Evidence map›Paper›PMID 26196132›Full record

ArticlePloS one2015

A New Method for Estimating the Number of Undiagnosed HIV Infected Based on HIV Testing History, with an Application to Men Who Have Sex with Men in Seattle/King County, WA.

Ian E Fellows, Martina Morris, Jeanette K Birnbaum, Julia C Dombrowski, Susan Buskin, Amy Bennett, Matthew R Golden

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Estimating the First 90 of the UNAIDS 90-90-90 Goal: A Review.Journal of the International Association of Providers of AIDS Care
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Ian E FellowsFellows Statistics, San Diego, CA, United States of America.
Martina MorrisDepartment of Sociology, University of Washington, Seattle, WA, United States of America; Department of Statistics, University of Washington, Seattle, WA, United States of America.
Jeanette K BirnbaumCenter for AIDS Research, University of Washington, Seattle, WA, United States of America.
Julia C DombrowskiDivision of Allergy & Infectious Diseases, University of Washington School of Medicine, Seattle, WA, United States of America.
Susan BuskinDepartment of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States of America; HIV/AIDS Program, Public Health Seattle/King County, Seattle, WA, United States of America.
Amy BennettDepartment of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States of America.
Matthew R GoldenDivision of Allergy & Infectious Diseases, University of Washington School of Medicine, Seattle, WA, United States of America; HIV/AIDS Program, Public Health Seattle/King County, Seattle, WA, United States of America.

Funding

University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI Kenneth Sherr · 1988 to 2026
$104.9M
Methods and Data CoreR24HD042828 · NICHD · UNIVERSITY OF WASHINGTON · PI CURRAN, SARA R. · 2002 to 2016
$9.3M
NIAID NIH HHS P30 AI027757NICHD NIH HHS R24 HD042828
6 · The paper itself

Abstract

We develop a new approach for estimating the undiagnosed fraction of HIV cases, the first step in the HIV Care Cascade. The goal is to address a critical blindspot in HIV prevention and treatment planning, with an approach that simplifies data requirements and can be implemented with open-source software. The primary data required is HIV testing history information on newly diagnosed cases. Two methods are presented and compared. The first is a general methodology based on simplified back-calculation that can be used to assess changes in the undiagnosed fraction over time. The second makes an assumption of constant incidence, allowing the estimate to be expressed as a simple closed formula calculation. We demonstrate the methods with an application to HIV diagnoses among men who have sex with men (MSM) from Seattle/King County. The estimates suggest that 6% of HIV-infected MSM in King County are undiagnosed, about one-third of the comparable national estimate. A sensitivity analysis on the key distributional assumption gives an upper bound of 11%. The undiagnosed fraction varies by race/ethnicity, with estimates of 4.9% among white, 8.6% of African American, and 9.3% of Hispanic HIV-infected MSM being undiagnosed.

Indexed as

Homosexuality, MaleModels, StatisticalBlack or African AmericanHispanic or LatinoHIV InfectionsHumansMaleMass ScreeningWashingtonWhite People

Identifiers

PMID26196132
PMCPMC4510124

What OpenQuestion holds

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LicenceCC BY
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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.