Development of an Effective Oral Vaccine Dissemination Strategy against Classical Swine Fever for Wild Boar in Gifu Prefecture, Japan

Abstract

In September 2018, classical swine fever (CSF) reemerged in Japan after more than a quarter of a century. After the first notification on a pig farm, wild boars positive for CSF were found continuously in the surrounding area. Gifu was the first prefecture in Japan to disseminate oral vaccines to wild boars in March 2019, with vaccines spread to approximately 14,000 sites between 2019 and 2020. While these diligent measures seemed to have shown some effectiveness, several vaccine spray sites remained without wild boar emergence. Based on the vaccine dissemination records from these periods, this study conducted a statistical analysis to propose more effective vaccine dissemination sites. First, a generalized linear mixed model was used to identify factors correlated with wild boar emergence. Then, two spatial interpolation methods, inverse distance weighted (IDW) and Kriging, were adopted to create a probability map of wild boar emergence for the entire Gifu Prefecture. The analysis showed a positive correlation between wild boar emergence and the appearance of raccoons, raccoon dogs, and crows as well as road density and wild boar distribution index. In particular, raccoon (OR: 1.83, 95%CI: 1.25–2.68, p < 0.001), raccoon dog (OR: 1.81, 95%CI: 1.25–2.66, p < 0.001), and medium level road density (OR: 1.56, 95%CI: 1.04–2.39, p = 0.04) were strongly correlated with wild boar emergence. The spatial interpolation approach resulted in better prediction accuracy for the Kriging method than for IDW by the root mean square error, but both approaches identified a high wild boar appearance probability area in southeastern Gifu and a low appearance probability area in central Gifu. Here we have demonstrated a tool to effectively disperse oral vaccine to wildlife.

Application of machine learning with large-scale data for an effective vaccination against classical swine fever for wild boar in Japan

“…In the previous study, we performed a generalized linear mixed model (GLMM) analysis based on data from sensor cameras installed at approximately 10% of all vaccine dispersal points to identify areas where wild boar was most likely to appear. We found a positive correlation between the emergence of other wildlife (raccoon, raccoon dog, and crow) and the emergence of wild boar 20 . In addition, road density and vegetation were also estimated to influence wild boar emergence.…”

“…The variable of vaccine dissemination season, a categorical variable, was subjected to a label encoding process. Our previous study found a correlation between the emergence of other animals and wild boar 20 , and therefore it may also influence the vaccine uptake rate of wild boar. The vaccine ingestion variable by other animals was treated as binary data for the same reasons as in the response variable setting.…”

“…To measure the effectiveness of the vaccination application, the remaining vaccine or vaccine packet was collected 5 days after application and the presence or absence of feeding by wild boar was determined based on the shape of the remaining vaccine packet 19 . Consequently, vaccine ingestion by wild boars was confirmed in approximately 30% of the dispersal sites 20 . The expansion of infected areas and the prolonged infection period will burden the economy, as will the cost of control measures.…”

Strategies for Transboundary Swine Disease Management in Asian Islands: Foot and Mouth Disease, Classical Swine Fever, and African Swine Fever in Taiwan, Japan, and the Philippines

“…MAFF took a comprehensive approach, intensifying surveillance efforts in regions where CSF-affected wild boars were identified. In March 2019, an oral vaccine, commonly referred to as a bait vaccine, was strategically administered to wild boars in selected prefectures with positive CSF cases and in surrounding areas [ 30 ]. A study on CSF dynamics and wild boar bait vaccination in Japan found a 12.1 percentage point increase (95% CI: 7.8–16.5) in antibody prevalence from the 2019 vaccine campaigns.…”

Geospatial analysis for strategic wildlife disease surveillance: African swine fever in South Korea (2019–2021)

“…Here, we selected factors that could affect surveillance performance based on insights from previous wild boar research in Asia [22][23][24], Korean topographic features [25], and data availability. Five key factors were chosen: elevation, distance from the nearest roads, human PLOS ONE population density, percent tree cover (cover tree), and pig density.…”