Evidence map›Paper›PMID 30811019›Full record

ArticleLifetime data analysis2019

Extending Bayesian back-calculation to estimate age and time specific HIV incidence.

Francesco Brizzi, Paul J Birrell, Martyn T Plummer, Peter Kirwan, Alison E Brown, Valerie C Delpech, O Noel Gill, Daniela De Angelis

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Lifetime data analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. Special issue dedicated to Odd O. Aalen.Lifetime data analysis · 2019
    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

8 authors at 3 institutions in 2 countries.

Francesco BrizziMedical Research Council Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK.ORCID http://orcid.org/0000-0003-4181-8522
Paul J BirrellMedical Research Council Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK.ORCID http://orcid.org/0000-0001-8131-4893
Martyn T PlummerIARC, 150 Cours Albert Thomas, 69372, Lyon Cedex 08, France.ORCID http://orcid.org/0000-0001-5130-6497
Peter KirwanPublic Health England, Colindale, London, NW9 5EQ, UK.
Alison E BrownPublic Health England, Colindale, London, NW9 5EQ, UK.
Valerie C DelpechPublic Health England, Colindale, London, NW9 5EQ, UK.
O Noel GillPublic Health England, Colindale, London, NW9 5EQ, UK.
Daniela De AngelisMedical Research Council Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK. daniela.deangelis@mrc-bsu.cam.ac.uk.ORCID http://orcid.org/0000-0001-6619-6112
Public Health England · GBUniversity of Cambridge · GBCentre international de recherche sur le cancer · FR

Funding

Medical Research Council MC_UU_00002/11World Health Organization 001
6 · The paper itself

Abstract

CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their inter-related contribution to the observed surveillance data. This paper, extends existing approaches to age-specific settings, permitting the joint estimation of age- and time-specific incidence and diagnosis rates and the derivation of other epidemiological quantities of interest. This allows the identification of specific age-groups at higher risk of infection, which is crucial in directing public health interventions. We investigate, through simulation studies, the suitability of various bivariate splines for the non-parametric modelling of the latent age- and time-specific incidence and illustrate our method on routinely collected data from the HIV epidemic among gay and bisexual men in England and Wales.

Indexed as

Bayes TheoremAdolescentAdultEnglandHIV InfectionsHumansIncidenceLikelihood FunctionsMaleMiddle AgedPopulation SurveillancePrevalenceRisk AssessmentTime FactorsWalesYoung AdultBack-calculationBayesian inferenceMulti-state modelRoutinely collected dataSplines

Identifiers

PMID30811019
PMCPMC6776486
OpenAlexW2917853092

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.