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Identifying risk clusters for African swine fever in Korea by developing statistical models
Kyeong Tae Ko1, Janghun Oh1, Changdae Son1
1Department of Statistics, Kyungpook National University, Daegu, Republic of Korea.
Frontiers in Veterinary Science
|August 8, 2024
Summary
African swine fever (ASF) risk clusters were identified in South Korea, showing a southward trend. This research aids in targeted interventions to control the spread of this highly fatal animal disease.
Area of Science:
- Veterinary Epidemiology
- Disease Ecology
- Wildlife Health
Background:
- African swine fever (ASF) is a highly contagious and lethal viral disease affecting domestic and wild pigs.
- Early identification of high-risk areas and understanding transmission patterns are critical for rapid containment.
- Wild boar populations are a key factor in the epidemiology and spread of ASF.
Purpose of the Study:
- To investigate the spatial and temporal heterogeneity of ASF in the Republic of Korea using wild boar carcass surveillance data.
- To identify high-risk clusters and analyze transmission dynamics of ASF.
- To develop a statistical model for risk assessment and resource allocation in disease management.
Main Methods:
- Analysis of surveillance data on ASF-infected wild boar carcasses from Late 2022 to Early 2023.
- Development of a rank-based statistical model to estimate weekly carcass numbers per district.
- Accounting for underestimation of risk and observation error due to varying surveillance intensities.
Main Results:
- A distinct southward annual propagation pattern of ASF-infected carcasses was observed.
- Risk clusters were consistently identified in northwestern Gyeongbuk, north Chungbuk, and southwestern Gangwon regions during both study periods.
- Observed and estimated risk cluster analyses yielded similar results, confirming regional hotspots.
Conclusions:
- The study enhances understanding of ASF spatial dynamics in wild boar populations.
- Identified risk areas require urgent and focused intervention for effective disease control.
- Findings provide crucial data for targeted resource allocation and improved ASF management strategies.
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