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What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection?
OBJECTIVES: According to the Korea Centers for Disease Control and Prevention, new active tuberculosis (TB) cases have increased since 2001. Some key factors explain and characterize the transmission dynamics of Korean TB infection, such as a higher ratio of latent individuals and a new reporting sy...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4064633/ https://www.ncbi.nlm.nih.gov/pubmed/24955311 http://dx.doi.org/10.1016/j.phrp.2014.01.002 |
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author | Kim, Sara Choe, Seoyun Kim, Junseong Nam, Sanga Shin, Yeon Lee, Sunmi |
author_facet | Kim, Sara Choe, Seoyun Kim, Junseong Nam, Sanga Shin, Yeon Lee, Sunmi |
author_sort | Kim, Sara |
collection | PubMed |
description | OBJECTIVES: According to the Korea Centers for Disease Control and Prevention, new active tuberculosis (TB) cases have increased since 2001. Some key factors explain and characterize the transmission dynamics of Korean TB infection, such as a higher ratio of latent individuals and a new reporting system implemented in 2001, among others. METHODS: We propose a mathematical TB model that includes exogenous reinfection to gain a better understanding of the recent trend for TB incidence. We divide the simulation time window into two periods, 1970–2000 and 2001–2012, according to the implementation date of a new TB detection system. RESULTS: Two sets of parameters, including the transmission rate, the latent period, the recovery rate, and the proportion of exogenous reinfection, are estimated using the least-squares method and calibrated to data on the incidence of active TB. CONCLUSION: Among some key parameters in the model, the case finding effort turned out to be the most significant impacting component on the reduction in the active TB cases. |
format | Online Article Text |
id | pubmed-4064633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
record_format | MEDLINE/PubMed |
spelling | pubmed-40646332014-06-20 What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? Kim, Sara Choe, Seoyun Kim, Junseong Nam, Sanga Shin, Yeon Lee, Sunmi Osong Public Health Res Perspect Original Article OBJECTIVES: According to the Korea Centers for Disease Control and Prevention, new active tuberculosis (TB) cases have increased since 2001. Some key factors explain and characterize the transmission dynamics of Korean TB infection, such as a higher ratio of latent individuals and a new reporting system implemented in 2001, among others. METHODS: We propose a mathematical TB model that includes exogenous reinfection to gain a better understanding of the recent trend for TB incidence. We divide the simulation time window into two periods, 1970–2000 and 2001–2012, according to the implementation date of a new TB detection system. RESULTS: Two sets of parameters, including the transmission rate, the latent period, the recovery rate, and the proportion of exogenous reinfection, are estimated using the least-squares method and calibrated to data on the incidence of active TB. CONCLUSION: Among some key parameters in the model, the case finding effort turned out to be the most significant impacting component on the reduction in the active TB cases. 2014-02-05 2014-02 /pmc/articles/PMC4064633/ /pubmed/24955311 http://dx.doi.org/10.1016/j.phrp.2014.01.002 Text en © 2014 Published by Elsevier B.V. on behalf of Korea Centers for Disease Control and Prevention. http://creativecommons.org/licenses/by-nc/3.0/ 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 Kim, Sara Choe, Seoyun Kim, Junseong Nam, Sanga Shin, Yeon Lee, Sunmi What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? |
title | What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? |
title_full | What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? |
title_fullStr | What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? |
title_full_unstemmed | What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? |
title_short | What Does a Mathematical Model Tell About the Impact of Reinfection in Korean Tuberculosis Infection? |
title_sort | what does a mathematical model tell about the impact of reinfection in korean tuberculosis infection? |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4064633/ https://www.ncbi.nlm.nih.gov/pubmed/24955311 http://dx.doi.org/10.1016/j.phrp.2014.01.002 |
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