Evidence map›Paper›PMID 42215687›Full record

ArticleCommunications medicine2026

Modelling assessment of epidemiological strategies based on self-screening tools.

Amandine Pepiot, Delphine Rahib, Annie Velter, Romulus Breban

Abstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Amandine PepiotSorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Paris, France.ORCID http://orcid.org/0000-0002-5103-7087
Delphine RahibSanté Publique France, French National Public Health Agency, Saint-Maurice Cedex, France.
Annie VelterSanté Publique France, French National Public Health Agency, Saint-Maurice Cedex, France.
Romulus BrebanUnité d'Epidémiologie des Maladies Emergentes, Institut Pasteur, Paris, France. romulus.breban@pasteur.fr.ORCID http://orcid.org/0000-0002-5821-8139

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo reach 2030 targets, the World Health Organization specifically recommends test-and-treat strategies to eliminate HIV and bacterial STI. Mathematical models identified the required coverages for the success of these interventions. However, they appear out of reach for current testing protocols based on medical recommendations. Still, promoting voluntary testing can effectively increase testing rates if individuals perceive high benefits associated to frequent testing. Design of multi-disease voluntary testing kits remains a key strategic tool to reach various epidemiological goals.

methodsWe construct mathematical models to describe individual-level decision-making about testing within a given epidemiological context. In particular, we discuss the four-disease epidemic of HIV, syphilis, chlamydia and gonorrhoeae in the Parisian community of men-who-have-sex-with-men. We acknowledge that individuals undergo pre-exposure prophylaxis against HIV that requires periodic testing. Furthermore, individuals may be biased in estimating their HIV risk relative to the risk of acquiring bacterial STI. Under these circumstances, we identify the combined testing strategies which bring HIV closest to elimination.

resultsAn unbiased perception of disease risk works best toward HIV elimination. Secondly, regardless PrEP coverage and perception bias, combining HIV and syphilis voluntary testing performs worse than testing for HIV alone or along with other STI such as chlamydia and/or gonorrhoeae, to achieve HIV elimination.

conclusionsWe argue against combining testing for HIV and syphilis as a voluntary testing strategy. Rather, to bring HIV closer to the elimination, it is best that voluntary testing for HIV and syphilis requires two distinct individual-level decisions.

Identifiers

PMID42215687
PMCPMC13507276

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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.