Monitoring linked epidemics: the case of tuberculosis and HIV.
<h4>Background</h4>The tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance.<h4>Methodology/principal findings</h4>We review efforts of WHO and collaborating agencies to track and...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2010-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0008796&type=printable |
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| Summary: | <h4>Background</h4>The tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance.<h4>Methodology/principal findings</h4>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.<h4>Conclusions/significance</h4>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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| ISSN: | 1932-6203 |