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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...

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Detalles Bibliográficos
Autores principales: Kim, Sara, Choe, Seoyun, Kim, Junseong, Nam, Sanga, Shin, Yeon, Lee, Sunmi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2014
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.
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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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