Evidence map›Paper›PMID 25406754›Full record

ArticleAIDS (London, England)2014

Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data.

Le Bao, Jingyi Ye, Timothy B Hallett

Abstract read
In one paragraph

Article in AIDS (London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Le BaoaDepartment of Statistics, the Pennsylvania State University, University Park, Pennsylvania, USA bDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.
Jingyi Ye
Timothy B Hallett

Funding

Medical Research Council MR/K010174/1
6 · The paper itself

Abstract

objectivesThe objective of this study is to extend the UNAIDS incidence estimation model, the UNAIDS Estimation and Projection Package (EPP), so that it can incorporate data from incidence assays.

methodsWe propose combining the likelihood of the incidence assay data with the likelihood of other data, in a manner that is consistent with the biomarker-based incidence estimator using incidence assay data. Two calibrating parameters specify the performance of the incidence assays: the false recent rate and the mean duration of recent infection. We then use synthetic data, based on prevalence data obtained from antenatal clinic surveillances, and in some cases household surveys, from 24 countries, to examine the impact of including incidence assay data, under circumstances wherein the incidence assay data imply the same or a different incidence rate as that inferred from the prevalence data alone, and wherein incorrect calibrating parameters for the incidence assay data are used.

resultsUsing incidence assay data, in addition to prevalence data, can improve estimate by narrowing uncertainty intervals in derived HIV incidence estimates, and by providing information on levels or trends in incidence that were not apparent in the prevalence data alone. However, the effect is relatively modest if the sample size of the incidence assay survey is small and results can be biased if the calibrating parameters for the incidence assay data are not known accurately.

conclusionIncorporating information from incidence assays in the manner proposed has the potential to improve estimates. Further work will examine in more detail the circumstances under which the contribution of incidence assay data would be most valuable.

Indexed as

Epidemiologic MethodsAdolescentAdultComputer SimulationFemaleHIV InfectionsHumansIncidenceMaleMiddle AgedYoung Adult

Identifiers

PMID25406754
PMCPMC4247275

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.