Evidence map›Paper›PMID 21525422›Full record

ArticleBiostatistics (Oxford, England)2011

Bayesian evidence synthesis for a transmission dynamic model for HIV among men who have sex with men.

A M Presanis, D De Angelis, A Goubar, O N Gill, A E Ades

Abstract read
In one paragraph

Article in Biostatistics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Evidence Synthesis for Stochastic Epidemic Models.Statistical science : a review journal of the Institute of Mathematical Statistics · 2018
    Article
  6. Article
  7. A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data.Journal of the Royal Statistical Society. Series C, Applied statistics · 2016
    Article
  8. Article
  9. Article
  10. Fully Bayesian hierarchical modelling in two stages, with application to meta-analysis.Journal of the Royal Statistical Society. Series C, Applied statistics · 2013
    Article
  11. Evidence synthesis for decision making 5: the baseline natural history model.Medical decision making : an international journal of the Society for Medical Decision Making · 2013
    Article
  12. Article
  13. Article
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

5 authors.

A M PresanisMRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 0SR, UK. anne.presanis@mrc-bsu.cam.ac.uk
D De Angelis
A Goubar
O N Gill
A E Ades

Funding

Medical Research Council G0600675Medical Research Council MC_U105260556Medical Research Council U.1052.00.007
6 · The paper itself

Abstract

Understanding infectious disease dynamics and the effect on prevalence and incidence is crucial for public health policies. Disease incidence and prevalence are typically not observed directly and increasingly are estimated through the synthesis of indirect information from multiple data sources. We demonstrate how an evidence synthesis approach to the estimation of human immunodeficiency virus (HIV) prevalence in England and Wales can be extended to infer the underlying HIV incidence. Diverse time series of data can be used to obtain yearly "snapshots" (with associated uncertainty) of the proportion of the population in 4 compartments: not at risk, susceptible, HIV positive but undiagnosed, and diagnosed HIV positive. A multistate model for the infection and diagnosis processes is then formulated by expressing the changes in these proportions by a system of differential equations. By parameterizing incidence in terms of prevalence and contact rates, HIV transmission is further modeled. Use of additional data or prior information on demographics, risk behavior change and contact parameters allows simultaneous estimation of the transition rates, compartment prevalences, contact rates, and transmission probabilities.

Indexed as

Bayes TheoremModels, BiologicalModels, StatisticalBiostatisticsHIV InfectionsHomosexuality, MaleHumansIncidenceMalePrevalenceRisk-Taking

Identifiers

PMID21525422
PMCPMC3169669

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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.