Bae, Kyoung-Eun
(Department of Biomedicine Health Science, College of Medicine, The Catholic University of Korea)
,
Chang, Yoon Kyung
(Department of Parasitology, College of Medicine, The Catholic University of Korea)
,
Kim, Tong-Soo
(Department of Parasitology and Tropical Medicine and Inha Research Institute for Medical Sciences, Inha University School of Medicine)
,
Hong, Sung-Jong
(Department of Medical Environmental Biology, Chung-Ang University College of Medicine)
,
Ahn, Hye-Jin
(Department of Parasitology, College of Medicine, The Catholic University of Korea)
,
Nam, Ho-Woo
(Department of Parasitology, College of Medicine, The Catholic University of Korea)
,
Kim, Dongjae
(Department of Biomedicine Health Science, College of Medicine, The Catholic University of Korea)
This study was performed to find out the clusters with high parasite infection risk to discuss the geographical pattern. Clusters were detected using SatScan software, which is a statistical spatial scan program using Kulldorff's scan statistic. Information on the parasitic infection cases in Korea ...
This study was performed to find out the clusters with high parasite infection risk to discuss the geographical pattern. Clusters were detected using SatScan software, which is a statistical spatial scan program using Kulldorff's scan statistic. Information on the parasitic infection cases in Korea 2011-2019 were collected from the Korea Centers for Disease Control and Prevention. Clusters of Ascaris lumbricoides infection were detected in Jeollabuk-do, and T. trichiura in Ulsan, Busan, and Gyeongsangnam-do. C. sinensis clusters were detected in Ulsan, Daegu, Busan, Gyeongsangnamdo, and Gyeongsangbuk-do. Clusters of intestinal trematodes were detected in Ulsan, Busan, and Gyeongsangnam-do. P. westermani cluster was found in Jeollabuk-do. E. vermicularis clusters were distributed in Gangwon-do, Jeju-do, Daegu, Daejeon, and Gwangju. This clustering information can be referred for surveillance and control on the parasitic infection outbreak in the infection-prone areas.
This study was performed to find out the clusters with high parasite infection risk to discuss the geographical pattern. Clusters were detected using SatScan software, which is a statistical spatial scan program using Kulldorff's scan statistic. Information on the parasitic infection cases in Korea 2011-2019 were collected from the Korea Centers for Disease Control and Prevention. Clusters of Ascaris lumbricoides infection were detected in Jeollabuk-do, and T. trichiura in Ulsan, Busan, and Gyeongsangnam-do. C. sinensis clusters were detected in Ulsan, Daegu, Busan, Gyeongsangnamdo, and Gyeongsangbuk-do. Clusters of intestinal trematodes were detected in Ulsan, Busan, and Gyeongsangnam-do. P. westermani cluster was found in Jeollabuk-do. E. vermicularis clusters were distributed in Gangwon-do, Jeju-do, Daegu, Daejeon, and Gwangju. This clustering information can be referred for surveillance and control on the parasitic infection outbreak in the infection-prone areas.
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제안 방법
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.
This study has provided the clusters with high risk of parasitic infection in Korea from 2011 to 2019, by using spatial scan analysis. Depending on the transmission of infections, the infections are respectively divided into soil-borne, fishborne, and contact-borne.
성능/효과
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 Gyeong-sangnam-do region had notably high risk of indicating T. trichiura infection.
2). The 3 fish-borne parasites consisted about 83% of the reported case data showing the prevalence of consuming raw or undercooked food. This culinary tradition came from the previous generation who had fresh-water fish and shellfish as a source of protein during famine.
[4]. The parasitic infections were of Ascaris lumbricoides, Trichuris trichiura, Clonorchis sinensis, Paragonimus westermani, intestinal trematodes and Enterobius vermicularis.
The secondary cluster was Daejeon. With 25% maximum cluster size, Busan, Gyeongsangnam-do and Ulsan was the most like-ly 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 Gyeong-sangnam-do region had notably high risk of indicating T.
참고문헌 (13)
1 Korea Centers for Disease Control and Prevention, Korea Association of Health Promotion Prevalence of Intestinal Parasitic Infection in Korea The 7th Report Seoul, Korea 2004
2 Korea Centers for Disease Control and Prevention, Korea Association of Health Promotion Prevalence of intestinal parasitic infection in Korea–The 8th Report Seoul, Korea 2012
3 Kulldorff M A spatial scan statistic Communications in Statistics—Theory and Methods 1997 26 1481 1496
4 Infectious Disease Portal Parasitic infection statistics [Internet] [cited 2020 Feb 13]. Available from: https://www.cdc.go.kr/npt/biz/npp/iss/parasitosisStatisticsMain.do
5 Korean Statistical Information Service Resident Population by City, County, and District [Internet] [cited 2020 Mar 12]. Available from: http://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1B040A3&conn_path=I3
6 Kulldorff M SaTScan TM User Guide for version 9.6 2018
7 Lee KJ Hwang MH Han SH Yang EJ A First steps for understanding and using spatial statistics analysis Korea Research Institute for Human Settlements 2015
8 Kulldorff M Nagarwalla N Spatial disease clusters: detection and inference Stat Med 1995 14 799 810 10.1002/sim.4780140809 7644860
10 Chen J Roth RE Naito AT Lengerich EJ Maceachren AM Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality Int J Health Geogr 2008 7 57 10.1186/1476-072X-7-57 18992163
11 Kulldorff M An isotonic spatial scan statistic for geographical disease surveillance J Nat Inst Publ Health 1999 48 94 101
12 Azage M Kumie A Worku A Bagtzoglou AC Childhood diarrhea exhibits spatiotemporal variation in northwest Ethiopia: a SaTScan spatial statistical analysis PLoS One 2015 10 e0144690 10.1371/journal.pone.0144690 26690058
13 Kim TS Cho SH Huh S Kong Y Sohn WM Hwang SS Chai JY Lee SH Park YK Oh DK Lee JK A nationwide survey on the prevalence of intestinal parasitic infections in the Republic of Korea 2004 Korean J Parasitol 2009 47 37 47 10.3347/kjp.2009.47.1.37 19290090
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