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Interpreting measures of tuberculosis transmission: a case study on the Portuguese population
BACKGROUND: Tuberculosis remains a high burden for Human society despite considerable investments in its control. Unique features in the history of infection and transmission dynamics of tuberculosis pose serious limitations on the direct interpretation of surveillance data and call for models that...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4069091/ https://www.ncbi.nlm.nih.gov/pubmed/24941996 http://dx.doi.org/10.1186/1471-2334-14-340 |
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author | Lopes, Joao Sollari Rodrigues, Paula Pinho, Suani TR Andrade, Roberto FS Duarte, Raquel Gomes, M Gabriela M |
author_facet | Lopes, Joao Sollari Rodrigues, Paula Pinho, Suani TR Andrade, Roberto FS Duarte, Raquel Gomes, M Gabriela M |
author_sort | Lopes, Joao Sollari |
collection | PubMed |
description | BACKGROUND: Tuberculosis remains a high burden for Human society despite considerable investments in its control. Unique features in the history of infection and transmission dynamics of tuberculosis pose serious limitations on the direct interpretation of surveillance data and call for models that incorporate latent processes and simulate specific interventions. METHODS: A transmission model was adjusted to the dataset of active tuberculosis cases reported in Portugal between 2002 and 2009. We estimated key transmission parameters from the data (i.e. time to diagnosis, treatment length, default proportion, proportion of pulmonary TB cases). Using the adjusted model to the Portuguese case, we estimated the total burden of tuberculosis in Portugal. We further performed sensitivity analysis to heterogeneities in susceptibility to infection and exposure intensity. RESULTS: We calculated a mean time to diagnose of 2.81 months and treatment length of 8.80 months in Portugal. The proportion defaulting treatment was calculated as 0.04 and the proportion of pulmonary cases as 0.75. Using these values, we estimated a TB burden of 1.6 million infected persons, corresponding to more than 15% of the Portuguese population. We further described the sensitivity of these estimates to heterogeneity. CONCLUSIONS: We showed that the model reproduces well the observed dynamics of the Portuguese data, thus demonstrating its adequacy for devising control strategies for TB and predicting the effects of interventions. |
format | Online Article Text |
id | pubmed-4069091 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40690912014-06-27 Interpreting measures of tuberculosis transmission: a case study on the Portuguese population Lopes, Joao Sollari Rodrigues, Paula Pinho, Suani TR Andrade, Roberto FS Duarte, Raquel Gomes, M Gabriela M BMC Infect Dis Research Article BACKGROUND: Tuberculosis remains a high burden for Human society despite considerable investments in its control. Unique features in the history of infection and transmission dynamics of tuberculosis pose serious limitations on the direct interpretation of surveillance data and call for models that incorporate latent processes and simulate specific interventions. METHODS: A transmission model was adjusted to the dataset of active tuberculosis cases reported in Portugal between 2002 and 2009. We estimated key transmission parameters from the data (i.e. time to diagnosis, treatment length, default proportion, proportion of pulmonary TB cases). Using the adjusted model to the Portuguese case, we estimated the total burden of tuberculosis in Portugal. We further performed sensitivity analysis to heterogeneities in susceptibility to infection and exposure intensity. RESULTS: We calculated a mean time to diagnose of 2.81 months and treatment length of 8.80 months in Portugal. The proportion defaulting treatment was calculated as 0.04 and the proportion of pulmonary cases as 0.75. Using these values, we estimated a TB burden of 1.6 million infected persons, corresponding to more than 15% of the Portuguese population. We further described the sensitivity of these estimates to heterogeneity. CONCLUSIONS: We showed that the model reproduces well the observed dynamics of the Portuguese data, thus demonstrating its adequacy for devising control strategies for TB and predicting the effects of interventions. BioMed Central 2014-06-18 /pmc/articles/PMC4069091/ /pubmed/24941996 http://dx.doi.org/10.1186/1471-2334-14-340 Text en Copyright © 2014 Lopes et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Lopes, Joao Sollari Rodrigues, Paula Pinho, Suani TR Andrade, Roberto FS Duarte, Raquel Gomes, M Gabriela M Interpreting measures of tuberculosis transmission: a case study on the Portuguese population |
title | Interpreting measures of tuberculosis transmission: a case study on the Portuguese population |
title_full | Interpreting measures of tuberculosis transmission: a case study on the Portuguese population |
title_fullStr | Interpreting measures of tuberculosis transmission: a case study on the Portuguese population |
title_full_unstemmed | Interpreting measures of tuberculosis transmission: a case study on the Portuguese population |
title_short | Interpreting measures of tuberculosis transmission: a case study on the Portuguese population |
title_sort | interpreting measures of tuberculosis transmission: a case study on the portuguese population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4069091/ https://www.ncbi.nlm.nih.gov/pubmed/24941996 http://dx.doi.org/10.1186/1471-2334-14-340 |
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