Evidence map›Paper›PMID 32106876›Full record

ArticleBMC research notes2020

On estimating the number of people with known HIV positive status.

Georges Nguefack-Tsague, Serge Clotaire Billong, Ousseni W Tiemtore, Albert Frank Zeh Meka, Ismael Diallo, Brian Bongwong, Marie Nicole Ngoufack, Ernest Mvilongo, Yemurai Ndowa, Houssey Diallo and 6 more

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2020. 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
0.3field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Trial
  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

16 authors at 4 institutions in 3 countries.

Georges Nguefack-TsagueBiostatistics Unit, Department of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, P.O. Box 8 550, Yaoundé, Cameroon. nguefacktsague@gmail.com.ORCID http://orcid.org/0000-0002-3847-3490
Serge Clotaire BillongBiostatistics Unit, Department of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, P.O. Box 8 550, Yaoundé, Cameroon.
Ousseni W TiemtoreInitiatives Conseil International-Santé (ICI-santé), Ouagadougou, Burkina Faso.
Albert Frank Zeh MekaNational AIDS Control Committee, Ministry of Public Health, Yaoundé, Cameroon.
Ismael DialloHôpital de jour, CHU-Yalgado Ouédraogo, Ouagadougou, Burkina Faso.
Brian BongwongBiostatistics Unit, Department of Public Health, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, P.O. Box 8 550, Yaoundé, Cameroon.
Marie Nicole NgoufackCentre International de Reference Chantal Biya, Yaoundé, Cameroon.
Ernest MvilongoNational AIDS Control Committee, Ministry of Public Health, Yaoundé, Cameroon.
Yemurai NdowaThe Global Fund to fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Houssey DialloThe Global Fund to fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Bruno ClaryThe Global Fund to fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Koubagnine TakpaUNAIDS, Yaoundé, Cameroon.
Jean-Baptiste Guiard-SchmidInitiatives Conseil International-Santé (ICI-santé), Ouagadougou, Burkina Faso.
Leonard BononoNational AIDS Control Committee, Ministry of Public Health, Yaoundé, Cameroon.
Jean-Bosco Elat-NfetamNational AIDS Control Committee, Ministry of Public Health, Yaoundé, Cameroon.
Jinkou ZhaoThe Global Fund to fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Global Fund to Fight AIDS, Tuberculosis and Malaria · CHMinistry of Public Health · CMUniversité de Yaoundé I · CMCentre Hospitalier Universitaire Yalgado Ouédraogo · BF

Funding

Global Fund to Fight AIDS, Tuberculosis and Malaria CMR-011-G11-H
6 · The paper itself

Abstract

objectiveIn 2014, the Joint United Nations Program on HIV and AIDS (UNAIDS) and partners set the '90-90-90 targets'. Many countries are facing the challenge of estimating the first 90. Our objective was to propose an alternative modelling procedure, and to discuss its usefulness for taking into account duplication.

resultsFor deduplication, we identified two important ingredients: the probability for an HIV+ person of being re-tested during the period and average number of HIV+ tests. Other adjusted factors included: the false positive probability; the death and emigration probabilities. The uncertainty of the adjusted estimate was assessed using the plausibility bounds and sensitivity analysis. The proposed method was applied to Cameroon for the period 1987-2016. Of the 560,000 people living with HIV estimated from UNAIDS in 2016; 504,000 out to know their status. The model estimates that 380,464 [379,257, 381,674] know their status (75.5%); thus 179,536 who do not know their status should be sought through the intensification of testing. These results were subsequently used for constructing the full 2016 Cameroon HIV cascade for identifying programmatic gap, prioritizing the resources, and guiding the strategies of the 2018-2022 National Strategy Plan and funding request.

Indexed as

Acquired Immunodeficiency SyndromeAlgorithmsAnti-Retroviral AgentsCameroonDisease EradicationHIV-1HIV InfectionsHumansMass ScreeningModels, TheoreticalPrevalenceReproducibility of ResultsSensitivity and SpecificityUnited NationsAnti-Retroviral Agents90-90-90 targetAverage number of HIV+ testsHIV cascadeRetesting probability

Identifiers

PMID32106876
PMCPMC7047381
OpenAlexW3012839038

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.