These carcasses are to be buried at the place of discovery after being sampled. Search areas are concentrated in and around fenced infected areas, and when a carcass is found, they are obligated to report it to the municipality. The search teams are composed of a variety of people, including civilians, hunters, and military personnel, and the government facilitates the search by offering a bounty for the discovery of wild boar. In South Korea, government-led search teams are organized nationwide, by region, to search for wild boar on a constant basis. Since then, the government has been actively working on population control by searching for and hunting wild boar, as well as installing fences around infected areas to prevent the spread of infection within the wild boar population. Immediately after confirmation of the wild boar case, fencing around the case-reported area was implemented to contain further spread of ASF infection in wild boar. About half a month later, the first ASF case in wild boar was reported along the border with North Korea, about 33.5 km distant from the first reported ASF-outbreak pig farm. The first ASF outbreak was confirmed in September 2019 at a pig farm in the northwestern part of the country. Contrary to this, the majority of notifications in South Korea have been reported in wild boar populations. Most of these ASF-affected countries reported the disease in domestic pig sectors, which was presumably due to inadequate biosecurity measures and illegal trade of infected pigs, as well as the transport of contaminated pork products. In Asia, since the first ASF notification was reported in China in 2018, outbreaks have been confirmed in 17 countries (China, Mongolia, Vietnam, Cambodia, North Korea, Laos, Myanmar, the Philippines, South Korea, East Timor, Indonesia, Papua New Guinea, India, Malaysia, Bhutan, Thailand, and Nepal) as of the end of September 2022. Infected carcasses could contaminate soil and be exposed to other wild boar, which heightens the risk of disease spread. ![]() Feces and urine are also infectious the half-life of the virus in urine is 15 days depending on the environmental temperature, and in feces, it is reported to be 5–8 days, but viral DNA can be detected for up to 2–4 years. ![]() In the case of raw meat, it can survive for more than three months in meat and offal. The virus is shed in large quantities in the blood where the virus can survive for 15 weeks at room temperature, months at 4 ☌, and indefinitely when frozen. It is well known that the virus can maintain its infectivity for a long time under various conditions. One of the main characteristics of ASFV is its high environmental resistance. In addition, indirect contact with ASFV-contaminated material may play an important role in the spread of the virus over long distances. Susceptible animals can become infected via direct contact with infected individuals. The clinical signs exhibited by infected individuals vary and are classified into four main stages based on clinical presentations and pathological lesions: peracute, acute, subacute, and chronic. Pigs, including wild boar, are generally regarded as susceptible hosts. ![]() ASFV is a double-stranded DNA virus of about 170–190 kbp and belongs to the family Asfaviridae. The results obtained would be useful for selecting priority areas for ASF control and would greatly assist in identifying efficient vaccination areas in the future.Īfrican swine fever (ASF), caused by the ASF virus (ASFV), is one of the most important transboundary animal diseases. We identified factors influencing ASF expansion based on spatio-temporal clusters. In a scenario only considering direct transmission among wild boar, R 0 ranged from 1.01 to 1.5 with an average of 1.10, while, in another scenario including indirect transmission via an infected carcass, R 0 ranged from 1.03 to 4.38 with an average of 1.56. The GLLR model analysis identified factors influencing cluster formation and indicated the possibility of estimating ASF epidemic areas based on environmental conditions. The cluster analysis resulted in the detection of 17 spatio-temporal clusters. In the meantime, the basic reproduction number (R 0) for each cluster was estimated to understand the growth of the epidemic. Secondly, generalized linear logistic regression (GLLR) model analysis was performed to identify environmental factors contributing to cluster formation. In this study, we first performed a spatio-temporal cluster analysis to understand ASF spread in wild boar. Since the first confirmation of African swine fever (ASF) in domestic pig farms in South Korea in September 2019, ASF continues to expand and most notifications have been reported in wild boar populations.
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