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

BACKGROUND:Understanding 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. METHODS:Using immunological and virologica...

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Veröffentlicht in:Journal of acquired immune deficiency syndromes (1999) 2017-08, Vol.75 (5), p.548-553
Hauptverfasser: Gonsalves, Gregg S, Paltiel, A David, Cleary, Paul D, Gill, Michael J, Kitahata, Mari M, Rebeiro, Peter F, Silverberg, Michael J, Horberg, Michael, Abraham, Alison G, Althoff, Keri N, Moore, Richard, Bosch, Ronald J, Tang, Tian, Hall, H Irene, Kaplan, Edward H
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container_end_page 553
container_issue 5
container_start_page 548
container_title Journal of acquired immune deficiency syndromes (1999)
container_volume 75
creator Gonsalves, Gregg S
Paltiel, A David
Cleary, Paul D
Gill, Michael J
Kitahata, Mari M
Rebeiro, Peter F
Silverberg, Michael J
Horberg, Michael
Abraham, Alison G
Althoff, Keri N
Moore, Richard
Bosch, Ronald J
Tang, Tian
Hall, H Irene
Kaplan, Edward H
description BACKGROUND:Understanding 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. METHODS:Using 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. RESULTS:HIV-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. CONCLUSIONS:Interventions should be targeted to more rapidly identifying newly infected individuals, and increasing the fraction of those engaged in care that achieves viral suppression.
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METHODS:Using 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. RESULTS:HIV-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. CONCLUSIONS:Interventions should be targeted to more rapidly identifying newly infected individuals, and increasing the fraction of those engaged in care that achieves viral suppression.</description><identifier>ISSN: 1525-4135</identifier><identifier>EISSN: 1944-7884</identifier><identifier>DOI: 10.1097/QAI.0000000000001429</identifier><identifier>PMID: 28471841</identifier><language>eng</language><publisher>United States: Copyright Wolters Kluwer Health, Inc. All rights reserved</publisher><subject>Acquired immune deficiency syndrome ; AIDS ; AIDS/HIV ; Anti-HIV Agents - therapeutic use ; Antiretroviral agents ; Antiretroviral drugs ; Antiretroviral therapy ; CD4 Lymphocyte Count ; Continuity of Patient Care - statistics &amp; numerical data ; Cross-Sectional Studies ; Disease control ; Female ; HIV ; HIV Infections - drug therapy ; HIV Infections - mortality ; HIV Infections - virology ; Human immunodeficiency virus ; Humans ; Immunology ; Male ; Models, Theoretical ; Patients ; Population Surveillance ; Probability ; Queues ; Therapy ; United States - epidemiology ; Viral Load ; Virology</subject><ispartof>Journal of acquired immune deficiency syndromes (1999), 2017-08, Vol.75 (5), p.548-553</ispartof><rights>Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.</rights><rights>Copyright Lippincott Williams &amp; Wilkins Aug 15, 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4859-eef82de53dac74aa1e18f908c01d47c54172a7957ef7d2deff95320d3e4d62923</citedby><cites>FETCH-LOGICAL-c4859-eef82de53dac74aa1e18f908c01d47c54172a7957ef7d2deff95320d3e4d62923</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28471841$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gonsalves, Gregg S</creatorcontrib><creatorcontrib>Paltiel, A David</creatorcontrib><creatorcontrib>Cleary, Paul D</creatorcontrib><creatorcontrib>Gill, Michael J</creatorcontrib><creatorcontrib>Kitahata, Mari M</creatorcontrib><creatorcontrib>Rebeiro, Peter F</creatorcontrib><creatorcontrib>Silverberg, Michael J</creatorcontrib><creatorcontrib>Horberg, Michael</creatorcontrib><creatorcontrib>Abraham, Alison G</creatorcontrib><creatorcontrib>Althoff, Keri N</creatorcontrib><creatorcontrib>Moore, Richard</creatorcontrib><creatorcontrib>Bosch, Ronald J</creatorcontrib><creatorcontrib>Tang, Tian</creatorcontrib><creatorcontrib>Hall, H Irene</creatorcontrib><creatorcontrib>Kaplan, Edward H</creatorcontrib><title>A Flow-Based Model of the HIV Care Continuum in the United States</title><title>Journal of acquired immune deficiency syndromes (1999)</title><addtitle>J Acquir Immune Defic Syndr</addtitle><description>BACKGROUND:Understanding 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. METHODS:Using 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. RESULTS:HIV-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%. 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METHODS:Using 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. RESULTS:HIV-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%. 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subjects Acquired immune deficiency syndrome
AIDS
AIDS/HIV
Anti-HIV Agents - therapeutic use
Antiretroviral agents
Antiretroviral drugs
Antiretroviral therapy
CD4 Lymphocyte Count
Continuity of Patient Care - statistics & numerical data
Cross-Sectional Studies
Disease control
Female
HIV
HIV Infections - drug therapy
HIV Infections - mortality
HIV Infections - virology
Human immunodeficiency virus
Humans
Immunology
Male
Models, Theoretical
Patients
Population Surveillance
Probability
Queues
Therapy
United States - epidemiology
Viral Load
Virology
title A Flow-Based Model of the HIV Care Continuum in the United States
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