Venue-Based Recruitment of Women at Elevated Risk for HIV: An HIV Prevention Trials Network Study

Background: The challenge of identifying and recruiting U.S. women at elevated risk for HIV acquisition impedes prevention studies and services. HIV Prevention Trials Network (HPTN) 064 was a U.S. multisite, longitudinal cohort study designed to estimate HIV incidence among women living in communities with prevalent HIV and poverty. Venue-based sampling (VBS) methodologies and participant and venue characteristics are described. Methods: Eligible women were recruited from 10 U.S. communities with prevalent HIV and poverty using VBS. Participant eligibility criteria included age 18–44 years, residing in a designated census tract/zip code, and self-report of at least one high-risk personal and/or male sexual partner characteristic associated with HIV acquisition (e.g., incarceration history). Ethnography was conducted to finalize recruitment areas and venues. Results: Eight thousand twenty-nine women were screened and 2,099 women were enrolled (88% black, median age 29 years) over 14 months. The majority of participants were recruited from outdoor venues (58%), retail spaces (18%), and social service organizations (13%). The proportion of women recruited per venue category varied by site. Most participants (73%) had both individual and partner characteristics that qualified them for the study; 14% were eligible based on partner risk only. Conclusion: VBS is a feasible and effective approach to rapidly recruit a population of women at enhanced risk for HIV in the United States. Such a recruitment approach is needed in order to engage women most at risk and requires strong community engagement

Estimating Design Effect and Calculating Sample Size for Respondent-Driven Sampling Studies of Injection Drug Users in the United States

Respondent-driven sampling (RDS) has become increasingly popular for sampling hidden populations, including injecting drug users (IDU). However, RDS data are unique and require specialized analysis techniques, many of which remain underdeveloped. RDS sample size estimation requires knowing design effect (DE), which can only be calculated post hoc. Few studies have analyzed RDS DE using real world empirical data. We analyze estimated DE from 43 samples of IDU collected using a standardized protocol. We find the previous recommendation that sample size be at least doubled, consistent with DE = 2, underestimates true DE and recommend researchers use DE = 4 as an alternate estimate when calculating sample size. A formula for calculating sample size for RDS studies among IDU is presented. Researchers faced with limited resources may wish to accept slightly higher standard errors to keep sample size requirements low. Our results highlight dangers of ignoring sampling design in analysis

Number of casual male sexual partners and associated factors among men who have sex with men: Results from the National HIV Behavioral Surveillance system

Abstract Background In 2006, the majority of new HIV infections were in MSM. We sought to describe numbers of casual sex partners among US MSM. Methods Data are from the first MSM cycle of the National HIV Behavioral Surveillance system, conducted from 2003 to 2005. Relationships between number of casual male sex partners within the previous year and demographic information, self-reported HIV status, and risk behaviors were determined through regression models. Results Among 11,191 sexually active MSM, 76% reported a casual male partner. The median casual partner number was three. Lower number of casual partners was associated with black race, Hispanic ethnicity, and having a main sex partner in the previous year. Factors associated with a higher number included gay identity, exchange sex, both injection and non-injection drug use. Being HIV-positive was associated with more partners among non-blacks only. Age differences in partner number were seen only among chat room users. Conclusions MSM who were black, Hispanic or had a main sex partner reported fewer casual sex partners. Our results suggest specific populations of MSM who may benefit most from interventions to reduce casual partner numbers.</p

Estimating the Number of Heterosexual Persons in the United States to Calculate National Rates of HIV Infection

<div><p>Background</p><p>This study estimated the proportions and numbers of heterosexuals in the United States (U.S.) to calculate rates of heterosexually acquired human immunodeficiency virus (HIV) infection. Quantifying the burden of disease can inform effective prevention planning and resource allocation.</p><p>Methods</p><p>Heterosexuals were defined as males and females who ever had sex with an opposite-sex partner and excluded those with other HIV risks: persons who ever injected drugs and males who ever had sex with another man. We conducted meta-analysis using data from 3 national probability surveys that measured lifetime (ever) sexual activity and injection drug use among persons aged 15 years and older to estimate the proportion of heterosexuals in the United States population. We then applied the proportion of heterosexual persons to census data to produce population size estimates. National HIV infection rates among heterosexuals were calculated using surveillance data (cases attributable to heterosexual contact) in the numerators and the heterosexual population size estimates in the denominators.</p><p>Results</p><p>Adult and adolescent heterosexuals comprised an estimated 86.7% (95% confidence interval: 84.1%-89.3%) of the U.S. population. The estimate for males was 84.1% (CI: 81.2%-86.9%) and for females was 89.4% (95% CI: 86.9%-91.8%). The HIV diagnosis rate for 2013 was 5.2 per 100,000 heterosexuals and the rate of persons living with diagnosed HIV infection in 2012was 104 per 100,000 heterosexuals aged 13 years or older. Rates of HIV infection were >20 times as high among black heterosexuals compared to white heterosexuals, indicating considerable disparity. Rates among heterosexual men demonstrated higher disparities than overall population rates for men.</p><p>Conclusions</p><p>The best available data must be used to guide decision-making for HIV prevention. HIV rates among heterosexuals in the U.S. are important additions to cost effectiveness and other data used to make critical decisions about resources for prevention of HIV infection.</p></div

Adult and adolescent heterosexuals living with diagnosed HIV infection- United States, 2012.

<p>*Number of cases attributable to heterosexual contact, statistically adjusted to account for reporting delays and missing risk factor information, but not for incomplete reporting.</p><p>^†Per 100,000 heterosexuals.</p><p>^§ Hispanics/Latinos may be of any race.</p><p>^¶ Other race includes American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, unknown race/ethnicity, and multiple races.</p><p>** Relative standard error >30% for meta-analysis estimate of the population proportion heterosexual for this group.</p><p>Note. Data include persons age 13 years and older with a diagnosis of HIV infection regardless of stage of disease at diagnosis. CI = confidence interval</p

Diagnoses of HIV infection among adult and adolescent heterosexuals, by selected characteristics—United States, 2013.

<p>*Number of cases attributable to heterosexual contact, statistically adjusted to account for reporting delays and missing risk factor information, but not for incomplete reporting.</p><p>^†Per 100,000 heterosexuals.</p><p>^§ Hispanics/Latinos may be of any race.</p><p>^¶ Other race includes American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, unknown race/ethnicity, and multiple races.</p><p>** Relative standard error >30% for meta-analysis estimate of the population proportion heterosexual for this group.</p><p>Note. Data include persons age 13 years and older with a diagnosis of HIV infection regardless of stage of disease at diagnosis. CI = confidence interval</p

Estimated proportion of heterosexual persons in the United States, by sex, race/ethnicity, and age group--meta-analysis of 3 national surveys^*.

<p>*Surveys used in the meta-analysis: General Social Survey (2010); NHANES = National Health and Nutrition Examination Survey (2009–2010); NSFG = National Survey of Family Growth (2006–2010). See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133543#pone.0133543.t001" target="_blank">Table 1</a> for description of each survey.</p><p>^† Relative Standard Error (RSE) = 30–49%.</p><p>CI = confidence interval.</p