JAIDS Journal of Acquired Immune Deficiency Syndromes:
Epidemiology and Prevention
Disparities in Engagement in Care and Viral Suppression Among Persons With HIV
Muthulingam, Dharushana MD, MS*; Chin, Jennie MBA†; Hsu, Ling MPH†; Scheer, Susan PhD, MPH†; Schwarcz, Sandra MD, MPH*,†
*University of California, San Francisco, CA; and
†San Francisco Department of Public Health, San Francisco, CA.
Correspondence to: Susan Scheer, PhD, MPH, San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102 (e-mail: firstname.lastname@example.org).
Supported by Centers for Disease Control and Prevention, Grant # 3U62PS001000-05, core surveillance cooperative agreement.
The authors have no conflicts of interest to disclose.
Received October 12, 2012
Accepted January 18, 2013
Background: Engagement across the spectrum of HIV care can improve health outcomes and prevent HIV transmission. We used HIV surveillance data to examine these outcomes.
Methods: San Francisco residents who were diagnosed with HIV between 2009 and 2010 were included. We measured the characteristics and proportion of persons linked to care within 6 months of diagnosis, retained in care for second and third visits, and virally suppressed within 12 months of diagnosis.
Results: Of 862 persons included, 750 (87%) entered care within 6 months of diagnosis; of these, 72% had a second visit in the following 3–6 months; and of these, 80% had a third visit in the following 3–6 months. Viral suppression was achieved in 50% of the total population and in 76% of those retained for 3 visits. Lack of health insurance and unknown housing status were associated with not entering care (P < 0.01). Persons with unknown insurance status were less likely to be retained for a second visit; those younger than 30 years were less likely to be retained for a third visit. Independent predictors of failed viral suppression included age <40 years, homelessness, unknown housing status, and having a single or 2 medical visits compared with 3 visits.
Conclusions: Socioeconomic resources and age, not race or gender, are associated with disparities in engagement in HIV care in San Francisco.
Current treatment for HIV infection is highly effective in reducing circulating virus, thereby restoring and maintaining health1–6 and reducing HIV transmission.7–10 As such, efforts for the timely diagnosis of HIV, linkage to and retention in care, treatment, and monitoring to ensure viral suppression have become priorities for public health officials at the local, state, and federal levels.11 Unfortunately, at each step along this continuum, from diagnosis to viral suppression, there is steady loss of persons to the point that only an estimated 19%–35% of HIV-infected persons achieve successful viral suppression.12,13
In the United States, HIV disproportionately affects persons of color, sexual minorities, injection drug users (IDUs), and lower income populations. Men who have sex with men (MSM), particularly African American MSM, are overrepresented in new diagnosis of HIV.14–16 Among persons living with HIV/AIDS, 48% are black, 27% are women, 64% are MSM, and 17% are Latino.15 From 2005 to 2008, half of new diagnoses occurred among African Americans, a trend driven in part by an increase among younger African Americans MSM.17 Among women, this racial disparity is more pronounced; in 2008, HIV diagnosis among African American women was 19 times greater than among white women and 4 times greater than among Hispanic women.14 Neither differences in individual risk behaviors nor testing patterns fully account for these disparities.18–20
Delays in diagnosis have been reported among people of color, heterosexuals, those with unknown risk, those without insurance, and among persons born outside of the United States.21–28 Once diagnosed, disparities exist in linkage to medical care, with decreased access among immigrants, younger persons, blacks, the uninsured, and those testing at publicly funded counseling and testing centers.28–30 Once linked to care, antiretroviral therapy (ART) is prescribed less frequently to younger persons, women, blacks and Latinos, and the uninsured.13,31,32 Among persons who enter care, retention in care is found to be lower among African Americans, Latinos, heterosexual men, IDUs, the unstably housed, persons with unmet social needs, and adolescents.33–37 Interruptions in therapy and failed viral suppression occur more frequently among women, Latinos, African Americans, younger age groups, those with substance use, and unstable housing.38–40
Reducing these disparities is 1 of 3 central goals in the national HIV/AIDS strategy for the United States. Characterizing the disparities in each step along the continuum from diagnosis to engagement in care can lead to effective interventions that target groups at greatest need. Although the federal government provides leadership and financial support for such actions, ultimately it falls to local health departments to measure their success in identifying, linking, retaining, effectively treating HIV-infected persons, and ensuring that disparities in these outcomes are overcome.
We used HIV surveillance data to measure sociodemographic and risk disparities in timely linkage to care, retention in care, and viral suppression among persons with HIV in San Francisco, a city with widely available low-cost or free HIV testing and care, including antiretroviral and prophylactic medications. The benefit of using surveillance data is that it is population based, systematically and routinely collected, and evaluated annually.
San Francisco HIV/AIDS Surveillance Activities
Surveillance methods for HIV/AIDS in San Francisco have been described in detail elsewhere.29,41 Briefly, all persons who are residents of San Francisco at the time of HIV/AIDS diagnosis are required by law to be reported to San Francisco Department of Public Health. California initiated mandatory reporting of (1) all HIV-positive antibody and viral load tests in 2002 and (2) all CD4 test results in 2008.42 Data collected at the time of HIV diagnosis include demographic and risk factor information, diagnosing facility, insurance status at diagnosis, country of birth, housing status (housed or homeless),43 date of first positive HIV antibody test, and all CD4 and viral load test results. We define an individual as residing in an impoverished neighborhood at diagnosis if they lived in a census tract where more than 20% of person aged 18 years or older had a median annual household income that was below the United States poverty level.44,45 The San Francisco Department of Public Health evaluates the completeness of case reporting annually and has found the completeness of reporting to be consistently above 90%.46–48
There were 862 San Francisco residents ≥13 years old diagnosed with HIV and/or AIDS between January 1, 2009, and December 31, 2010, and reported to the San Francisco Department of Public Health through March 6, 2012. The date of HIV diagnosis was defined as the earliest of any of the following: the first confirmed positive HIV antibody test; HIV viral load or CD4 test after the last known negative test; physician diagnosis of HIV/AIDS; or self-report that occurred in 2009–2010. Cases for whom only a year of diagnosis was available were excluded because we could not calculate the number of months between diagnosis and entry into care (n = 2). We excluded 3 cases that were diagnosed at death and 9 cases that were known to have moved out of San Francisco within 12 months of HIV diagnosis, the time period included in the study outcome.
Initiation of and Retention in Care
We measured initiation of and retention in care over a minimum of 12 months using CD4 and viral load tests as indicators of persons receiving care. We used the date of the first CD4 or viral load test, whichever was earlier, as the month of entry into care. The Centers for Disease Control and Prevention (CDC) recommends that persons enter medical care within 3 months of diagnosis.49 We applied a less restricted time frame for timely entry into care because we relied only on laboratory test results to indicate receipt of care. As such, we measured the proportion of persons who entered care within 6 months, within 7–12 months, more than a year after diagnosis, or for whom no evidence of entry into care was found after diagnosis. We measured 2 outcomes for retention in care. First, among persons who entered care within 6 months of diagnosis, we measured the proportion of persons who had a second laboratory test within 3–6 months after entry into care. Second, among persons who had a second laboratory test within 3–6 months after entry into care, we measured the proportion who had a third laboratory test within 3–6 months after the second test. We selected our timeframes for retention in care based upon recommended care guidelines and because lapses in care, particularly within the first year of care, are associated with adverse health outcomes.2,50 For each of these outcomes, we compared differences in the sociodemographic and risk characteristics.
We used the CDC definition of viral suppression (<200 copies/mL).51 Viral suppression is usually achieved in 12–24 weeks for a patient adherent to ART without viral resistance, with some patients taking longer. We measured viral suppression within 12 months of diagnosis to allow for persons who failed initial therapy to switch to an alternative regimen and to compare our findings to similar analyses that used surveillance data.13 We calculated the proportion of the total population and the proportion of persons who were retained in care for up to 3 visits who achieved viral suppression and compared the characteristics of persons who achieved viral suppression to those who did not. We also measured the independent predictors of not achieving viral suppression within 12 months of diagnosis.
The χ2 test was used to measure the association between categorical outcome measures and sociodemographic and risk characteristics, and the Wilcoxon rank sum test was used to compare differences in medians. We used stepwise multivariable logistic regression to identify the independent predictors of not achieving viral suppression among persons who were in care some time during the 12 months following diagnosis. The sociodemographic and risk variables, frequency of care visits, and the log of the first viral load value within 12 months of diagnosis were included in the model and retained at the significance level of P < 0.05. Persons for whom viral load test results were missing were excluded in the model (n = 15). All analyses were conducted using SAS version 9.1 (SAS Institute. Inc., Cary, NC).
There were 862 San Francisco residents ≥13 years old diagnosed with HIV and/or AIDS between January 1, 2009, and December 31, 2010. A total of 750 (87%) persons entered care within the 6 months of diagnosis, 28 (3%) entered care within 7–12 months after diagnosis, and the remaining 84 (10%) had their first visit either more than 12 months after diagnosis or did not have evidence of entering care in San Francisco. The median first CD4 count (cells/mm3) of persons linked to care was 423 compared with 419 among persons who entered care later or who did not initiate care during the observation period (P = 0.44). Of those who were linked to care within 6 months of diagnosis, 540 (72%) had at least 1 additional follow-up laboratory test within 3–6 months after the first visit; and among those with this second visit, 434 (80%) had a third visit within 3–6 months after the second visit (Table 1 and Fig. 1).
Linkage to care within 6 months of diagnosis was significantly less frequent among MSM who also inject drugs and persons for whom HIV risk was not known (84% and 69%, respectively, P < 0.01), persons without health insurance or whose insurance status was unknown (86% and 70%, respectively, P < 0.01), and persons whose housing status at diagnosis was unknown (70%, P < 0.01). Retention in care for a second visit was less frequent among persons whose insurance status was not known (60%, P < 0.05). Among persons who were retained in care for a third visit 3–6 months after the second visit, a significantly lower proportion were under 30 years old and a significantly higher proportion were aged 50 years and older (72% and 90%, respectively, P = 0.02).
Of the total study population, 431 (50%) achieved viral suppression within 12 months of diagnosis (Table 2 and Fig. 1). Viral suppression was significantly lower among persons who were younger, MSM who also inject drugs, whose risk group was not reported, who were uninsured or whose insurance status was unknown, who lived in an impoverished neighborhood or whose residence was not known at diagnosis, and who were homeless or whose housing status was not known. Seventy-six percent of persons who were retained in care for at least a third clinic visit achieved viral suppression. Although the percentages of persons achieving viral suppression among those who were retained in care for up to 3 visits were higher than among the total study population, the distribution within subgroups was similar.
In our multivariate analysis, we identified several factors that were associated with an increased risk of not achieving viral suppression within 12 months of diagnosis. The factors were age younger than 40 years at diagnosis compared with persons aged 40 or older [odds ratio (OR): 1.92, 95% confidence interval (CI): 1.4 to 2.7], being homeless (OR: 2.13, 95% CI: 1.3 to 3.5), or having an unknown housing status (OR: 2.67, 95% CI: 1.4 to 5.0) compared with persons who were housed at diagnosis and having only a single medical visit (OR: 11.50, 95% CI: 7.8-17.1) or just 2 visits (OR: 3.21, 95% CI: 2.0 to 5.1) compared with 3 visits within 12 months after diagnosis.
In San Francisco, a city with widely available HIV testing, access to care, and ART at low or no cost, we found that close to 90% of newly diagnosed cases were linked to care within 6 months. Short-term retention in care was not as high; only 72% of persons had a second viral load or CD4 test in the following 3–6 months. But of those with a second test, 80% showed evidence of continued care for at least the next 3–6 months. Unfortunately, because half of the population of newly diagnosed individuals dropped out along the continuum of care, only 50% of the total population achieved viral suppression within 12 months of diagnosis. As expected, among those who remained in care for up to 12 months (i.e., retained in care for a third visit), the proportion virally suppressed was higher than in the total population.
Along this continuum of care, 2 markers of social marginalization and decreased resources—health insurance and housing status—emerged as factors associated with poor utilization of care and not achieving viral suppression. Homelessness has been consistently shown to correlate with poorer health outcomes compared with those who are stably housed.43,52–54 Unstable housing is associated with delayed care and fewer ambulatory visits in persons living with HIV.55–58 This may be from competing priorities such as food security, barriers to managing complex health conditions (such as lack of transportation and storage), and higher burden of comorbidities, including mental illness and substance use.55,59,60 When stable housing is provided as an intervention, HIV outcomes improve.35,52,61,62
Similarly, lower socioeconomic status has long been established as associated with poorer health outcomes, independent of race/ethnicity and insurance, in a variety of chronic illnesses.63–66 In the era of highly effective ART, higher socioeconomic status predicts better care utilization67 and survival.68,69 Finally, our finding that lack of insurance is associated with decreased utilization of outpatient care is also consistent with other studies,56,67,70–72 potentially accounting for increased HIV mortality among the uninsured.73 But in contrast to other studies of care utilization,33,56,67,70,71,74–76 we did not identify gender or race/ethnic differences in entry and retention in care, although the comparison may be limited given the variation in outcomes measured, populations studied, and the interaction among these variables.
The CDC recently published estimates of indicators of engagement in care using several sources of national surveillance data in which they estimate that in 2010, 77% of diagnosed persons were linked to care within 4 months of diagnosis and 51% of diagnosed persons were retained in care.13 Although our definition of timely linkage to care was more generous and our definition of ongoing engagement in care was more restrictive than those used in the national estimates, our results compare favorably to these. Though not included in our analysis, previous studies of HIV risk populations in San Francisco have found, for example, that less than 6% of infected MSM were unaware of their infection; a proportion markedly lower than the national estimates of 20%.13,77
We estimated viral suppression within 12 months of diagnosis among the total population and among persons who had a third visit within 3–6 months after the second visit. Among the persons who remained in care, our finding that 76% were virally suppressed was similar to the national estimate of 77%.13 However, among the diagnosed population, the proportion that was virally suppressed in San Francisco was substantially greater than the proportion reported nationally by CDC (50% versus 35%, respectively) although the estimates of the proportion of persons receiving ART nationwide (89%)13 was similar to what we have reported from San Francisco (83%–89%).77 This may reflect our restriction of the analysis to newly diagnosed cases in San Francisco rather than all living cases, including infected but undiagnosed persons; a separate analysis using the CDC methodology in which we used total population of living HIV cases found that 44% of the HIV-infected population in San Francisco was virally suppressed.78 The differences in the proportions of the infected population that are virally suppressed in San Francisco compared with national data may reflect the much lower proportion of undiagnosed infection among San Francisco risk populations.
Several limitations of this analysis should be considered. We defined linkage to care as an HIV-specific laboratory test within 6 months of diagnosis and retention in care as subsequent tests in the following 3–6 months. Time frames are a bit longer than recommended by the Department of Health and Human Services for CD4 and viral load testing every 3–4 four months.2 We did this to capture persons who may delay obtaining laboratory tests after a clinic visit. Relying exclusively on laboratory tests to indicate medical care can miss persons who received other types of care such as mental health and social support services. A CD4 or viral load test within 6 months of diagnosis may misclassify persons whose tests were conducted at the time of diagnosis and may not represent entry into care. This is unlikely to present a substantial misclassification bias in our study because there were only 13 cases whose CD4 or viral load tests occurred on the same day as their HIV antibody test who also did not have any subsequent tests during the observation period.
Although viral suppression is often defined as an undetectable viral load (<20–74 copies/mL, depending on the assay), some successfully treated individuals can have isolated and transient detectable low levels (usually <400 copies/mL). We defined viral suppression as a viral load of <200 copies per milliliter, consistent with the CDC, AIDS Clinical Trials Group, and Department of Health and Human Services,2,51 because some individuals experience transient elevations in viral load and variation in assays can produce detectable but low levels of virus and neither of these appear to be associated with virological failure.79–82
Our findings come from routine surveillance of HIV and as such cannot distinguish persons who moved from San Francisco from those who are not receiving care because current surveillance methods do not permit following individuals who no longer reside in San Francisco. In addition, HIV-infected San Francisco residents are reported to the San Francisco Department of Public Health but may receive some or all of their care outside of San Francisco. If so, we may have underestimated care use and viral suppression. Updates to the national HIV reporting data management system have been designed to assist in identifying persons who reside in or move to other jurisdictions and should improve estimates of care utilization through monitoring of laboratory data. Our markers of poverty, homelessness, and health insurance only pertain to the time of diagnosis, are imprecise, and do not include other key social determinants of health such as education,37,64,68,83,84 incarceration history,57,85,86 or level of social support.70,87,88 The HIV-infected population in San Francisco differs from that of many other jurisdictions where HIV infection occurs in greater frequency among women, African Americans, Latinos, IDUs, and residents of impoverished neighborhoods and as such our findings may not be representative of other communities.89
Despite these limitations, these findings provide a baseline upon which we can monitor the extent to which our population engages in care and achieves viral suppression. To reach the ultimate goal of eliminating HIV transmission through community-wide viral suppression in San Francisco, enhancing efforts toward early diagnosis, entry, and retention in care, universal provision of ART and adherence support are essential. Our article also highlights the need to prioritize the social and life style determinants of health. Although the ongoing standardized methods of HIV surveillance provide consistent data with which to monitor diagnosis and care indicators, they cannot provide a complete picture of care utilization. For this reason, we support the recommendations outlined in the Institute of Medicine report on monitoring HIV care in the United States to use multiple data sources to evaluate successes, failures, and associated factors associated with HIV diagnosis and care.90
1. Mocroft A, Vella S, Benfield T, et al.. Changing patterns of mortality across Europe in patients infected with HIV-1. Lancet. 1998;352:1725–1730.
3. Palella FJ, Delaney KM, Moorman AC, et al.. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators. N Engl J Med. 1998;338:853–860.
4. Vittinghoff E, Scheer S, O’Malley P, et al.. Combination antiretroviral therapy and recent declines in AIDS incidence and mortality. J Infect Dis. 1999;179:717–720.
5. The Antiretroviral Therapy Cohort Collaboration. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008;372:293–299.
6. García F, De Lazzari E, Plana M, et al.. Long-term CD4+ T-cell response to highly active antiretroviral therapy according to baseline CD4+ T-cell count. J Acquir Immune Defic Syndr. 2004;36:702–713.
7. Wood E, Kerr T, Marshall BDL, et al.. Longitudinal community plasma HIV-1 RNA concentrations and incidence of HIV-1 among injecting drug users: prospective cohort study. BMJ. 2009;338:b1649.
8. Quinn TC, Wawer MJ, Sewankambo N, et al.. Viral load and heterosexual transmission of human immunodeficiency virus type 1. Rakai Project Study Group. N Engl J Med. 2000;342:921–929.
9. Dieffenbach CW, Fauci AS. Universal voluntary testing and treatment for prevention of HIV transmission. JAMA. 2009;301:2380–2382.
10. Montaner JSG, Hogg R, Wood E, et al.. The case for expanding access to highly active antiretroviral therapy to curb the growth of the HIV epidemic. Lancet. 2006;368:531–536.
12. Gardner EM, McLees MP, Steiner JF, et al.. The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection. Clin Infect Dis. 2011;52:793–800.
13. Cohen SM, Van Handel MM, Branson BM, et al.. Vital Signs: HIV Prevention Through Care and Treatment- United States. MMWR Morb Mortal Wkly Rep. 2011;60:1618–1622.
14. Laffoon B, Johnson AS, Cohen S, et al.. National black HIV/AIDS awareness disparities in diagnoses of HIV infection between blacks/African Americans and other racial/eEthnic populations—37 States, 2005–2008. MMWR Morb Mortal Wkly Rep. 2011;60:1999–2002.
16. Centers for Disease Control and Prevention. HIV/AIDS Surveillance Report, 2006. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2008:1–11.
17. Prejean J, Song R, Hernandez A, et al.. Estimated HIV Incidence in the United States, 2006–2009. PLoS ONE. 2011;6:e17502.
18. Harawa NT, Greenland S, Bingham TA, et al.. Associations of race/ethnicity with HIV prevalence and HIV-related behaviors among young men who have sex with men in 7 urban centers in the United States. J Acquir Immune Defic Syndr. 2004;35:526–536.
19. Christopoulos KA, Das M, Colfax GN. Linkage and retention in HIV care among men who have sex with men in the United States. Clin Infect Dis. 2011;52(suppl 2):S214–S222.
20. Millett GA, Flores SA, Peterson JL, et al.. Explaining disparities in HIV infection among black and white men who have sex with men: a meta-analysis of HIV risk behaviors. AIDS. 2007;21:2083–2091.
21. Nakashima A, Campsmith M, Wolfe M, et al.. Late versus early testing of HIV–16 Sites, United States, 2000–2003. MMWR Morb Mortal Wkly Rep. 2003;52:581–586.
22. Chen NE, Gallant JE, Page KR. A systematic review of HIV/AIDS survival and delayed diagnosis among Hispanics in the United States. J Immigr Minor Health. 2012;14:65–81.
23. Dennis AM, Napravnik S, Seña AC, et al.. Late entry to HIV care among Latinos compared with non-Latinos in a southeastern US cohort. Clin Infect Dis. 2011;53:480–487.
24. Saganic L, Carr J, Solorio R, et al.. Comparing measures of late HIV diagnosis in Washington State. AIDS Res Treat. 2012;2012:182672.
25. Schwarcz S, Hsu L, Dilley JW, et al.. Late diagnosis of HIV infection: trends, prevalence, and characteristics of persons whose HIV diagnosis occurred within 12 months of developing AIDS. J Acquir Immune Defic Syndr. 2006;43:491–494.
26. Schwarcz SK, Hsu L, Chin C-SJ, et al.. Do people who develop AIDS within 12 months of HIV diagnosis delay HIV testing? Public Health Rep. 2011;126:552–559.
27. Tang JJ, Levy V, Hernandez MT. Who are California’s late HIV testers? An analysis of state AIDS surveillance data, 2000–2006. Public Health Rep. 2011;126:338–343.
28. Milberg J, Sharma R, Scott F, et al.. Factors associated with delays in accessing HIV primary care in rural Arkansas. AIDS Patient Care STDS. 2001;15:527–532.
29. Hsu LC, Chen M, Kali J, et al.. Assessing receipt of medical care and disparity among persons with HIV/AIDS in San Francisco, 2006–2007. AIDS Care. 2011;23:383–392.
30. Tripathi A, Gardner LI, Ogbuanu I, et al.. Predictors of time to enter medical care after a new HIV diagnosis: a statewide population-based study. AIDS Care. 2011;23:1366–1373.
31. Gebo KA, Fleishman JA, Conviser R, et al.. Racial and gender disparities in receipt of highly active antiretroviral therapy persist in a multistate sample of HIV patients in 2001. J Acquir Immune Defic Syndr. 2005;38:96–103.
32. Wood E, Montaner JSG, Bangsberg DR, et al.. Expanding access to HIV antiretroviral therapy among marginalized populations in the developed world. AIDS. 2003;17:2419–2427.
33. Hall HI, Gray KM, Tang T, et al.. Retention in care of adults and adolescents living with HIV in 13 U.S. areas. J Acquir Immune Defic Syndr. 2012;60:77–82.
34. Tobias CR, Cunningham W, Cabral HD, et al.. Living with HIV but without medical care: barriers to engagement. AIDS Patient Care STDS. 2007;21:426–434.
35. Wolitski RJ, Kidder DP, Pals SL, et al.. Randomized trial of the effects of housing assistance on the health and risk behaviors of homeless and unstably housed people living with HIV. AIDS Behav. 2010;14:493–503.
36. Ryscavage P, Anderson E, Sutton S. Clinical outcomes of adolescents and young adults in adult HIV care. J Acquir Immune Defic Syndr. 2011;58:193–197.
37. Sohler NL, Li X, Cunningham CO. Gender disparities in HIV health care utilization among the severely disadvantaged: can we determine the reasons? AIDS Patient Care STDS. 2009;23:775–783.
38. Oh DL, Sarafian F, Silvestre A, et al.. Evaluation of adherence and factors affecting adherence to combination antiretroviral therapy among White, Hispanic, and Black men in the MACS Cohort. J Acquir Immune Defic Syndr. 2009;52:290–293.
39. Sullivan PS, Campsmith ML, Nakamura G V, et al.. Patient and regimen characteristics associated with self-reported nonadherence to antiretroviral therapy. PLoS ONE. 2007;2:e552.
40. Schackman BR, Ribaudo HJ, Krambrink A, et al.. Racial differences in virologic failure associated with adherence and quality of life on efavirenz-containing regimens for initial HIV therapy: results of ACTG A5095. J Acquir Immune Defic Syndr. 2007;46:547–554.
41. Zetola NM, Bernstein K, Ahrens K, et al.. Using surveillance data to monitor entry into care of newly diagnosed HIV-infected persons: San Francisco, 2006–2007. BMC Public Health. 2009;9:17.
43. Schwarcz SK, Hsu LC, Vittinghoff E, et al.. Impact of housing on the survival of persons with AIDS. BMC Public Health. 2009;9:1–18.
44. U.S. Census Bureau. 2006–2010 American Community Survey. 2010.
45. Schneider E, Whitmore S, Glynn MK, et al.. Revised surveillance case definitions for HIV infection among adults, adolescents, and children aged < 18 months and for HIV infection and AIDS among children aged 18 months to < 13 Years—United States, 2008. MMWR Recomm Rep. 2008;57:1–12.
46. Chu PL, Hsu LC, Schwarcz SK. Comparison of methods to measure the completeness of HIV/AIDS reporting in San Francisco. Presented at: Oral Abstract Session: AIDS 2008–XVII International AIDS Conference; Mexico City, Mexico: August 3-8, 2008.
47. Schwarcz SK, Hsu LC, Parisi MK, et al.. The impact of the 1993 AIDS case definition on the completeness and timeliness of AIDS surveillance. AIDS. 1999;13:1109–1114.
48. San Francisco Department of Public Health. HIV/AIDS Epidemiology Annual Report. San Francisco, CA:San Francisco Department of Public Health; 2008.
50. Mugavero MJ, Lin H-Y, Willig JH, et al.. Missed visits and mortality among patients establishing initial outpatient HIV treatment. Clinical Infectious Diseases. 2009;48(2):248–56.
52. Leaver CA, Bargh G, Dunn JR, et al.. The effects of housing status on health-related outcomes in people living with HIV: a systematic review of the literature. AIDS Behav. 2007;11:85–100.
53. Aidala AA, Sumartojo E. Why Housing? AIDS Behav. 2007;11:1–6.
54. Furlotte C, Schwartz K, Koornstra JJ, et al.. “Got a room for me?” Housing experiences of older adults living with HIV/AIDS in Ottawa. Can J Aging. 2012;31:37–48.
55. Henry R, Richardson JL, Stoyanoff S, et al.. HIV/AIDS health service utilization by people who have been homeless. AIDS Behav. 2008;12:815–821.
56. Cunningham CO, Sohler NL, Wong MD, et al.. Utilization of health care services in hard-to-reach marginalized HIV-infected individuals. AIDS Patient Care STDS. 2007;21:177–186.
57. Chen NE, Meyer JP, Avery AK, et al.. Adherence to HIV treatment and care among previously homeless jail detainees. AIDS Behav. 2011.
58. Smith MY, Rapkin BD, Winkel G, et al.. Housing status and health care service utilization among low-income persons with HIV/AIDS. J Gen Intern Med. 2000;15:731–738.
59. Gelberg L, Gallagher TC, Andersen RM, et al.. Competing priorities as a barrier to medical care among homeless adults in Los Angeles. Am J Public Health. 1997;87:217–220.
60. Breakey WR, Fischer PJ, Kramer M, et al.. Health and mental health problems of homeless men and women in Baltimore. JAMA. 1989;262:1352–1357.
61. Kidder DP, Wolitski RJ, Campsmith ML, et al.. Health status, health care use, medication use, and medication adherence among homeless and housed people living with HIV/AIDS. Am J Public Health. 2007;97:2238–2245.
62. Buchanan D, Kee R, Sadowski LS, et al.. The health impact of supportive housing for HIV-positive homeless patients: a randomized controlled trial. Am J Public Health. 2009;99:S675–S680.
63. Bindman AB, Grumbach K, King TE. Health care disparities: An overview. In: King TE, Wheeler MB, eds. Medical Management of Vulnerable and Underserved Patients: Principles, Practice, and Populations. New York, NY: McGraw-Hill; 2007:13–25.
64. Fiscella K, Williams DR. Health disparities based on socioeconomic inequities: implications for urban health care. Acad Med. 2004;79:1139–1147.
65. Isaacs SL, Schroeder SA. Class—the ignored determinant of the Nation’s health. N Engl J Med. 2004;351:1137–1142.
66. Marmot MG, Rose G, Shipley M, et al.. Employment grade and coronary heart disease in British civil servants. J Epidemiol Community Health. 1978;32:244–249.
67. Shapiro M, Morton S. Variations in the care of HIV-infected adults in the United States. J Am Med Assoc. 1999;281:2305–2315.
68. McMahon J, Wanke C, Terrin N, et al.. Poverty, hunger, education, and residential status impact survival in HIV. AIDS Behav. 2011;15:1503–1511.
69. McFarland W, Chen S, Hsu L, et al.. Low socioeconomic status is associated with a higher rate of death in the era of highly active antiretroviral therapy, San Francisco. J Acquir Immune Defic Syndr. 2003;33:96–103.
70. Uphold CR, Mkanta WN. Use of health care services among persons living with HIV infection: State of the science and future directions. AIDS Patient Care STDS. 2005;19:473–485.
71. Kerr JC, Stephens TG, Gibson JJ, et al.. Risk factors associated with inpatient hospital utilization in HIV-positive individuals and relationship to HIV care engagement. J Acquir Immune Defic Syndr. 2012;60:173–182.
72. Palacio H, Shiboski C, Yelin E, et al.. Access to and utilization of primary care services among HIV-infected women. J Acquir Immune Defic Syndr. 1999;21:293–300.
73. Bhattacharya J, Goldman D, Sood N. The link between public and private insurance and HIV-related mortality. J Health Econ. 2003;22:1105–1122.
74. Riley ED, Gandhi M, Hare C, et al.. Poverty, unstable housing, and HIV infection among women living in the United States. Curr HIV/AIDS Rep. 2007;4:181–186.
75. Torian L V, Wiewel EW. Continuity of HIV-related medical care, New York City, 2005–2009: do patients who initiate care stay in care? AIDS Patient Care STDS. 2011;25:79–88.
76. Stone VE. HIV/AIDS in women and racial/ethnic minorities in the U.S. Curr Infect Dis Rep. 2012;14:53–60.
77. San Francisco Department of Public Health. HIV/AIDS Epidemiology Annual Report. San Francisco, CA: San Francisco Department of Public Health; 2010.
78. Benbow N, Scheer S, Wohl A, et al.. Linkage, retention, ART use and viral suppression in four large cities in the United States. Presented at: 19th International AIDS Conference; Washington, DC: July 22-27, 2012. Abstract MOPDC0303.
79. Havlir D V, Bassett R, Levitan D, et al.. Prevalence and predictive value of intermittent viremia with combination HIV therapy. JAMA. 2001;286:171–179.
80. Martinez V, Marcelin A-G, Morini JP, et al.. HIV-1 intermittent viraemia in patients treated by non-nucleoside reverse transcriptase inhibitor-based regimen. AIDS. 2005;19:1065–1069.
81. Sungkanuparph S, Overton ET, Seyfried W, et al.. Intermittent episodes of detectable HIV viremia in patients receiving nonnucleoside reverse-transcriptase inhibitor-based or protease inhibitor-based highly active antiretroviral therapy regimens are equivalent in incidence and prognosis. Clin Infect Dis. 2005;41:1326–1332.
82. Charpentier C, Landman R, Laouénan C, et al.. Persistent low-level HIV-1 RNA between 20 and 50 copies/mL in antiretroviral-treated patients: associated factors and virological outcome. J Antimicrob Chemother. 2012;67:2231–2235.
83. Winkleby MA, Jatulis DE, Frank E, et al.. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. Am J Public Health. 1992;82:816–820.
84. Shacham E, Nurutdinova D, Onen N, et al.. The interplay of sociodemographic factors on virologic suppression among a U.S. outpatient HIV clinic population. AIDS Patient Care STDS. 2010;24:229–235.
85. Zaller ND, Fu JJ, Nunn A, et al.. Linkage to care for HIV-infected heterosexual men in the United States. Clin Infect Dis. 2011;52(suppl 2):S223–S230.
86. Meyer JP, Chen NE, Springer SA. HIV treatment in the criminal justice system: critical knowledge and intervention gaps. AIDS Res Treat. 2011;2011:680617.
87. Gonzalez JS, Hendriksen ES, Collins EM, et al.. Latinos and HIV/AIDS: examining factors related to disparity and identifying opportunities for psychosocial intervention research. AIDS Behav. 2009;13:582–602.
88. Wolfson MC, Kaplan G, Lynch J, et al.. Relation between income inequality and mortality: empirical demonstration. West J Med. 1999;172:22–24.
89. Centers for Disease Control and Prevention. Cases of HIV infection and AIDS in the United States and dependent areas, by race/ethnicity, 2003–2007. HIV/AIDS Surveillance Suppl Rep. 2009;14:2007–2008.
90. IOM (Institute of Medicine). Monitoring HIV Care in the United States: Indicators and Data Systems Committee to Review Data Systems for Monitoring HIV Care Board on Population Health and Public Health Practice. Washington, DC: National Academies Press. 2012.
HIV care; disparities; engagement in care; viral suppression; persons with HIV; HIV surveillance
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