Evidence map›Paper›PMID 34567992›Full record

ArticlePublic health action2021

Mobile HIV testing in South Africa: maximizing yield through data-guided site selection.

T Mabuto, S Holzman, G Kubeka, C J Hoffmann

Abstract read
In one paragraph

Article in Public health action, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

T MabutoAurum Institute, Johannesburg, South Africa.
S HolzmanJohns Hopkins University School of Medicine, Baltimore, MD, USA.
G KubekaAurum Institute, Johannesburg, South Africa.
C J HoffmannAurum Institute, Johannesburg, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile community HIV testing can effectively reach undiagnosed people living with HIV in southern Africa. Variable yield in HIV test positivity has been a challenge with high- and low-yield sites often being closely situated. We sought to test whether easy-to-identify, site-level characteristics were associated with HIV positivity yield in a routine mobile HIV testing program.

methodsWe used routine testing program test data augmented with site-level characterization, either of the community or shopping site at which HIV testing was offered. Specifically, we described the local environment and interviewed key informants to gain additional information regarding the availability of HIV and other services in the locale.

resultsWe included 122 residential and 26 shopping sites with median HIV-positive test yields of 7.6% and 6.9%, respectively. The range for community sites was from 2 to 55% with high and low yields at geographically proximal sites. Factors related to lower income and marginalization, including informal housing and the absence of name-brand stores in shopping venues, were associated with higher HIV-positive testing yield.

conclusionsCharacterization of sites, particularly identifying factors related to marginalization, lack of services, and poverty, can aid in identifying sites with higher HIV-positive yield.

Indexed as

geospatial mappingHIV care continuumimplementation science

Identifiers

PMID34567992
PMCPMC8455025

What OpenQuestion holds

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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.