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Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?

OBJECTIVES: A hierarchical generalized linear model (HGLM) was applied to estimate the transmission pattern of scrub typhus from 2001 to 2011 in the Republic of Korea, based on spatial and temporal correlation. METHODS: Based on the descriptive statistics of scrub typhus incidence from 2001 to 2011...

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Autores principales: Noh, Maengseok, Lee, Youngjo, Chu, Chaeshin, Gwack, Jin, Youn, Seung-Ki, Huh, Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Centers for Disease Control and Prevention 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3747676/
https://www.ncbi.nlm.nih.gov/pubmed/24159528
http://dx.doi.org/10.1016/j.phrp.2013.01.002
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author Noh, Maengseok
Lee, Youngjo
Chu, Chaeshin
Gwack, Jin
Youn, Seung-Ki
Huh, Sun
author_facet Noh, Maengseok
Lee, Youngjo
Chu, Chaeshin
Gwack, Jin
Youn, Seung-Ki
Huh, Sun
author_sort Noh, Maengseok
collection PubMed
description OBJECTIVES: A hierarchical generalized linear model (HGLM) was applied to estimate the transmission pattern of scrub typhus from 2001 to 2011 in the Republic of Korea, based on spatial and temporal correlation. METHODS: Based on the descriptive statistics of scrub typhus incidence from 2001 to 2011 reported to the Korean Centers for Disease Control and Prevention, the spatial and temporal correlations were estimated by HGLM. Incidences according to age, sex, and year were also estimated by the best-fit model out of nine HGLMs. A disease map was drawn to view the annual regional spread of the disease. RESULTS: The total number of scrub typhus cases reported from 2001 to 2011 was 51,136: male, 18,628 (36.4%); female, 32,508 (63.6%). The best-fit model selected was a combination of the spatial model (Markov random-field model) and temporal model (first order autoregressive model) of scrub typhus transmission. The peak incidence was 28.80 per 100,000 persons in early October and the peak incidence was 40.17 per 100,000 persons in those aged 63.3 years old by the best-fit HGLM. The disease map showed the spread of disease from the southern central area to a nationwide area, excepting Gangwon-do (province), Gyeongsangbuk-do (province), and Seoul. CONCLUSION: In the transmission of scrub typhus in Korea, there was a correlation to the incidence of adjacent areas, as well as that of the previous year. According to the disease map, we are unlikely to see any decrease in the incidence in the near future, unless ongoing aggressive measures to prevent the exposure to the vector, chigger mites, in rural areas, are put into place.
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spelling pubmed-37476762013-10-24 Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea? Noh, Maengseok Lee, Youngjo Chu, Chaeshin Gwack, Jin Youn, Seung-Ki Huh, Sun Osong Public Health Res Perspect Original Article OBJECTIVES: A hierarchical generalized linear model (HGLM) was applied to estimate the transmission pattern of scrub typhus from 2001 to 2011 in the Republic of Korea, based on spatial and temporal correlation. METHODS: Based on the descriptive statistics of scrub typhus incidence from 2001 to 2011 reported to the Korean Centers for Disease Control and Prevention, the spatial and temporal correlations were estimated by HGLM. Incidences according to age, sex, and year were also estimated by the best-fit model out of nine HGLMs. A disease map was drawn to view the annual regional spread of the disease. RESULTS: The total number of scrub typhus cases reported from 2001 to 2011 was 51,136: male, 18,628 (36.4%); female, 32,508 (63.6%). The best-fit model selected was a combination of the spatial model (Markov random-field model) and temporal model (first order autoregressive model) of scrub typhus transmission. The peak incidence was 28.80 per 100,000 persons in early October and the peak incidence was 40.17 per 100,000 persons in those aged 63.3 years old by the best-fit HGLM. The disease map showed the spread of disease from the southern central area to a nationwide area, excepting Gangwon-do (province), Gyeongsangbuk-do (province), and Seoul. CONCLUSION: In the transmission of scrub typhus in Korea, there was a correlation to the incidence of adjacent areas, as well as that of the previous year. According to the disease map, we are unlikely to see any decrease in the incidence in the near future, unless ongoing aggressive measures to prevent the exposure to the vector, chigger mites, in rural areas, are put into place. Korea Centers for Disease Control and Prevention 2013-02 /pmc/articles/PMC3747676/ /pubmed/24159528 http://dx.doi.org/10.1016/j.phrp.2013.01.002 Text en Copyright ©2013, Korea Centers for Disease Control and Prevention This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Noh, Maengseok
Lee, Youngjo
Chu, Chaeshin
Gwack, Jin
Youn, Seung-Ki
Huh, Sun
Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
title Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
title_full Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
title_fullStr Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
title_full_unstemmed Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
title_short Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
title_sort are there spatial and temporal correlations in the incidence distribution of scrub typhus in korea?
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3747676/
https://www.ncbi.nlm.nih.gov/pubmed/24159528
http://dx.doi.org/10.1016/j.phrp.2013.01.002
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