ArticleInfectious Disease Modelling2018
Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study.
Article in Infectious Disease Modelling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Epidemiology of gonorrhea in countries of the Middle East and North Africa: systematic review, meta analyses, and meta regressions.BMC global and public health · 2024Pooled it
- HSV-2 as a biomarker of HIV epidemic potential in female sex workers: meta-analysis, global epidemiology and implications.Scientific reports · 2020Pooled it
- Expanding syphilis test uptake using rapid dual self-testing for syphilis and HIV among men who have sex with men in China: A multiarm randomized controlled trial.PLoS medicine · 2022Trial
- A network-based model to explore the role of testing in the epidemiological control of the COVID-19 pandemic.BMC infectious diseases · 2021Article
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3 authors.
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Abstract
introductionHIV epidemics in hard-to-reach high-risk subpopulations are often discovered years after epidemic emergence in settings with poor surveillance infrastructure. Using hypothesis-generation modeling, we aimed to investigate and demonstrate the concept of using routine HIV testing data to identify and characterize hidden epidemics in high-risk subpopulations. We also compared this approach to surveillance based on AIDS case notifications.
methodsA deterministic mathematical model was developed to simulate an emerging HIV epidemic in a high-risk subpopulation. A stochastic Monte Carlo simulation was implemented on the total population to simulate the sampling process of generating routine HIV testing data. Epidemiological measures were estimated on the simulated epidemic and on the generated testing sample. Sensitivity analyses were conducted on the results.
resultsIn the simulated epidemic, HIV prevalence saturated at 32% in the high-risk subpopulation and at 0.33% in the total population. The epidemic started its emerging-epidemic phase 28 years after infection introduction, and saturated 67 years after infection introduction. In the simulated HIV testing sample, a significant time trend in prevalence was identified, and the generated metrics of epidemic emergence and saturation were similar to those of the simulated epidemic. The epidemic was identified 4.0 (95% CI 3.4-4.6) years after epidemic emergence using routine HIV testing, but 29.7 (95% CI 15.8-52.1) years after emergence using AIDS case notifications. In the sensitivity analyses, none of the sampling biases affected the conclusion of an emerging epidemic, but some affected the estimated epidemic growth rate.
conclusionsRoutine HIV testing data provides a tool to identify and characterize hidden and emerging epidemics in high-risk subpopulations. This approach can be specially useful in resource-limited settings, and can be applied alone, or along with other complementary data, to provide a meaningful characterization of emerging but hidden epidemics.
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