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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...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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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 |
Sumario: | 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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