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Monitoring Linked Epidemics: The Case of Tuberculosis and HIV

BACKGROUND: The tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance. METHODOLOGY/PRINCIPAL FINDINGS: We review efforts of WHO and collaborating agencies to track and fight the TB/HIV co-epidemic, and di...

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Autores principales: Sánchez, María S., Lloyd-Smith, James O., Getz, Wayne M.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808389/
https://www.ncbi.nlm.nih.gov/pubmed/20098716
http://dx.doi.org/10.1371/journal.pone.0008796
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author Sánchez, María S.
Lloyd-Smith, James O.
Getz, Wayne M.
author_facet Sánchez, María S.
Lloyd-Smith, James O.
Getz, Wayne M.
author_sort Sánchez, María S.
collection PubMed
description BACKGROUND: The tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance. METHODOLOGY/PRINCIPAL FINDINGS: We review efforts of WHO and collaborating agencies to track and fight the TB/HIV co-epidemic, and discuss modeling—via mathematical, statistical, and computational approaches—as a means to identify disease indicators designed to integrate data from linked diseases in order to characterize how co-epidemics change in time and space. We present R (TB/HIV), an index comparing changes in TB incidence relative to HIV prevalence, and use it to identify those sub-Saharan African countries with outlier TB/HIV dynamics. R (TB/HIV) can also be used to predict epidemiological trends, investigate the coherency of reported trends, and cross-check the anticipated impact of public health interventions. Identifying the cause(s) responsible for anomalous R (TB/HIV) values can reveal information crucial to the management of public health. CONCLUSIONS/SIGNIFICANCE: We frame our suggestions for integrating and analyzing co-epidemic data within the context of global disease monitoring. Used routinely, joint disease indicators such as R (TB/HIV) could greatly enhance the monitoring and evaluation of public health programs.
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spelling pubmed-28083892010-01-23 Monitoring Linked Epidemics: The Case of Tuberculosis and HIV Sánchez, María S. Lloyd-Smith, James O. Getz, Wayne M. PLoS One Research Article BACKGROUND: The tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance. METHODOLOGY/PRINCIPAL FINDINGS: We review efforts of WHO and collaborating agencies to track and fight the TB/HIV co-epidemic, and discuss modeling—via mathematical, statistical, and computational approaches—as a means to identify disease indicators designed to integrate data from linked diseases in order to characterize how co-epidemics change in time and space. We present R (TB/HIV), an index comparing changes in TB incidence relative to HIV prevalence, and use it to identify those sub-Saharan African countries with outlier TB/HIV dynamics. R (TB/HIV) can also be used to predict epidemiological trends, investigate the coherency of reported trends, and cross-check the anticipated impact of public health interventions. Identifying the cause(s) responsible for anomalous R (TB/HIV) values can reveal information crucial to the management of public health. CONCLUSIONS/SIGNIFICANCE: We frame our suggestions for integrating and analyzing co-epidemic data within the context of global disease monitoring. Used routinely, joint disease indicators such as R (TB/HIV) could greatly enhance the monitoring and evaluation of public health programs. Public Library of Science 2010-01-20 /pmc/articles/PMC2808389/ /pubmed/20098716 http://dx.doi.org/10.1371/journal.pone.0008796 Text en Sánchez et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Sánchez, María S.
Lloyd-Smith, James O.
Getz, Wayne M.
Monitoring Linked Epidemics: The Case of Tuberculosis and HIV
title Monitoring Linked Epidemics: The Case of Tuberculosis and HIV
title_full Monitoring Linked Epidemics: The Case of Tuberculosis and HIV
title_fullStr Monitoring Linked Epidemics: The Case of Tuberculosis and HIV
title_full_unstemmed Monitoring Linked Epidemics: The Case of Tuberculosis and HIV
title_short Monitoring Linked Epidemics: The Case of Tuberculosis and HIV
title_sort monitoring linked epidemics: the case of tuberculosis and hiv
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808389/
https://www.ncbi.nlm.nih.gov/pubmed/20098716
http://dx.doi.org/10.1371/journal.pone.0008796
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