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

J Acquir Immune Defic Syndr. 2017 Aug 15;75(5):548-553. doi: 10.1097/QAI.0000000000001429.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Anti-HIV Agents / therapeutic use*
  • CD4 Lymphocyte Count
  • Continuity of Patient Care* / statistics & numerical data
  • Cross-Sectional Studies
  • Female
  • HIV Infections / drug therapy*
  • HIV Infections / mortality
  • HIV Infections / virology
  • Humans
  • Male
  • Models, Theoretical*
  • Population Surveillance
  • United States / epidemiology
  • Viral Load

Substances

  • Anti-HIV Agents

Grant support