This study was performed under the regulation of the IRB Committee of The Catholic University of Korea (No. MIRB-20200529-002). This research adhered to the tenets of the Declaration of Helsinki.

The nationwide parasitic infection cases reported for 9 years (2011–2019) were collected from 16 administrative districts by the Korea Disease Control and Prevention Agency (KCDA) [4]. The parasitic infections were of Ascaris lumbricoides, Trichuris trichiura, Clonorchis sinensis, Paragonimus westermani, intestinal trematodes and Enterobius vermicularis.

The population data of 16 administrative divisions 2011–2019 were obtained from the Korean Statistical Information Service [5]. The geographical locations of the infection cases were set to the latitude and longitude of administrative center as the search point since the case data were compiled by administrative district unit. The population and number of parasitic infection cases were summed up as accumulated counts and numbers for the 9 years by administrative district (Table 1).

SaTScan Software using the spatial scan statistic [3] were employed to cluster the parasitic infection cases and to evaluate statistical significance of the located clusters through simulation. The discrete Poisson model was used since the parasitic infection case data were linked to their background population at risk [6]. The spatial scan statistic detected clusters by creating a circular window on a map and scanning the study area by varying a window size. The null hypothesis is that disease risk of both inside and outside of the window are the same, while the alternative hypothesis is that disease risk within the window is different from the outside [7]. A likelihood ratio for every window was calculated and the maximum likelihood ratio was defined as the test statistic. The window with the maximum likelihood ratio was identified as the most likely cluster, the significant cluster which is least likely to have occurred by chance while other windows were classified as secondary clusters. The window size determines a percentage of the population at risk within the window and SaTscan Software provides its users an option to set maximum cluster size, the upper bound of window size. [6,8]. By increasing window size, its radius expands until the risk population within the window reaches the set value. If other administrative districts are located within the radius, the cluster is created by combining 2 districts into one and becomes larger cluster [7]. Therefore, increase of the window size resulted in larger clusters by merging of adjacent administrative districts in the radius [7,9]. It is important to find appropriate set value of cluster size because large value could hide effect of small core clusters, and small value could overlook the regional pattern of clusters [10]. This study adapted 5%, 15%, and 25% as the values to spot the cluster in different window size. Statistical significance of the clusters was calculated using the Monte Carlo simulations [11,12] and expressed as p-value. A significance level of alpha <0.05 was used as a standard. R program (ver. 4.0.1) was used to visualize cluster patterns on a map. The clusters were numbered in order of likelihood ratio. This study analyzed accumulated data for 9 years, 2011–2019, without taking time into account.

With 5% maximum cluster size, Ulsan, Daegu, Jeju-do, and Gangwon-do were clustered. Ulsan was the most likely cluster (LLR) with relative risk (RR) of 6.2, indicating that total parasite infection risk in Ulsan was 6.2 times higher than in the other districts. Followed were Daegu, Jeju-do and Gangwon-do in order of their likelihood ratio. With 15% maximum window size, Busan and Gyeongsangnam-do was the most likely cluster, indicating parasitic infection risk in Busan and Gyeongsangnam-do area was 8.7 times higher than other areas. With 25% maximum window size, Busan, Gyeongsangnam-do, Ulsan and Daegu were the most likely cluster, indicating the total parasite infection risk in these districts was 15 times higher than in the other districts (Table 2). The general parasitic infection 2011–2019 showed that core outbreaks were prominent in Ulsan, Daegu, and Jeju-do while the regional outbreak pattern was found in the southeastern region such as Busan, Gyeongsangnam-do, Ulsan, and Daegu (Fig. 1).

With 5% maximum cluster size, the cases of A. lumbricoides were most likely cluster in Jeollabuk-do, indicating the risk of A. lumbricoides infection was 8.7 times higher in Jeollabuk-do than other areas. The secondary cluster was Daejeon. With 15% of maximum cluster size, the most likely cluster was Jeollabuk-do and Daejeon. Clustering with 25% window was same to that of 15%. The cases of A. lumbricoides infection were mainly distributed in Jeollabuk-do.

T. trichiura with 5% maximum cluster size, the most likely cluster was Ulsan with relative risk of 2.4 while secondary clusters were Daejeon and Daegu. With 15% maximum cluster size, Busan and Gyeongsangnam-do was the most likely cluster with relative risk of 9.6, indicating T. trichiura infection risk was 9.6 times higher in Busan and Gyeongsangnam-do. The secondary cluster was Daejeon. With 25% maximum cluster size, Busan, Gyeongsangnam-do and Ulsan was the most likely cluster with relative risk of 10, indicating T. trichiura infection in Busan, Gyeongsangnam-do and Ulsan area was 10 times higher than other regions (Table 3). Overall, 15% and 25% analysis showed that big clusters including Busan and Gyeongsangnam-do region had notably high risk of indicating T. trichiura infection.

C. sinensis with 5% maximum cluster size, Ulsan was the most likely cluster with relative risk of 8.5, indicating C. sinensis infection in Ulsan was 8.5 times higher than other areas. The secondary cluster was Daegu. With 15% maximum cluster size, Busan and Gyeongsangnam-do was the most likely cluster with relative risk of 9.7. Gyeongsangbuk-do and Daegu was the secondary cluster. With 25% maximum cluster size, Busan, Gyeongsangnam-do, Ulsan and Daegu were the most likely cluster with relative risk of 27.2. Spatial scan analysis on the C. sinensis-infected cases showed a consistent pattern in every cluster size that the C. sinensis infection risk was prominent in Gyeongsangnam-do (Table 4).

For intestinal trematodes, with 5% maximum cluster size, the most likely cluster was Ulsan with relative risk of 2.2, indicating that the intestinal trematode infections in Ulsan was 2.2 times higher than in the other areas. With 15% maximum cluster size, the most likely cluster was Busan and Gyeongsangnam-do with relative risk of 28.4. With 25% maximum cluster size, the most likely cluster was Busan, Gyeongsangnam-do and Ulsan with relative risk of 33.7. In summary, the intestinal trematode infection was of high risk in Gyeongsangnam-do region.

The clusters of P. westermani infections with 5%, 15%, and 25% window size were all same. The most likely cluster was in Jeollabuk-do with relative risk of 16.9.

With 5% maximum cluster size, Gangwon-do was the most likely cluster with relative risk of 16, indicating E. vermicularis infection risk in Gangwon-do was 16 times higher than in the other regions. The secondary cluster was in Jeju-do followed by Daegu, Daejeon and Gwangju. Jeju-do, however, showed exceptionally relative risk of 24.51 (Table 5). In E. vermicularis infection analysis, the results of 15% and 25% windows were the same to that of 5% window. The E. vermicularis infections distributed all over the study regions, while Gangwon-do and Jeju-do showed high risk of enterobiasis.