Primary acquisition of drug-resistant HIV at the time of initial infection, referred to as transmitted drug resistance (TDR), is an underappreciated public health challenge. Of the estimated 48 600 HIV infections in the US in 2006 , approximately 7100 involved acquisition of HIV already resistant to at least one antiretroviral . Two different mechanisms for TDR have been proposed. In the first scenario, patients in care but suboptimally adherent to antiretrovirals acquire resistance mutations [3–6] and transmit them to others. In the second scenario, viremic persons initially infected with resistant HIV pass it on to recipients  during sexual or needle-sharing risk behaviour [8–10]. Both mechanisms likely contribute to the stable approximately 10–20% prevalence of TDR seen in North America [11–15] and Europe [16–19]. Although opinions differ on which is the more significant of the two [7,20,21], opportunities clearly exist for persons already engaged in HIV care to transmit resistant viruses to others.
Over 70% of HIV-infected persons report some form of sexual activity following their HIV diagnosis , but estimates of the proportion engaging in unprotected sex vary considerably. As many as 60% of seropositive men and women use condoms inconsistently with primary or casual sex partners [22–26]. Investigations into behavioural change following HIV diagnosis among MSM demonstrate a period of decreased risk behaviour , with half relapsing to unprotected sex within three years [28,29]. A small but significant proportion of individuals (<5%) report no change in risk behaviours following diagnosis .
Patients who engage in ongoing risk behaviour tend to be less adherent to prescribed antiretroviral regimens [30–34]. This combination of poor antiretroviral adherence and sexual (or injection drug) risk activity provides a pathway for the transmission of resistance. Evidence suggests that although this subgroup of nonadherent patients is small, they may contribute disproportionately to the forward transmission of resistant viruses [32,34]. We sought to better characterize the extent to which nonadherent patients contribute to the risk of TDR, using cross-sectional clinical and behavioural data from the University of North Carolina at Chapel Hill (UNC) Center for AIDS Research HIV Clinical Cohort (UCHCC). The present study had two aims: to examine patterns of nonadherence, high-risk sexual behaviour, detectable HIV viraemia and antiretroviral drug resistance, and to identify factors associated with potential transmission of drug-resistant HIV among patients engaged in HIV care.
Materials and methods
Patients and design
All HIV-infected patients aged at least 18 years and receiving HIV care at the UNC Infectious Diseases Clinic are approached for their willingness to participate in the ongoing, observational UCHCC study. Written informed consent is obtained from all individuals; less than 5% of patients decline participation. Clinical and demographic data are collected through standardized medical record abstractions at enrolment and every 6 months thereafter. Details about data collection, laboratory measurements and clinical care were previously described . To improve capture of social and behavioural data not consistently available in medical records, UCHCC participants were offered the opportunity to complete a comprehensive, standardized, face-to-face interview, the Clinical, Sociodemographic and Behavioral Survey (CSDS), which incorporates multiple validated instruments, including 4-day adherence recall  and alcohol and substance use assessments [37,38]. The present study is a retrospective, cross-sectional analysis at the time of interview. If a participant completed multiple interviews over time, only the most recent was included. Only patients with complete outcome data were included in our analysis.
Our primary outcome was a combination of having unprotected sex, detectable HIV viraemia and evidence of antiretroviral resistance around the time of the interview. We defined unprotected sex as having at least one sex partner in the past 6 months and not consistently using condoms. Detectable viraemia was defined as HIV RNA at least 400 copies/ml; the level closest to the interview date was used, within a window beginning 6 months prior and ending 1 month thereafter. As HIV RNA assays used during the collection of these data had lower limits of detection of either 400 or 50, patients with undetectable HIV RNA were assigned average values of 200 and 25, respectively, for use in calculating viral load distributions.
Resistance was defined by the 2009 WHO list of surveillance drug resistance mutations (SDRMs) , a curated list specifically created for epidemiological analyses of TDR prevalence . Genotypic resistance tests (GRTs) conducted prior to or on the interview day were included.
Two interview questions concerned antiretroviral adherence: ‘How many doses have you missed in the last 4 days: 0, 1, or 2 or more?’ and ‘Thinking about the past 4 weeks, on average how would you rate your ability to take all of your HIV medications as your doctor prescribed: excellent, very good, good, fair, poor or very poor?’ We considered at least one missed dose in the prior 4 days as not adherent. ‘Very good’ and ‘good’ were grouped together, as were ‘fair’, ‘poor’ and ‘very poor’.
Demographic, behavioural and clinical variables were described, and associations with unprotected sex and presence of a known SDRM were assessed. Wilcoxon rank-sum tests were used to compare continuous variables and Pearson's χ 2 test was used for categorical variables, with exact P values calculated where appropriate. Statistical significance was defined as a P value of less than 0.05.
On the basis of the number of sexual partners, condom utilization, HIV RNA detectability and presence of any SDRM, we constructed a flow chart to help define those individuals at a greater risk of transmitting drug resistance to others. Log-linear binomial regression models were used to calculate prevalence ratios and 95% confidence intervals (CI) associated with predictors of membership in this high-risk group. Bivariate associations with P values less than 0.1 were considered for inclusion in the multivariable analysis. All analyses were performed with SAS (version 9.3, SAS Institute, Cary, North Carolina, USA).
A number of sensitivity analyses were performed. Because patients may underestimate the number of partners or overestimate condom utilization, a bounded analysis was conducted to assess the range in the proportion of the study population at risk for transmitting drug-resistant HIV. Regression models were repeated to examine whether predictors remained the same with the expanded definition of the high-risk group.
The UNC Institutional Review Board previously approved the UCHCC and CSDS, which also covered associated secondary data analyses.
Of 482 unique face-to-face interviews completed between 2000 and 2011, 244 met inclusion criteria (Supplemental Figure, http://links.lww.com/QAD/A391). Median age was 43 years (range, 19–74 years; Table 1), and 37% were women. Nonwhite participants represented 79% of the sample; blacks accounted for 70%. A majority had at least a high school education, and 13% were college graduates. One-fifth of respondents described being homeless at some point since their HIV diagnosis. Thirty-eight percent were MSM (60% of male respondents). Thirty-two percent of included patients were interviewed in 2000–2003; 19% in 2004–2006; and 50% in 2007–2011. Demographics of interviewees were very similar to the overall UCHCC . Patients excluded from analysis due to incomplete data did not differ demographically, but had fewer diagnoses of clinical AIDS, higher CD4+ cell counts and less antiretroviral experience than those included in analysis (Supplemental Tables 1 and 2, http://links.lww.com/QAD/A391).
Median time from HIV diagnosis to interview was 8 years (range, 0.1–21.9 years; Table 2), with 28% meeting a clinical definition of AIDS during their care. Median CD4+ cell count among interviewees was 426 cells/μl (range, 9–1496 cells/μl), and 59% had HIV RNA viral loads below 400 copies/ml. Eighty-four percent of the group were on antiretrovirals, with a median of 6.7 years since their first regimen was prescribed (range, 0.1–20.4 years). Forty-four percent of participants were heavily treatment experienced, with exposure to more than four antiretroviral regimens. Only eight were antiretroviral-naive (3%).
Depression and substance use
Just over half had a history of depression (Table 1). Thirty-eight percent of participants noted active substance use at the time of the interview. Marijuana (23%) and crack cocaine (19%) were most common; injection drug use was rare (n = 2, 0.8%). Only 9% of respondents used alcohol heavily, defined as consumption at least four times per week.
Among the 204 participants on antiretrovirals when interviewed, 58% self-reported ‘excellent’ adherence (Table 2). Eight percent missed at least two doses in the prior 4 days. Viral loads were strongly associated with adherence; 80% of those self-reporting ‘excellent’ adherence had undetectable HIV RNA, compared with 48 and 24% among those with ‘good’ and ‘poor’ adherence, respectively (P < 0.01).
Sexual behaviour and condom utilization
Seventy percent of individuals reported some sexual activity in the prior 6 months (n = 172); among these, 23% had two to four partners (n = 39), and 6% reported more than four partners (n = 10). Nearly two-thirds of sexually active participants reported vaginal sex (56 women, 49 men), with 65 (61%) indicating they used a condom ‘all of the time’ for vaginal intercourse. Three women and 56 men had anal sex; only 49% consistently used condoms.
Factors associated with unprotected sexual activity
Participants reporting unprotected sex were younger than those who either consistently used condoms or were abstinent (41 versus 45 years, P < 0.01; Table 1). No sexual differences existed in frequency of unprotected sex, but MSM were more likely to report unprotected sexual activity than heterosexual men (P = 0.04). Unprotected sex was more common among active substance users (P = 0.04), and we observed nonsignificant trends towards more unprotected sex among whites and Native Americans (P = 0.40).
Persons with a clinical history of AIDS were less likely to report unprotected intercourse (P < 0.01; Table 2). Median viral loads were higher among interviewees reporting unprotected sex [295 copies/ml, interquartile range (IQR), 25–13 000 copies/ml] than among those who consistently used condoms or were abstinent (62 copies/ml, IQR, 25–3687 copies/ml; P = 0.04). Suboptimal adherence was nonsignificantly associated with unprotected sexual activity. Among individuals who reported unprotected sex, 20% missed at least one antiretroviral dose in the prior 4 days, compared with 13% among those not engaging in unprotected sex (P = 0.12). Those with self-assessed ‘good’ or ‘poor’ adherence were more likely to have unprotected intercourse than those with ‘excellent’ adherence (P = 0.33).
Prevalence of drug-resistant mutations
One hundred and thirty-one study participants (54%) had at least one SDRM (Fig. 1), including 12 antiretroviral-naive individuals with any SDRM at entry to care. The most frequently observed reverse transcriptase mutation was M184V, seen in 94 individuals (39%). K103N and K70R were also frequently detected (23 and 13% prevalence, respectively). The most common protease mutations were L90M (9%) and I54V (7%). Overall, 45% harboured SDRMs for nucleoside reverse transcriptase inhibitor (NRTIs) (n = 110), 31% had nonnucleoside reverse transcriptase inhibitor (NNRTI) resistance (n = 76) and 23% had protease inhibitor (PI) resistance (n = 56). Triple-class resistance was noted in 26 cases (11%).
Factors associated with drug-resistant mutations
Age, sex and race were not associated with having SDRMs (Table 1). However, those with a history of homelessness, depression or active cocaine use were more likely to have resistance (all P ≤ 0.04). Participants with a longer time since HIV diagnosis, a longer time on antiretrovirals or a greater number of regimens were more likely to have an SDRM (all P < 0.01). Compared with poorly adherent participants, those with excellent adherence harboured SDRMs less often (86 vs. 51%; P = 0.03). The proportion with newly identified resistance decreased over time (P = 0.1).
Potential transmission of drug resistance
As shown in Fig. 2, 70% reported sexual activity in the prior 6 months, and a majority used condoms inconsistently (n = 94). Among the 44 individuals with inconsistent condom use and HIV RNA more than 400 copies/ml, 30 had documented resistance (12% of the subset). Viraemia in this high-risk group was significant; 90% had HIV RNA more than 1500 copies/ml. Nine individuals had single-class resistance, 14 had dual-class and seven had triple-class SDRMs.
In bivariate analyses (Table 3), we found that individuals who completed some college education had a two-fold greater prevalence in the high-risk group (prevalence ratio 2.03, 95% CI, 1.02–4.02) and noted a nonsignificant trend towards a greater prevalence of MSM (prevalence ratio 1.89, 95% CI, 0.97–3.69). However, in bivariate and multivariate analyses, substance use and homelessness emerged as having the two strongest associations with membership in the high-risk group. Participants who used any illicit substance in the prior year or who reported heavy alcohol use had a three-fold greater prevalence in the high-risk group than nonusers [adjusted prevalence ratio (aPR) 3.12, 95% CI, 1.47–6.62]. Interviewees who reported any homelessness since HIV diagnosis had an adjusted high-risk group prevalence 2.2 times that of individuals with continuous housing (95% CI, 1.16–4.18).
Participant underestimation of sexual activity and/or overestimation of condom use would alter the proportion categorized into our defined high-risk group. Considering all patients with detectable drug-resistant viraemia as members of our high-risk group increased the size of this group to 56, or 23% of those with complete data. Our findings were consistent using this expanded high-risk group definition, with substance abuse (aPR 1.82, 95% CI, 1.15– 2.88) and homelessness since HIV diagnosis (aPR 1.99, 95% CI, 1.28– 3.10) remaining associated with risk of transmitting antiretroviral resistance to others.
Given revised US treatment guidelines advocating antiretroviral initiation for all HIV-infected persons regardless of CD4+ cell count  and a shift towards ‘test, link and treat’ models of HIV care , we are poised to see greater numbers of patients on therapy in the coming years. With this increase in the number of people taking antiretrovirals, we will likely observe an increase in the number of nonadherent patients engaged in sexual risk behaviour, even if the proportions of such patients observed in our study (12%) and other cohorts (5–20%) [31–34] remain unchanged. As this group may contribute disproportionately to transmission of resistant HIV , an expansion of TDR could be seen over time. Thus, improving our understanding of potential sources of TDR is perhaps more important than ever before.
In our cross-sectional study of HIV-infected patients in care, we observed all the requisite factors needed for sexual transmission of resistant HIV to occur. Forty percent reported suboptimal adherence to their antiretrovirals. Nearly 60% of sexually active participants had unprotected sex at least once in the previous 6 months and tended to be younger and active substance users. The presence of an SDRM was associated with active cocaine use, a history of homelessness since HIV diagnosis, depression and poor antiretroviral adherence. Finally, we found that the risk of having an opportunity to transmit resistant HIV was doubled by a history of homelessness and tripled by active substance use. The relationship of homelessness to the presence of antiretroviral mutations and potential TDR has not been previously reported, but housing instability is a recognized contributor to poorer adherence .
These findings add to the limited existing literature on the potential for sexual transmission of resistant HIV among patients in care. Because poor adherence often leads to the development of antiretroviral resistance , studies of opportunities for TDR have primarily examined the link between nonadherence and sexual risk behaviour. Several clinic-based cohort studies in the United States have shown that the odds of high-risk sexual behaviour are increased 1.5–2.5 times among patients with suboptimal antiretroviral adherence, despite significant differences among the studies in terms of demographics, geography and participant behaviours [30,31,34,44]; the prevalence of patients in this group ranged from 8.5  to 18% . Three additional studies took a more direct approach, focusing on patients with genotypically proven antiretroviral resistance who reported high-risk behaviour. Kozal et al.  studied 333 patients in care (but not necessarily taking antiretrovirals) and found that 23% reported unprotected anal or vaginal sex in the prior 3 months; among these, 18 had resistance, for an overall prevalence of 4.5%. Notably, this small subset reported 207 sexual events in the recall period, 80% of which were unprotected, providing evidence that a few individuals might account for a disproportionately large number of potential transmission events. Chin-Hong et al.  evaluated 279 patients in San Francisco, noting that 17% of MSM and 6% of heterosexual men and women with resistant viruses had unprotected sex with serodiscordant or status-unknown partners in the prior 4 months. Finally, at 14% of encounters with members of a Baltimore IDU cohort, participants with significant antiretroviral resistance described unprotected sex and/or needle-sharing during periods of incomplete virological suppression on antiretrovirals .
Clearly, not every patient who develops resistance has unprotected sex. However, the strength of this association – observed across multiple, diverse clinical cohorts – suggests that nonadherence and the accumulation of resistance could serve as a marker of coincident sexual risk behaviour. As many HIV providers check HIV RNA more often than they update a patient's sexual history , any detectable viraemia should prompt a discussion with the patient about not only adherence but also transmission risk behaviour. Targeted interventions to reduce sexual partner number and improve condom utilization among patients with new or documented resistance could be important first steps towards reducing the spread of TDR. Finally, the role of substance abuse as a factor in both nonadherence and transmission risk cannot be underestimated; appropriate treatment for addiction is essential for preventing resistance and reducing high-risk sexual behaviours.
Our study is not without limitations. Only 250 of 482 participants completing face-to-face interviews had ever undergone resistance testing (52%). We felt the likelihood was low that undocumented mutations were present among the 232 who never had a GRT, as our institutional practice has long been to check for resistance in the setting of treatment failure. Social desirability bias during the face-to-face interview may have led participants to underestimate the number of sexual partners or overestimate adherence, but we explored this with our bounded sensitivity analysis and found similar factors associated with our primary outcome. Finally, our composite primary outcome reflects the factors necessary for transmission of resistant HIV to occur; it is impossible to know what viruses were circulating in the blood or genital tract at exactly the time of potential transmission events.
In summary, we found a small but significant proportion of clinic patients with viraemia and documented resistant HIV continue to engage in sexual behaviours that place others at a risk for TDR. Clinic-based, targeted secondary prevention and adherence interventions could substantially reduce opportunities for forward transmission of resistant HIV in the future.
This study was originally presented by H.M.S. at the XIX International AIDS Conference, 22–27 July 2012, Washington, DC, USA (Poster MOPE169). The authors thank Elizabeth Yanik, Sam Stinnette, Brant Stalzer and Luca Vernazza for their assistance.
H.M.S. extracted data, conducted all statistical analyses, produced the tables and cowrote and revised the manuscript; S.N. provided statistical advice and helped revise the manuscript; O.M.Z. supervised data collection for the clinical cohort, assisted with data extraction and helped revise the manuscript; J.J.E. assisted in the design of the study and helped revise the manuscript; and C.B.H. designed and supervised the study, performed literature searches, produced the figures and cowrote and revised the manuscript.
This work was supported by the Social and Behavioral Science Research Core of the University of North Carolina Center for AIDS Research, the Agency for Healthcare Research and Quality (5R01HS018731 to S.N.) and the National Institute of Allergy and Infectious Diseases and the National Center for Advancing Translational Sciences at National Institutes of Health (2T32AI070114 to H.M.S., 2P30AI50410 to J.J.E, 8KL2TR000084 to C.B.H.).
Conflicts of interest
The authors have no conflicts of interest to report.
1. Prejean J, Song R, Hernandez A, Ziebell R, Green T, Walker F, et al. Estimated HIV Incidence in the United States, 2006–2009
. PLoS One
2. Wheeler WH, Ziebell RA, Zabina H, Pieniazek D, Prejean J, Bodnar UR, et al. Prevalence of transmitted drug resistance associated mutations and HIV-1 subtypes in new HIV-1 diagnoses, U.S.-2006
3. Bangsberg DR, Moss AR, Deeks SG. Paradoxes of adherence and drug resistance to HIV antiretroviral therapy
. J Antimicrob Chemother
4. Bangsberg DR, Kroetz DL, Deeks SG. Adherence-resistance relationships to combination HIV antiretroviral therapy
. Curr HIV/AIDS Rep
5. Bangsberg DR. Preventing HIV antiretroviral resistance through better monitoring of treatment adherence
. J Infect Dis
2008; 197 (Suppl 3):S272–S278.
6. Tam LW, Chui CK, Brumme CJ, Bangsberg DR, Montaner JS, Hogg RS, et al. The relationship between resistance and adherence in drug-naive individuals initiating HAART is specific to individual drug classes
. J Acquir Immune Defic Syndr
7. Brenner BG, Roger M, Moisi DD, Oliveira M, Hardy I, Turgel R, et al. Transmission networks of drug resistance acquired in primary/early stage HIV infection
8. Hecht FM, Grant RM, Petropoulos CJ, Dillon B, Chesney MA, Tian H, et al. Sexual transmission of an HIV-1 variant resistant to multiple reverse-transcriptase and protease inhibitors
. N Engl J Med
9. Boden D, Hurley A, Zhang L, Cao Y, Guo Y, Jones E, et al. HIV-1 drug resistance in newly infected individuals
10. Salomon H, Wainberg MA, Brenner B, Quan Y, Rouleau D, Cote P, et al. Prevalence of HIV-1 resistant to antiretroviral drugs in 81 individuals newly infected by sexual contact or injecting drug use. Investigators of the Quebec Primary Infection Study
11. Grant RM, Hecht FM, Warmerdam M, Liu L, Liegler T, Petropoulos CJ, et al. Time trends in primary HIV-1 drug resistance among recently infected persons
12. Little SJ, Holte S, Routy JP, Daar ES, Markowitz M, Collier AC, et al. Antiretroviral-drug resistance among patients recently infected with HIV
. N Engl J Med
13. Weinstock HS, Zaidi I, Heneine W, Bennett D, Garcia-Lerma JG, Douglas JM Jr, et al. The epidemiology of antiretroviral drug resistance among drug-naive HIV-1-infected persons in 10 US cities
. J Infect Dis
14. Ross L, Lim ML, Liao Q, Wine B, Rodriguez AE, Weinberg W, et al. Prevalence of antiretroviral drug resistance and resistance-associated mutations in antiretroviral therapy-naive HIV-infected individuals from 40 United States cities
. HIV Clin Trials
15. Hurt CB, McCoy SI, Kuruc J, Nelson JA, Kerkau M, Fiscus S, et al. Transmitted antiretroviral drug resistance among acute and recent HIV infections in North Carolina from 1998 to 2007
. Antivir Ther
16. Cane P, Chrystie I, Dunn D, Evans B, Geretti AM, Green H, et al. Time trends in primary resistance to HIV drugs in the United Kingdom: multicentre observational study
17. Masquelier B, Bhaskaran K, Pillay D, Gifford R, Balestre E, Jorgensen LB, et al. Prevalence of transmitted HIV-1 drug resistance and the role of resistance algorithms: data from seroconverters in the CASCADE collaboration from 1987 to 2003
. J Acquir Immune Defic Syndr
18. Wensing AM, van de Vijver DA, Angarano G, Asjo B, Balotta C, Boeri E, et al. Prevalence of drug-resistant HIV-1 variants in untreated individuals in Europe: implications for clinical management
. J Infect Dis
19. Vercauteren J, Wensing AM, van de Vijver DA, Albert J, Balotta C, Hamouda O, et al. Transmission of drug-resistant HIV-1 is stabilizing in Europe
. J Infect Dis
20. Leigh Brown AJ, Frost SD, Mathews WC, Dawson K, Hellmann NS, Daar ES, et al. Transmission fitness of drug-resistant human immunodeficiency virus and the prevalence of resistance in the antiretroviral-treated population
. J Infect Dis
21. Brown AE, Gifford RJ, Clewley JP, Kucherer C, Masquelier B, Porter K, et al. Phylogenetic reconstruction of transmission events from individuals with acute HIV infection: toward more-rigorous epidemiological definitions
. J Infect Dis
22. Marks G, Burris S, Peterman TA. Reducing sexual transmission of HIV from those who know they are infected: the need for personal and collective responsibility
23. Kline A, VanLandingham M. HIV-infected women and sexual risk reduction: the relevance of existing models of behavior change
. AIDS Educ Prev
24. Wenger NS, Kusseling FS, Beck K, Shapiro MF. Sexual behavior of individuals infected with the human immunodeficiency virus. The need for intervention
. Arch Intern Med
25. van Kesteren NM, Hospers HJ, Kok G. Sexual risk behavior among HIV-positive men who have sex with men: a literature review
. Patient Educ Couns
26. van der Straten A, Gomez CA, Saul J, Quan J, Padian N. Sexual risk behaviors among heterosexual HIV serodiscordant couples in the era of postexposure prevention and viral suppressive therapy
27. Fox J, White PJ, Macdonald N, Weber J, McClure M, Fidler S, et al. Reductions in HIV transmission risk behaviour following diagnosis of primary HIV infection: a cohort of high-risk men who have sex with men
. HIV Med
28. de Wit JB, van Griensven GJ. Time from safer to unsafe sexual behaviour among homosexual men
29. Adib SM, Joseph JG, Ostrow DG, Tal M, Schwartz SA. Relapse in sexual behavior among homosexual men: a 2-year follow-up from the Chicago MACS/CCS
30. Flaks RC, Burman WJ, Gourley PJ, Rietmeijer CA, Cohn DL. HIV transmission risk behavior and its relation to antiretroviral treatment adherence
. Sex Transm Dis
31. Kalichman SC, Rompa D. HIV treatment adherence and unprotected sex practices in people receiving antiretroviral therapy
. Sex Transm Infect
32. Kozal MJ, Amico KR, Chiarella J, Schreibman T, Cornman D, Fisher W, et al. Antiretroviral resistance and high-risk transmission behavior among HIV-positive patients in clinical care
33. Chin-Hong PV, Deeks SG, Liegler T, Hagos E, Krone MR, Grant RM, et al. High-risk sexual behavior in adults with genotypically proven antiretroviral-resistant HIV infection
. J Acquir Immune Defic Syndr
34. Remien RH, Exner TM, Morin SF, Ehrhardt AA, Johnson MO, Correale J, et al. Medication adherence and sexual risk behavior among HIV-infected adults: implications for transmission of resistant virus
. AIDS Behav
35. Howe CJ, Cole SR, Napravnik S, Eron JJ. Enrollment, retention, and visit attendance in the University of North Carolina Center for AIDS Research HIV clinical cohort, 2001-2007
. AIDS Res Hum Retroviruses
36. Chesney MA, Ickovics JR, Chambers DB, Gifford AL, Neidig J, Zwickl B, et al. Self-reported adherence to antiretroviral medications among participants in HIV clinical trials: the AACTG adherence instruments. Patient Care Committee & Adherence Working Group of the Outcomes Committee of the Adult AIDS Clinical Trials Group (AACTG)
. AIDS Care
37. WHO ASSIST Working GroupThe Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility
38. Babor TF, Higgins-Biddle JC, Saunders JB, Monteriro MG. AUDIT: The Alcohol Use Disorders Identification Test: guidelines for use in primary care
. 2nd ed.Geneva, Switzerland:WHO; 2001.
39. Bennett DE, Camacho RJ, Otelea D, Kuritzkes DR, Fleury H, Kiuchi M, et al. Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update
. PLoS One
40. Shafer RW, Rhee SY, Pillay D, Miller V, Sandstrom P, Schapiro JM, et al. HIV-1 protease and reverse transcriptase mutations for drug resistance surveillance
41. Panel on Antiretroviral Guidelines for Adults and AdolescentsGuidelines for the use of antiretroviral agents in HIV-1 infected adults and adolescents
. 2012; Washington, DC:US Department of Health and Human Services, 1–239.
42. Gardner EM, McLees MP, Steiner JF, Del Rio C, Burman WJ. The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection
. Clin Infect Dis
43. Kidder DP, Wolitski RJ, Campsmith ML, Nakamura GV. Health status, healthcare use, medication use, and medication adherence among homeless and housed people living with HIV/AIDS
. Am J Public Health
44. Wilson TE, Barrón Y, Cohen M, Richardson J, Greenblatt R, Sacks HS, et al. Adherence to antiretroviral therapy and its association with sexual behavior in a national sample of women with human immunodeficiency virus
. Clin Infect Dis
45. Sethi AK, Celentano DD, Gange SJ, Gallant JE, Vlahov D, Farzadegan H. High-risk behavior and potential transmission of drug-resistant HIV among injection drug users
. J Acquir Immune Defic Syndr
46. CDCIncorporating HIV prevention into the medical care of persons living with HIV: recommendations of CDC, the Heatlh Resources and Services Administration, the National Institutes of Health, and the HIV Medicine Association of the Infectious Diseases Society of America
. MMWR Recomm Rep