Cost Effectiveness of Routine and Targeted HIV Testing, Washington, DC, 2011.

<p>¹⁾ the number of averted HIV transmissions is estimated by multiplying the number of persons with HIV who became aware of their status and the difference in transmission rates before and after knowing their HIV status. h = d * [f–g].</p><p>²⁾ The average HIV transmission rate for all groups was used for the number of averted transmissions.</p><p><b>Source</b>: Program Evaluation and Monitoring System (PEMS), Fiscal year 2011 Washington, DC DOH</p><p>Cost Effectiveness of Routine and Targeted HIV Testing, Washington, DC, 2011.</p

Factors associated with select IOM-defined care indicators, DC Cohort, 2011–2016^a^,^b^,^c.

<p>Factors associated with select IOM-defined care indicators, DC Cohort, 2011–2016<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0186036#t004fn001" target="_blank">^a</a>^,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0186036#t004fn002" target="_blank">^b</a>^,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0186036#t004fn003" target="_blank">^c</a>.</p

Proportion of DC cohort participants meeting criteria for selected HHS and IOM indicators for quality of care, DC cohort, 2011–2016.

<p>This figure represents individuals who were enrolled in the DC Cohort as of September 30, 2016 and met the criteria for selected Department of Health and Human Services and Institute of Medicine HIV quality of care indicators. While high proportions of participants met the HIV-related indicators (69%-95%), screening for sexually transmitted infections was relatively low (26%-51%).</p

HHS and IOM quality of care indicators assessed using DC Cohort study data^a.

<p>HHS and IOM quality of care indicators assessed using DC Cohort study data<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0186036#t001fn001" target="_blank">^a</a>.</p

Attitudinal barriers to HIV testing by City.

<p>Attitudinal barriers to HIV testing by City.</p

Characterization of HIV diversity, phylodynamics and drug resistance in Washington, DC

<div><p>Background</p><p>Washington DC has a high burden of HIV with a 2.0% HIV prevalence. The city is a national and international hub potentially containing a broad diversity of HIV variants; yet few sequences from DC are available on GenBank to assess the evolutionary history of HIV in the US capital. Towards this general goal, here we analyze extensive sequence data and investigate HIV diversity, phylodynamics, and drug resistant mutations (DRM) in DC.</p><p>Methods</p><p>Molecular HIV-1 sequences were collected from participants infected through 2015 as part of the DC Cohort, a longitudinal observational study of HIV+ patients receiving care at 13 DC clinics. Sequences were paired with Cohort demographic, risk, and clinical data and analyzed using maximum likelihood, Bayesian and coalescent approaches of phylogenetic, network and population genetic inference. We analyzed 601 sequences from 223 participants for <i>int</i> (~864 bp) and 2,810 sequences from 1,659 participants for <i>PR/RT</i> (~1497 bp).</p><p>Results</p><p>Ninety-nine and 94% of the <i>int</i> and <i>PR/RT</i> sequences, respectively, were identified as subtype B, with 14 non-B subtypes also detected. Phylodynamic analyses of US born infected individuals showed that HIV population size varied little over time with no significant decline in diversity. Phylogenetic analyses grouped 13.5% of the <i>int</i> sequences into 14 clusters of 2 or 3 sequences, and 39.0% of the <i>PR/RT</i> sequences into 203 clusters of 2–32 sequences. Network analyses grouped 3.6% of the <i>int</i> sequences into 4 clusters of 2 sequences, and 10.6% of the <i>PR/RT</i> sequences into 76 clusters of 2–7 sequences. All network clusters were detected in our phylogenetic analyses. Higher proportions of clustered sequences were found in zip codes where HIV prevalence is highest (r = 0.607; P<0.00001). We detected a high prevalence of DRM for both <i>int</i> (17.1%) and <i>PR/RT</i> (39.1%), but only 8 <i>int</i> and 12 <i>PR/RT</i> amino acids were identified as under adaptive selection. We observed a significant (P<0.0001) association between main risk factors (men who have sex with men and heterosexuals) and genotypes in the five well-supported clusters with sufficient sample size for testing.</p><p>Discussion</p><p>Pairing molecular data with clinical and demographic data provided novel insights into HIV population dynamics in Washington, DC. Identification of populations and geographic locations where clustering occurs can inform and complement active surveillance efforts to interrupt HIV transmission.</p></div

Resources and funding barriers to HIV testing by City.

<p>Resources and funding barriers to HIV testing by City.</p

HIV Testing Policy, Funding, and Implementation Practices.

a<p>Community service organizations include homeless services, substance abuse recovery centers, life skills programs, housing assistance programs, faith-based organizations, and other community-oriented service organizations.</p>b<p>Five organizations participating in the Houston survey only use opt-out consent during pregnancy as required by Texas law but do not use opt-out consent otherwise. Therefore, the bulk of consent used for these organizations would be opt-in. Results if these organizations are re-classified into the “opt-in approach only” category: 26 (60.5%) organizations use opt-in approach only, 3 (7.0%) organizations use opt-out approach only, and 14 (32.6%) organizations use a combination of opt-in and opt-out consent.</p>c<p>Respondents could check more than one response.</p>d<p>Other responses in DC include general revenue (n = 1). Other responses in Houston include donations (n = 12) and general revenue (n = 2).</p>e<p>Other responses in DC include general revenue (n = 1). Other responses in Houston include donations (n = 8) and general revenue (n = 2). One Houston organization selected both donations and general revenue for a total of n = 9 organizations selecting “other”.</p>f<p>One Houston organization estimated 1–2 tests were completed. The average, 1.5 tests, was recorded as the response.</p><p>HIV Testing Policy, Funding, and Implementation Practices.</p

Staff capacity barriers to HIV testing by City.

<p>Staff capacity barriers to HIV testing by City.</p

HIV DNA polymorphism and drug resistant mutations (DRM).

<p>HIV DNA polymorphism and drug resistant mutations (DRM).</p