| Autor: |
Satoshi Ito, Jaime Bosch, Cecilia Aguilar-Vega, Hyunkyu Jeong, Jose Manuel Sánchez-Vizcaíno |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
PLoS ONE, Vol 19, Iss 6, p e0305702 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0305702 |
| Popis: |
Since the confirmation of African swine fever (ASF) in South Korea in 2019, its spread, predominantly in wild boars, has been a significant concern. A key factor in this situation is the lack of identification of risk factors by surveillance bias. The unique orography, characterized by high mountains, complicates search efforts, leading to overlooked or delayed case detection and posing risks to the swine industry. Additionally, shared rivers with neighboring country present a continual threat of virus entry. This study employs geospatial analysis and statistical methods to 1) identify areas at high risk of ASF occurrence but possibly under-surveilled, and 2) indicate strategic surveillance points for monitoring the risk of ASF virus entry through water bodies and basin influences. Pearson's rho test indicated that elevation (rho = -0.908, p-value < 0.001) and distance from roads (rho = -0.979, p-value < 0.001) may have a significant impact on limiting surveillance activities. A map of potential under-surveilled areas was created considering these results and was validated by a chi-square goodness-of-fit test (X-square = 208.03, df = 1, p-value < 0.001). The strong negative correlation (rho = -0.997, p-value |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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