Evidence map›Paper›PMID 28471841›Full record

ArticleJournal of acquired immune deficiency syndromes (1999)2017

A Flow-Based Model of the HIV Care Continuum in the United States.

Gregg S Gonsalves, A David Paltiel, Paul D Cleary, Michael J Gill, Mari M Kitahata, Peter F Rebeiro, Michael J Silverberg, Michael Horberg, Alison G Abraham, Keri N Althoff and 5 more

Abstract read
In one paragraph

Article in Journal of acquired immune deficiency syndromes (1999), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. A qualitative model of the HIV care continuum in Vancouver, Canada.Health systems (Basingstoke, England) · 2022
    Article
  4. Article
  5. Substance use and HIV stage at entry into care among people with HIV.Archives of public health = Archives belges de sante publique · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Tenofovir Diphosphate in Dried Blood Spots Is Strongly Associated With Viral Suppression in Individuals With Human Immunodeficiency Virus Infections.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2019
    Observational
  12. Review
  13. Development of a Cascade of Care for responding to the opioid epidemic.The American journal of drug and alcohol abuse · 2019
    Article
  14. 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

15 authors.

Gregg S GonsalvesDepartments of *Epidemiology of Microbial Diseases; and †Health Policy and Management, Yale School of Public Health, New Haven, CT; ‡Department of Medicine, University of Calgary, Alberta, Canada; §Center for AIDS Research, University of Washington, Seattle, WA; ‖Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN; ¶Division of Research, Kaiser Permanente Northern California, Oakland, CA; #Kaiser Permanente Mid-Atlantic Permanente Research Institute, Rockville, MD; **Department of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, MD; ††Department of Epidemiology, Johns Hopkins University, Baltimore, MD; ‡‡Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD; §§Center for Biostatistics in AIDS Research, Harvard School of Public Health, Boston, MA; ‖‖ICF International, Atlanta, GA; ¶¶Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA; and ##Yale School of Management, Yale School of Public Health, Yale School of Engineering and Applied Science, Yale University, New Haven, CT.
A David Paltiel
Paul D Cleary
Michael J Gill
Mari M Kitahata
Peter F Rebeiro
Michael J Silverberg
Michael Horberg
Alison G Abraham
Keri N Althoff
Richard Moore
Ronald J Bosch
Tian Tang
H Irene Hall
Edward H Kaplan

Funding

Statistical and Data Management Center (SDMC), AIDS Clinical Trials Group (ACTG)UM1AI068634 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Marlene Ann Cooper, Michael David Hughes · 2011 to 2026
$246.6M
WOMEN'S HEALTH AGENDAU01AI038858 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI BENSON, CONSTANCE ANN · 1996 to 2008
$157.5M
AIDS Clinical Trials Group NetworkU01AI068636 · NIAID · SOCIAL AND SCIENTIFIC SYSTEMS, INC. · PI KURITZKES, DANIEL R. · 2006 to 2010
$147.1M
UCSF CLINICAL AND TRANSLATIONAL SCIENCE INSTITUTEUL1RR024131 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHNSTON, S. CLAIBORNE · 2006 to 2011
$111.2M
University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI EDWIN ROBERTO ORELLANA · 1988 to 2026
$104.9M
Unsolicited R24 for the CFAR-Network of Integrated Clinical Sciences, CNICSR24AI067039 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Michael S. Saag · 2006 to 2026
$99.4M
Virology CoreP30AI027763 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MALLORY O JOHNSON · 1988 to 2026
$93.6M
Virology CoreP30AI027767 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Latesha Ellen Elopre · 1988 to 2026
$84.1M
STATISTICAL AND DATA MANAGEMENT CENTERU01AI038855 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI HUGHES, MICHAEL DAVID · 1996 to 2006
$78.1M
Engaging University of California Stakeholders for Biorespository ResearchUL1TR000004 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GRANDIS, JENNIFER RUBIN · 2012 to 2015
$78.0M
Studies of Ocular Complications of AIDS - Coordinating CenterU10EY008057 · NEI · JOHNS HOPKINS UNIVERSITY · PI VAN NATTA, MARK L · 1988 to 2012
$78.0M
Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
NCATS NIH HHS KL2 TR000421NCATS NIH HHS KL2 TR002317NCATS NIH HHS UL1 TR000004NCATS NIH HHS UL1 TR000083NCATS NIH HHS UL1 TR000454NCI NIH HHS N02CP55504NCI NIH HHS R01 CA165937NCI NIH HHS Z01 CP010176NCRR NIH HHS M01 RR000052NCRR NIH HHS UL1 RR024131NEI NIH HHS K23 EY013707NEI NIH HHS U10 EY008052NEI NIH HHS U10 EY008057NEI NIH HHS U10 EY008067NIAAA NIH HHS R01 AA016893NIAAA NIH HHS U01 AA013566NIAAA NIH HHS U01 AA020790NIAAA NIH HHS U24 AA020794NIAID NIH HHS K01 AI093197NIAID NIH HHS K01 AI131895NIAID NIH HHS K24 AI065298NIAID NIH HHS P30 AI027757NIAID NIH HHS P30 AI027763NIAID NIH HHS P30 AI027767NIAID NIH HHS P30 AI036219NIAID NIH HHS P30 AI050410NIAID NIH HHS P30 AI094189NIAID NIH HHS P30 AI110527NIAID NIH HHS R24 AI067039NIAID NIH HHS U01 AI031834NIAID NIH HHS U01 AI034989NIAID NIH HHS U01 AI034993NIAID NIH HHS U01 AI034994NIAID NIH HHS U01 AI035004NIAID NIH HHS U01 AI035039NIAID NIH HHS U01 AI035040NIAID NIH HHS U01 AI035041NIAID NIH HHS U01 AI035042NIAID NIH HHS U01 AI037613NIAID NIH HHS U01 AI037984NIAID NIH HHS U01 AI038855NIAID NIH HHS U01 AI038858NIAID NIH HHS U01 AI042590NIAID NIH HHS U01 AI068634NIAID NIH HHS U01 AI068636NIAID NIH HHS U01 AI069432NIAID NIH HHS U01 AI069434NIAID NIH HHS U01 AI069918NIAID NIH HHS U01 AI103390NIAID NIH HHS U01 AI103397NIAID NIH HHS U01 AI103401NIAID NIH HHS U01 AI103408NIAID NIH HHS UM1 AI035043NIAID NIH HHS UM1 AI068634NICHD NIH HHS U01 HD032632NIDA NIH HHS F31 DA037788NIDA NIH HHS K24 DA000432NIDA NIH HHS R01 DA004334NIDA NIH HHS R01 DA011602NIDA NIH HHS R01 DA012568NIDA NIH HHS R01 DA015612NIDA NIH HHS U01 DA036935NIMHD NIH HHS G12 MD007583NIMHD NIH HHS U54 MD007587NIMH NIH HHS R01 MH105203
6 · The paper itself

Abstract

backgroundUnderstanding the flow of patients through the continuum of HIV care is critical to determine how best to intervene so that the proportion of HIV-infected persons who are on antiretroviral treatment and virally suppressed is as large as possible.

methodsUsing immunological and virological data from the Centers for Disease Control and Prevention and the North American AIDS Cohort Collaboration on Research and Design from 2009 to 2012, we estimated the distribution of time spent in and dropout probability from each stage in the continuum of HIV care. We used these estimates to develop a queueing model for the expected number of patients found in each stage of the cascade.

resultsHIV-infected individuals spend an average of about 3.1 months after HIV diagnosis before being linked to care, or dropping out of that stage of the continuum with a probability of 8%. Those who link to care wait an additional 3.7 months on average before getting their second set of laboratory results (indicating engagement in care) or dropping out of care with probability of almost 6%. Those engaged in care spent an average of almost 1 year before achieving viral suppression on antiretroviral therapy or dropping out with average probability 13%. For patients who achieved viral suppression, the average time suppressed on antiretroviral therapy was an average of 4.5 years.

conclusionsInterventions should be targeted to more rapidly identifying newly infected individuals, and increasing the fraction of those engaged in care that achieves viral suppression.

Indexed as

Continuity of Patient CareModels, TheoreticalAnti-HIV AgentsCD4 Lymphocyte CountCross-Sectional StudiesFemaleHIV InfectionsHumansMalePopulation SurveillanceUnited StatesViral LoadAnti-HIV Agents

Identifiers

PMID28471841
PMCPMC5533168

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.