ArticlePloS one2010
Monitoring linked epidemics: the case of tuberculosis and HIV.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Virulence ofJournal of fungi (Basel, Switzerland) · 2025Article
- Joint spatiotemporal modelling of tuberculosis and human immunodeficiency virus in Ethiopia using a Bayesian hierarchical approach.BMC public health · 2025Article
- Article
- Benzotriazole: An overview on its versatile biological behavior.European journal of medicinal chemistry · 2015Review
- Potential impact of the US President's Emergency Plan for AIDS relief on the tuberculosis/HIV coepidemic in selected Sub-Saharan African countries.The Journal of infectious diseases · 2013Article
- Prevalence of Candida co-infection in patients with pulmonary tuberculosis.The Australasian medical journal · 2013Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundThe tight epidemiological coupling between HIV and its associated opportunistic infections leads to challenges and opportunities for disease surveillance. METHODOLOGY/PRINCIPAL
findingsWe 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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Registered trials
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