German, Danielle PhD, MPH*; Sifakis, Frangiscos PhD†; Maulsby, Cathy PhD*; Towe, Vivian L PhD‡; Flynn, Colin P ScM§; Latkin, Carl A PhD*; Celentano, David D ScD†; Hauck, Heather MSW§; Holtgrave, David R PhD*
Since the late 1990s, the gay community's early success in initiating risk reduction behavior change and slowing the rate of new cases of HIV/AIDS1-3 has been overshadowed by evidence of a resurgence of HIV/AIDS among men who have sex with men (MSM) in the United States. HIV infection rates among MSM have climbed steadily since the early 1990s, now accounting for more than half of new infections.4 The rate of new HIV diagnosis among MSM is 44 times higher compared with non-MSM men.5
Throughout the MSM HIV/AIDS epidemic, black men have been at particular risk. In 1986, nearly 15% of cumulative AIDS cases in homosexual and bisexual men occurred among black men.6 By the end of 2007, black MSM comprised more than one fourth of the cumulative reported AIDS cases among MSM7 and 35% of new infections among MSM were among blacks.8
Maryland had the second highest estimated AIDS diagnosis rate in the United States in 2008.9 Baltimore is the location hardest hit by HIV/AIDS in Maryland, accounting for 78% of prevalence in the central region. MSM account for 24% of HIV/AIDS prevalence and represents the only transmission category in central Maryland for which HIV incidence is increasing.10
There are more new HIV infections among black MSMs aged 13 to 29 years than any other age or race/ethnic group.8 In Maryland, one in five black MSMs are estimated to be HIV-positive compared with one in 24 Hispanic/Latino MSM and one in 38 white MSM.11 The Young Men's Survey (YMS) showed that young black MSM in Baltimore had the highest percent prevalence of HIV infection, HIV incidence12 and unrecognized HIV infection13 among seven participating cities.
The Centers for Disease Control and Prevention National HIV Behavioral Surveillance System (NHBS) collects behavioral data among populations at high risk for HIV, including MSM, in selected US areas with high HIV prevalence.14 Recently released 2008 findings show that 19% of MSMs are HIV-positive and 44% of HIV-positive men are unaware of their HIV status nationwide.15 HIV prevalence and unrecognized HIV infection was highest among black MSMs. Among participating cities, HIV prevalence ranged from 6% in Atlanta to 39% in Baltimore. Unrecognized infection ranged from 15% in Seattle to 73% in Baltimore. These high rates of HIV and unrecognized infection among Baltimore MSMs further bolster a need to understand social and behavioral correlates of HIV in this city.
Research among young MSM in Baltimore shows strong racial disparities in HIV infection16,17 and HIV incidence.18 Older age, recent sexually transmitted disease diagnosis, and high numbers of sex partners have also been associated with HIV among young Baltimore MSM.16 It is unknown whether these findings can be generalized to the larger community of MSMs in Baltimore. Additionally, little is known about factors associated with unrecognized HIV infection in this population. The NHBS project, known as the Behavioral Surveillance Research (BESURE) Study in Baltimore, recruited MSMs in 2005 and 2008. Using data from both BESURE MSM waves, the current article examined the extent of racial disparity and correlates of HIV prevalence and awareness of HIV seropositivity at each time point.
Sampling Design and Recruitment
The BESURE Study (NHBS Baltimore) is an HIV infection and behavioral risk cross-sectional survey among populations at high risk for HIV. The methods and sampling for NHBS-MSM have been previously described in detail.15,19 Two serial cross-sectional waves of venue-based data collection were conducted among MSM in Baltimore. The first was conducted between June 2004 and April 2005 and the second between July and October 2008. Study protocols for both waves were identical.
Formative research included focus groups with MSM and interviews with community informants and public health practitioners to identify current public and private venues (eg, bars, clubs, businesses, events, neighborhood locations) frequently attended by Baltimore MSMs and high-traffic day/time periods for recruitment. Sampling frames were subsequently constructed from the universe of venues and their corresponding day/time periods and 15 or more venue-day-time periods (ie, sampling events) were randomly selected and scheduled for recruitment each month. Sampling events averaged 18 per month in both waves.
During each sampling event, study recruiters consecutively approached men who crossed a predetermined intercept area at the venue and assessed eligibility. Eligible participants were: males 18 years or older, Baltimore-Towson metropolitan area residents, and had not previously participated in the current data collection wave; sexual identity or practice did not preclude men from being eligible. Eligible men completed study procedures either in a nearby mobile unit or in study offices at another scheduled time. All study procedures were anonymous. Consent was provided orally and documented in writing by trained interviewers. Consent for HIV testing was provided separately and not required for study participation in either wave. After completing informed consent procedures, participants were interviewed using a handheld computer-assisted standard questionnaire, provided a serum sample for HIV testing, received counseling and referral to prevention services, and received US $50 as reimbursement for their time. Follow-up appointments were scheduled within 2 weeks for HIV test results, posttest counseling, and referral to care or services as appropriate. The protocol and all study materials were reviewed and approved by the Maryland Department of Health and Mental Hygiene and The Johns Hopkins Bloomberg School of Public Health Institutional Review Boards.
The standardized questionnaire included demographics, HIV-related risk behaviors, medical history, and sexual identity. Race/ethnicity categories were non-Hispanic white, black, Hispanic, Native American, Pacific Islander, Asian-American, or of mixed race (ie, participants who reported being of more than one racial/ethnic ancestry). Because small numbers of Hispanic, Native American, Pacific Islander, Asian-American, and mixed race participants precluded detailed analysis, a single category called “other race” was created in addition to categories for non-Hispanic white and black. Age was categorized to reflect quartiles of the age distribution of study participants. Being currently homeless was examined as a binary variable, whereas education was reported as the level attained at the time of the survey.
Participants were asked about HIV risk behaviors over their lifetimes and in the prior year. Recent sexual risk behaviors included number of male sexual partners (categorized to reflect quartiles of number of partners), sex with men only or sex with men and women, and unprotected anal intercourse (UAI). UAI was defined as not using a condom during one or more sex acts in the prior 12 months and categorized as “no UAI,” UAI only with a main male sexual partner, or UAI with at least one casual or exchange (ie, sex in exchange for money or goods) male sexual partner. Lifetime variables included having received a prior HIV test, having injected illicit drugs, and having had a sexually transmitted disease diagnosis. Behaviors in the past year included having used nonprescribed drugs and having visited a doctor's office. Finally, participants reported whether they had no, public, or private insurance coverage.
Blood specimens with sufficient volume were tested for HIV-1 antibodies by the Maryland Department of Health and Mental Hygiene Laboratories Administration with a US Food and Drug Administration-licensed enzyme immunoassay (Sanofi Diagnostics Pasteur, Chaska, MN). The Maryland Department of Health and Mental Hygiene Laboratory confirmed repeatedly reactive samples using Western blot (Bio-Rad, Hercules, CA, or Epitope, Inc, Organon-Teknika Corporation, Durham, NC). An HIV-seropositive individual was defined as having a reactive enzyme immunoassay with a positive Western blot confirmation. Three respondents with indeterminant test results were excluded from the analysis. Unrecognized HIV infection was defined as having a confirmed HIV positive BESURE Study test and either reporting a negative or an unknown prior HIV test result during the survey. This category also included three respondents who refused to report results of their most recent test in the second wave.
Sample characteristics between Wave 1 and Wave 2 were compared using the chi-square statistic. Analyses with HIV positivity as the outcome were restricted to the 645 men and 448 men who reported a same-sex experience within the past year in the first and second cross-sectional waves, respectively, and whose HIV test results were definitive. Analyses of unrecognized HIV infection were restricted to the 243 MSMs and 168 MSMs who tested HIV positive in the first and second cross-sectional waves, respectively. We assessed patterns of attendance at venues types included in the sampling frame. There was no association between frequency of venue attendance and the two outcomes of interest and data are presented and analyzed without weights.20
Associations between demographic variables and HIV risk behaviors with HIV prevalence and HIV unrecognized infection were assessed using the chi-square statistic. Unadjusted prevalence ratios were calculated with corresponding 95% confidence intervals using SAS (SAS Institute Inc, Cary, NC) PROC GENMOD's log-binomial regression capability with a binomial distribution and a logarithmic link function.21 Variables that showed a significant association with HIV prevalence or with HIV unrecognized infection (P ≤ 0.05) were analyzed using the COPY method to directly estimate adjusted prevalence ratios with their corresponding 95% confidence interval.22 Both unadjusted and adjusted PROC GENMOD analyses used the REPEATED statement to account for clustering by venue. The prevalence ratio was deemed as a more appropriate measure of association and a better approximation of the relative risk because the frequency of both outcomes exceeded 15%.23,24 We arrived at the most parsimonious model by removing variables that were insignificant (P > 0.05) using a backward stepwise approach and as determined by the likelihood ratio test. QIC was used to assess model fit. All statistical analyses were performed using Statistical Analysis Software (SAS) Version 9.1.
Participant and Sample Characteristics
Figure 1 shows recruitment and venue information for both waves. During the first cross-sectional wave (2004-2005), 1296 men were approached to participate. After eligibility and enrollment, 891 had complete survey and serologic information and 645 reported a same-sex experience in the year before the survey (Fig. 1). Eligible participants were recruited from 74 venues with mean venue sample size of 8.3 (standard deviation, 14.6; range, 1-88). During the second cross-sectional wave (2008), 1326 men were approached for participation. After eligibility and enrollment, 600 participants had complete survey and serologic information and 448 reported a prior year same-sex experience (Fig. 1). In Wave 2, eligible participants were recruited from 31 venues with mean venue sample size of 13.6 (standard deviation, 9.0; range, 2-35).
The demographic and HIV risk behavior composition of the two samples from the two waves differed (Table 1). Compared with the first cross-sectional wave, the second cross-sectional wave was more likely to enroll MSM who reported: black race; being younger than 24 years of age; homelessness; having had two to three male sexual partners in the past year; having had male sexual partners only; not having had UAI; using noninjection drugs in the past year; and lifetime drug injection. The two samples did not statistically differ in educational attainment, ever receiving an HIV test, ever receiving a sexually transmitted infection diagnosis, health insurance status, or past year doctor visits.
In the first cross-sectional wave, median age was 34 years (range, 18-69 years), 70% were of a minority race, and more than half reported postsecondary education. Most reported being homosexual/gay (63%), never injecting illegal drugs (83%), no sexually transmitted disease diagnosis (84%), and had been tested for HIV (87%). In the prior year, 67% had sex with men only and 74% had more than one same-sex partner. Approximately half reported using noninjected illegal drugs of which marijuana (76%) was most common followed by cocaine (47%) and crack cocaine (25%). Approximately 60% had some form of health insurance and 77% had visited a doctor in the past year. Median time since last HIV test was 276 days.
In the second cross-sectional study, median age was 30 years (range, 18-72 years), 77% were of a minority race, and more than half reported postsecondary education. Most reported being homosexual/gay (68%), never injecting drugs (94%), no sexually transmitted disease diagnosis (81%), and having ever tested for HIV (90%). Three fourths had sex with men only and the majority reported multiple male partners in the past year. Among the 59% who reported noninjected illegal drug use, marijuana was most common (89%) followed by cocaine (28%) and crack cocaine (20%). The majority had some form of health insurance and 81% had visited a doctor in the past year. Median time since last HIV test was 305 days.
Prevalence of HIV Infection and Associated Factors
Prevalence of HIV infection by socioeconomic and behavioral characteristics is presented in Table 2 for both cross-sectional recruitment waves. In 2004-2005, 38% of participants tested HIV-positive. HIV prevalence by race was 51% among black MSM, 13% among non-Hispanic white MSM, and 24% among other MSM of color. Table 3 shows the results of univariate and multivariate analyses of prevalent HIV infection for both waves of data collection. In the first wave, minority race, being older than 24 years, having nine or more partners, sexually transmitted disease diagnosis, having public health insurance, and a doctor's visit in the prior year were significantly and independently associated with being HIV-positive. Older MSMs were 1.4 to 1.8 times more likely to be HIV-positive compared with 18 to 24 year olds. Black MSMs were approximately 3.7 times and other race MSMs were 2.0 times more likely to be HIV-positive than non-Hispanic white MSMs.
In the second wave, 38% of participants overall, 45% of black, 18.3% of non-Hispanic white MSM, and 25% of other men of color tested HIV-positive. HIV infection was significantly and independently associated with black race, UAI with casual or exchange male partners in the prior year (compared with no UAI), and prior sexually transmitted infection diagnosis. Risk of being HIV-positive among black MSM was 2.5 times higher than among non-Hispanic white MSMs.
Prevalence of Unrecognized HIV Infection and Associated Factors
Prevalence of unrecognized HIV infection by socioeconomic and behavioral factors is shown in Table 2 for both cross-sectional recruitment waves. In the first wave, 58% of HIV-positive MSMs were unaware of their HIV-positive serostatus at the time of enrollment. Of these, 57% reported their most recent test was negative, 20% did not obtain the results of their most recent test, 3% had a recent indeterminant test, less than 1% had never been tested, and 20% did not know results of their most recent test. The proportion unrecognized HIV infection was higher among younger men, from 38% among those 45 years or older to 89% among those 18 to 24 years of age. By race, the proportion of unrecognized HIV infection ranged from 64% among black men to 15% among non-Hispanic white participants.
Table 4 shows the results of univariate and multivariate analyses of characteristics associated with unrecognized HIV infection. In the first wave, unrecognized infection was higher among those who reported minority race/ethnicity, younger age, multiple partners, UAI with main partners, no sexually transmitted disease diagnosis, no health insurance, and no doctor visit in the past year. In multivariate analysis, minority race/ethnicity, decreasing age, having two to three partners (compared with one), having no health insurance (compared with private insurance), and not visiting a doctor in past year were significantly associated with unrecognized HIV infection (Table 3). Controlling for these factors, black MSMs were four times as likely and other MSMs of color were 3.5 times as likely to have unrecognized infection than non-Hispanic white MSMs.
In the second wave (2008), 74% of HIV-positive participants were unaware of their HIV-positive serostatus. Among these, 67% reported their most recent test was negative, 15% did not obtain the results of their most recent test, 4% had a recent indeterminant test, 0% had never been tested, 5.7% did not know results of their most recent test, and 2.4% refused to answer. Seventy-seven percent of black MSMs did not know they were HIV positive compared with 47% of non-Hispanic white MSM. None of the six HIV-positive men of other race/ethnicity were aware of their HIV status. Unrecognized infection was significantly higher among men of other race/ethnicity and who had both male and female partners but significantly lower among men older than 45 years, those with public insurance (compared with no insurance), and those who had seen a doctor in the past year. In multivariate analysis, men older than 45 years and those who had visited a doctor in the past year were 35% less likely and approximately 20% less likely, respectively, to be unaware of their HIV infection.
These results show a high prevalence of HIV infection and unrecognized HIV infection among MSM in Baltimore in 2005 and 2008, particularly among men of color and young men. Two Centers for Disease Control and Prevention reports have compared HIV prevalence and unrecognized infection rates among MSM in US cities. In 2005, MSMs in Baltimore had the highest HIV prevalence and undiagnosed infection rates compared with their counterparts in Los Angeles, Miami, San Francisco, and New York25 and, in 2008, rates in Baltimore exceeded those of 20 other high prevalence cities.15 A recent study estimated that racial disparities in MSM HIV infection were highest in Maryland compared with 16 other southern states (Maryland rate ratio, 7.1; P < 0.001 versus total 4.6, P < 0.001).11 Although it is possible that the NHBS HIV prevalence rankings are confounded by racial differences across cities, the current study confirms the disproportionate HIV burden borne by black and other minority MSMs in Baltimore. There is a very real possibility that the HIV epidemic among MSM may further expand, particularly given the high levels of unrecognized infection among young MSMs and UAI among men unaware of their HIV infection.
Despite the different demographic and behavioral compositions of these two recruitment waves, overall HIV prevalence was consistent. These findings corroborate reports of high HIV prevalence among MSMs from other cities24 and expand on prior reports of pronounced racial disparity in HIV among young Baltimore MSMs.17,18 Recent attention to HIV resurgence among US MSM may not fully account for the historically high HIV prevalence among black MSMs as observed in Baltimore. HIV infection in these studies among adult MSMs was much higher than the in 1996-2000 YMS study among young MSM in Baltimore, which reported 12% prevalence overall and 27% among non-Hispanic blacks,16 yet the similarity in demographic and behavioral correlates of infection between this study and the YMS findings suggests that there are persistent prevention needs in Baltimore.
Notably, the majority of men who tested HIV-positive in both waves of data collection were not aware of their HIV status. Beginning in 2001, the Centers for Disease Control and Prevention recommended greater emphasis on finding undiagnosed HIV infections26 and later revised the recommendation to enhance testing in healthcare settings.27 Although the effectiveness and cost of this approach relative to other HIV testing policies has been debated,28 the current study examined the burden of unrecognized HIV infection and racial disparities of unrecognized infections among MSMs in Baltimore at two time points following these recommendations. The very high observed proportion of participants who were unaware of their HIV infection suggests that testing efforts are not adequately reaching MSMs in Baltimore, particularly minority and young MSMs, which in turn limits access to the benefits of HIV treatment and secondary prevention.
Known HIV infection was associated with a doctor visit, suggesting that clinical settings are feasible venues to target some MSMs and may be effectively providing testing services. However, many primary healthcare providers miss opportunities to provide HIV testing29 and counseling.30 Given the high HIV prevalence rates and multiple risk behaviors, a diverse portfolio of HIV behavioral interventions along with routine testing and counseling will be needed to adequately meet the challenges of the current epidemic. This study used a structured venue-based sampling method to recruit participants. A similar methodology for outreach HIV testing efforts and other prevention programming may be viable for increasing service availability for Baltimore MSMs.
These findings are subject to numerous limitations. Temporal relationships cannot be determined as a result of the cross-sectional design in both waves and temporal trend comparisons are not definitive, because they may be the result of true differences or the recruitment of different samples. Differential enrollment bias may have occurred between the two waves. Although the study protocols were identical, qualitative differences in implementation may have occurred. The venue universe differed between waves and this may also have contributed to differences between the 2004-2005 and 2008 samples. Demographic and HIV risk behavior data were self-reported and therefore subject to misreporting as a result of recall or social desirability, concerns about stigma, or cultural differences. Some men who knew their HIV status to be positive may have reported negative status as a result of perceived stigma or concern about study eligibility, although materials clearly described eligibility and reinforced anonymity and staff members were trained in rapport-building and cultural sensitivity. Lack of disclosure resulting from stigma concerns may also be a barrier to partner disclosure and a worthy target of prevention efforts. Sexual behavior and drug use measures were summary measures, which may limit interpretation. Findings may not be generalizable to MSMs who do not frequent study recruitment venues, who only frequent less well-attended venues, or do not reside in the Baltimore-Towson metropolitan area. There may also be residual bias and underestimation of uncertainty because the data were not weighted by venue attendance patterns and likelihood of recruitment.
Despite limitations, these BESURE surveys provide a needed assessment of urban MSMs and a useful foundation for future research and HIV prevention planning. That these two recruitment waves were demographically different but had similar epidemiologic profiles suggests a broad need for prevention across the diverse population of Baltimore MSMs. These surveys indicate that venue-based recruitment methods are feasible for reaching diverse MSM populations and may be useful for HIV testing and prevention programs. Given that demographic and behavioral characteristics did not alter the association between race/ethnicity and HIV status, it is likely that individual-level explanations are insufficient to explain the observed disparities. Input from local community members, providers, and researchers points to the following to combat the strikingly pronounced epidemiologic disparities observed here: culturally sensitive health care and structural prevention approaches to reduce stigma and discrimination toward same-sex behavior and HIV infection; interventions that increase procondom use norms; prevention for positives; integration of prevention and medical care; and contextualized prevention strategies that address men who have sex with both women and men. It is imperative to implement interventions that are not only ethnically diverse, but also ones that acknowledge and embrace the diversity of ethnic, sexual, and social identities and lifestyles among urban MSMs.
We express gratitude to the BESURE Study field staff, NHBS colleagues, and the men who participated in this study.
1. Martin JL, Garcia MA, Beatrice ST. Sexual behavior changes and HIV antibody in a cohort of New York City gay men. Am J Public Health
2. Winkelstein W Jr, Samuel M, Padian NS, et al. The San Francisco Men's Health Study: III. Reduction in human immunodeficiency virus transmission among homosexual/bisexual men, 1982-86. Am J Public Health
3. Winkelstein W Jr, Wiley JA, Padian NS, et al. The San Francisco Men's Health Study: continued decline in HIV seroconversion rates among homosexual/bisexual men. Am J Public Health
4. Hall HI, Song R, Rhodes P, et al. Estimation of HIV incidence in the United States. JAMA
6. Centers for Disease Control and Prevention. AIDS Weekly Surveillance Report, December 29, 1986
. Atlanta: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2006.
7. Centers for Disease Control and Prevention. HIV/AIDS Surveillance Report, 2005
. Atlanta: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2007.
8. Centers for Disease Control and Prevention. Subpopulation estimates from the HIV incidence surveillance system--United States, 2006. MMWR Morb Mortal Wkly Rep
9. Centers for Disease Control and Prevention. Diagnoses of HIV Infection and AIDS in the United States and Dependent Areas, 2008. HIV Surveillance Report
. Atlanta: CDC; 2008:20.
10. Maryland Department of Health and Mental Hygeine. HIV/AIDS in Central Maryland: An Epidemiologic Profile
. Baltimore: Center for Surveillance and Epidemiology, Infectious Disease and Environmental Health Administration, Maryland Department of Health and Mental Hygiene; 2009.
11. Lieb S, Prejean J, Thompson DR, et al. HIV prevalence rates among men who have sex with men in the Southern United States: population-based estimates by race/ethnicity. AIDS Behav
. 2010 Sep 25 [Epub ahead of print].
12. Centers for Disease Control and Prevention. HIV incidence among young men who have sex with men-seven US cities, 1994-2000. MMWR Morb Mortal Wkly Rep
13. MacKellar DA, Valleroy LA, Secura GM, et al. Unrecognized HIV infection, risk behaviors, and perceptions of risk among young men who have sex with men: opportunities for advancing HIV prevention in the third decade of HIV/AIDS. J Acquir Immune Defic Syndr
14. Gallagher KM, Sullivan PS, Lansky A, et al. Behavioral surveillance among people at risk for HIV infection in the US: the National HIV Behavioral Surveillance System. Public Health Rep
. 2007;122(Suppl 1):32-38.
15. Centers for Disease Control and Prevention. The prevalence of human immunodeficiency virus (HIV) and awareness of HIV infection among men who have sex with men-21 cities, United States, 2008. MMWR Morb Mortal Wkly Rep
16. Sifakis F, Hylton JB, Flynn C, et al. Prevalence of HIV infection and prior HIV testing among young men who have sex with men. The Baltimore Young Men's Survey. AIDS Behav
17. Celentano DD, Sifakis F, Hylton J, et al. Race/ethnic differences in HIV prevalence and risks among adolescent and young adult men who have sex with men. J Urban Health
18. Sifakis F, Hylton JB, Flynn C, et al. Racial disparities in HIV incidence among young men who have sex with men: the Baltimore Young Men's Survey. J Acquir Immune Defic Syndr
19. MacKellar DA, Gallagher KM, Finlayson T, et al. Surveillance of HIV risk and prevention behaviors of men who have sex with men--a national application of venue-based, time-space sampling. Public Health Rep
. 2007;122(Suppl 1):39-47.
20. MacKellar D, Valleroy L, Karon J, et al. The Young Men's Survey: methods for estimating HIV seroprevalence and risk factors among young men who have sex with men. Public Health Rep
. 1996;111(Suppl 1):138-144.
21. Spiegelman D, Hertzmark E. Easy SAS calculations for risk or prevalence ratios and differences. Am J Epidemiol
22. Deddens, JA, Petersen MR. Approaches for estimating prevalence ratios. Occup Environ Med
23. McNutt LA, Wu C, Xue X, et al. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol
24. Zochetti C, Consonni D, Bertazzi P. Estimation of prevalence rate ratios from cross-sectional data. Int J Epidemiol
25. Centers for Disease Control and Prevention. HIV prevalence, unrecognized infection, and HIV testing among men who have sex with men--five US cities, June 2004-April 2005. MMWR Morb Mortal Wkly Rep
26. Janssen RS, Holtgrave DR, Valdiserri RO, et al. The serostatus approach to fighting the HIV epidemic: Prevention strategies for infected individuals. Am J Public Health
27. Branson BM, Handsfield HH, Lampe MA, et al. Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep
28. Holtgrave DR, Pinkerton SD. Can increasing awareness of HIV seropositivity reduce infections by 50% in the United States? J Acquir Immune Defic Syndr
29. Liddicoat RV, Horton NJ, Urban R, et al. Assessing missed opportunities for HIV testing in medical settings. J Gen Intern Med
30. Tao G, Branson BM, Anderson LA, et al. Do physicians provide counseling with HIV and STD testing at physician offices or hospital outpatient departments? AIDS
© 2011 Lippincott Williams & Wilkins, Inc.