fever dynamics among wild boar populations

African Swine Fever (ASF) has been slowly but steadily increasing its endemic range throughout Europe, posing an imminent risk to the pig industry. ASF transmission among wild boar occurs mainly through wild boar population movements, hence wild boar presence and density are important risk factors for introducing, maintaining, and spreading the disease. The understanding of wild boar population dynamics and their role in ASF transmission and persistence remains limited. It is crucial to gain knowledge in this area to improve wildlife management while minimizing the risks for ASF introduction and spread. We adapted an individual-based spatio-temporal stochastic model developed by Halasa et al. (2019) and tailored it to two regions in France. The model assessed yearly hunting activity, the carcass persistence seasonality, and the specific landscape characteristics of the Franco-Belgian border region and the Pyrénées-Atlantiques department. Following the establishment of local population dynamics through preliminary runs of the model, the model was run 100 iterations over 8 years in the two study areas where ASF was randomly seeded after the 2nd year of simulation. For each scenario, the model was initiated with 500 wild boar groups randomly spread across the study areas. Hunting activities were included and excluded to assess the impact on population growth and ASF spread. Results showed an ever-growing wild boar population for all scenarios, which was balanced when hunting activities were included. When introducing ASF, the wild boar populations were dramatically impacted in both areas with a decrease of 63 % of the population at the Franco-Belgian border and 86 % in the Pyrénées-Atlantiques department. Habitat fragmentation and landscape connectivity were highlighted as important factors shaping ASF propagation. The Franco-Belgian border, which had the most fragmented habitat with unsuitable areas for wild boars, was shown to limit wild boar movements, reducing the probability, and spread of ASF across the landscape. The lack of connectivity was reflected in a less effective transmission and lower number of infected groups (406 versus 467). In contrast, the epidemic duration was lengthened in the fragmented habitat compared to the homogenous area (2.6 years vs 1.6 years). This study provided information on defining and implementing control measures in case of an ASF incursion, since delimitation of the area via fences artificially induces landscape fragmentation, which is important for controlling ASF outbreaks.

Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies

African swine fever (ASF), caused by the African swine fever virus (ASFV), is highly virulent in domestic pigs and wild boar (Sus scrofa), causing up to 100% mortality. The recent epidemic of ASF in Europe has had a serious economic impact and poses a threat to global food security. Unfortunately, there is no effective treatment or vaccine against ASFV, limiting the available disease management strategies. Mathematical models allow us to further our understanding of infectious disease dynamics and evaluate the efficacy of disease management strategies. The ASF Challenge, organised by the French National Research Institute for Agriculture, Food, and the Environment, aimed to expand the development of ASF transmission models to inform policy makers in a timely manner. Here, we present the model and associated projections produced by our team during the challenge. We developed a stochastic model combining transmission between wild boar and domestic pigs, which was calibrated to synthetic data corresponding to different phases describing the epidemic progression. The model was then used to produce forward projections describing the likely temporal evolution of the epidemic under various disease management scenarios. Despite the interventions implemented, long-term projections forecasted persistence of ASFV in wild boar, and hence repeated outbreaks in domestic pigs. A key finding was that it is important to consider the timescale over which different measures are evaluated: interventions that have only limited effectiveness in the short term may yield substantial long-term benefits. Our model has several limitations, partly because it was developed in real-time. Nonetheless, it can inform understanding of the likely development of ASF epidemics and the efficacy of disease management strategies, should the virus continue its spread in Europe.

Pigkeepers’ knowledge and perceptions regarding African swine fever and the control measures in Estonia

African swine fever (ASF) has been present in Estonia since 2014, and pigkeepers play a major role in controlling the spread of viral infection in domestic pigs. Participatory epidemiology may provide insight into livestock keepers’ existing attitudes and compliance with implementing control strategies. By conducting focus group discussions and using participatory epidemiology tools, this study aimed to reveal pigkeepers’ knowledge and awareness of ASF clinical signs, transmission routes, and preventive measures. Furthermore, opinions including trust in stakeholders in ASF control, acceptability of ASF eradication, and control measures by pigkeepers in Estonia were identified. The most indicative ASF signs in pigs were “increased mortality” and “fever, inappetence, lethargy”. The highest risk of virus introduction into the herd was designated to “agricultural machinery, vehicles”, “rodents, birds, insects”, and “people”. “Fencing” was the most liked ASF preventive measure, while “training of staff in biosecurity and informing the visitors” was considered the most effective measure. The least accepted ASF eradication measure was “culling of all animals on the farm”. Generally, pigkeepers perceived that healthy animals should not be culled but only ASF-infected pigs. Additionally, healthy pigs could be slaughtered and used for the production of heat-treated canned meat. “Destroying the feed” of ASF-infected farms was not favoured because some pigkeepers proposed using it for other animal species. Regarding ASF territorial restrictions (zoning), “lower meat prices” and “economic losses” were regarded as consequences with the greatest impact. Pigkeepers ranked trust in “Veterinary Authority and Ministry of Rural Affairs” regarding their role in ASF prevention and control as high while perceiving themselves as the most trustworthy stakeholder within the ASF network. This study demonstrates a generally good level of awareness among the pigkeepers in Estonia concerning the clinical manifestation of ASF, the most relevant transmission routes of the virus for their farms, and preventive measures for ASF. Pigkeepers are aware of their own role in preventing ASF, and there is a high level of trust between them and government authorities. Additional efforts are needed from authorities to communicate better the purpose of some ASF control and eradication measures to the pigkeepers. Further incentives are required to support the implementation of costly biosecurity measures, assure compliance, and mitigate the consequences of these measures.

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.