Space-time cluster analysis of foot-and-mouth disease in South Korea
MetadataShow full item record
The 2010/2011 South Korea Foot-and-Mouth Disease (FMD) epidemic was one of the most serious outbreaks in its history, however, insufficient attention was paid to investigate the disease pattern. The objective of this research is to characterize the patter of disease cases using space-time cluster detection methods. The Ripley’s K-function and space-time scan statistic were used to perform the spatial and spatio-temporal cluster detection. The heterogeneity of population at risk was taken into account by introducing the kernel density estimation of disease cases in K-function and using discrete Poisson model in the space-time scan statistic. We conducted the cluster analysis based on georeferenced FMD occurrence data and the national census data of domestic farms. The global cluster analysis result suggested a short-range spatial clustering, which could be observed at a distance smaller than 18 km, for pig cases, but no global clustering was found for cattle cases. Five individual clusters were identified for cattle cases and three were identified for pig cases using space-time scan statistic. The result of cluster detection presented the pattern of disease cases during the epidemic and showed the spatial difference among disease clusters, which indicated the influence of local conditions on the disease clustering.