Conclusions & Implications

Slides:



Advertisements
Similar presentations
PMTCT FAILURE: THE ROLE OF MATERNAL AND FACILITY –RELATED FACTORS ICASA Presentation 8 th to 12 th Dec 2013 Onono Maricianah 1, Elizabeth A. Bukusi 1,
Advertisements

Antiretroviral therapy eligibility at enrollment and time to treatment initiation in Ethiopia Chloe A. Teasdale 1, Chunhui Wang 1, Sileshi Lulseged 1,
Influences of Marijuana Use on Adolescent HIV/STI Acquisition and Care Jonathan M. Ellen, MD Johns Hopkins School of Medicine.
HIV in the United Kingdom: 2013 HIV and AIDS Reporting Section Centre for Infectious Disease Surveillance and Control (CIDSC) Public Health England London,
The hidden HIV epidemic: what do mathematical models tell us? The case of France Virginie Supervie, Jacques Ndawinz & Dominique Costagliola U943 Inserm.
C. Andres Bedoya, PhD Behavioral Medicine Service Department of Psychiatry Massachusetts General Hospital / Harvard Medical School Factors related to high-risk.
Virologic and immunologic response following antiretroviral therapy initiation among pregnant and postpartum women with acute HIV-1 infection: MOPDB0101.
Introduction DCDOH supports HIV test and treat activities - increased number of HIV tests performed, emphasis on earlier linkage to care. Limited data.
Racial Disparities in Antiretroviral Therapy Use and Viral Suppression among Sexually Active HIV-infected Men who have Sex with Men— United States, Medical.
The Effect of Gender Based Violence (GBV) on Mortality: a longitudinal study of US women with & at risk for HIV Kathleen M. Weber Steve R. Cole, Jane Burke-Miller,
Washington D.C., USA, JULY Rulin C. Hechter 1 MD,PhD Jean Q. Wang 1 PhD Margo A. Sidell 1 ScD William J. Towner 2 MD 1 Dept.
Transition Program of HIV-infected adolescents to Adult HIV care in Buenos Aires, Argentina S. Arazi Caillaud 1, D. Mecikovsky 1, A.Bordato.
Typologies of Alcohol Dependent Cocaine-using Women Enrolled in a Community-based HIV Intervention Victoria A. Osborne, Ph.D., MSW*, Linda B. Cottler,
Engagement in the HIV care cascade among transgender women enrolled in a public HIV clinic in Buenos Aires, Argentina, M.E. Socías 1,2, O. Sued.
Lipoatrophy and lipohypertrophy are independently associated with hypertension: the effect of lipoatrophy but not lipohypertrophy on hypertension is independent.
Methods Data for this NIDA-funded HIV prevention trial (Project WORTH) were drawn from 337 women offenders under community supervision, who reported using.
Olivia Chang, MPH Research and Program Manager Pangaea Global AIDS
Annual Epidemiological Spotlight on HIV in London: 2014 data Field Epidemiology Services PHE Publications gateway number
HIV Testing in Acute Care Settings Rich Rothman, MD, PhD, FACEP CDC, DHHS, OraSure Technologies, Abbott  Historical.
HIV and STI Department, Health Protection Agency - Colindale HIV and AIDS Reporting System Predictors for high viraemia among the treatment naïve population.
HIV in America What’s New in 2012 Christopher Hurt, MD Clinical Assistant Professor NC AIDS Education and Training Center 2012 HIV Update.
1 Machismo as a determinant for HIV/STD risk behavior among Latino MSM Jacqueline L. Sears, MPH.
Background  Substance abusers are at risk for HIV and other STIs.  Anal intercourse (AI) is riskier than vaginal intercourse.  Studies of AI have focused.
HIV Risk Factors and Injection Drug Use among Men who Have Sex with Men in Unguja Island, Zanzibar, Tanzania A. Holman 1, M. Dahoma 2, L. Johnston 3, K.
Elijah Odoyo-June 1,3, John Rogers 2, Walter Jaoko 1,3, Robert C. Bailey 1, 2 1 Nyanza Reproductive Health Society 2 University of Illinois at Chicago.
Associations Between Recent Gender- Based Violence and Pregnancy, Sexually Transmitted Infections, Condom Use Practices, and Negotiation of Sexual Practices.
Differences between undiagnosed, HIV-positive and HIV-negative Black transgender women in the United States: Results from POWER Presented by Leigh A. Bukowski,
Forced Sexual Violence and HIV Infection among MSM in Tamil Nadu Presented by Santosh Kumar Sharma On behalf of Rakesh Kumar Singh Ph.D Research Scholar.
Correlates of Never Using Condoms for Oral Sex Sara K. Head, MPH 1 Richard A. Crosby, PhD 1 Gregory Moore, MD 1 Adewale Troutman, MD 2 1 University of.
1 High levels of risk behavior among people living with HIV initiating and waiting to start antiretroviral therapy in Cape Town South Africa TP Eisele,
Correlates of being outside the cascade among adults aged years in Zimbabwe: Results from the Zimbabwe Population-based HIV.
Why don’t Key Populations Access HIV
Men are absent across the HIV continuum of care in a rural area of southern Mozambique Laura Fuente-Soro, Elisa Lopez-Varela, Orvalho Augusto , Charfudin.
1University of Kentucky, Lexington, Kentucky
Kimberly Jeffries Leonard, Ph.D.
Gaps in the cascade of care in two high prevalence settings in Zimbabwe and Malawi Nolwenn Conan1, Cyrus Paye2, Erica Simons2, Abraham Mapfumo3, Tsitsi.
Correlates of ever had sex among perinatally HIV-infected adolescents in Uganda.   Scovia Nalugo Mbalinda, Noah Kiwanuka, Lars E. Ericksson, Rhoda Wanyenze,
Psychosocial and behavioral predictors of partner notification for STD and HIV exposure among MSM Matthew J. Mimiaga, ScD, MPH, Sari L. Reisner, MA,
Hatch-Maillette, M. 1, Calsyn, D. A1,2, Doyle, S. 1, Woods, A
Melanie L. Fritza Ronald J. Lubelchek, MD a, b, c*
HIV treatment cascade analysis for people who inject drugs in Ukraine: identifying the correlates of HIV care outcomes Kostyantyn Dumchev1, Olga Varetska2,
Promoting male partner and couples testing through secondary distribution of self-tests by pregnant and postpartum women: a randomized trial Kawango Agot1,
Factors affecting virological failure in patients receiving antiretroviral therapy: a prospective HIV Clinical cohort in rural Uganda. Patrick Kazooba1,
The potential for selection and misclassification bias when sampling men who have sex with men (MSM) in gay bars Karyn Heavner, PhD 1, 2, James Tesoriero,
Kristen Williams, Jonathan J.K. Stoltman, and Mark K. Greenwald
L.F. Jefferys1, J. Hector1, M.A. Hobbins2, J. Ehmer2, N. Anderegg3
Amanda D. Castel, MD, MPH Assistant Research Professor
HIV prevalence and sexual behavioral roles among Men who have sex with men (MSM) in Nigeria T. Badru , O. Adedokun, E. Oladele , O. Adebayo , H. Khamofu.
STIs in a multi-site sample of high-risk, substance-using MSM:
Being physically abused Adjusted Odds Ratio (95% CI)
SEXUAL RISK BEHAVIOR OF PLWHA IN THE WA MUNICIPALITY
Management and Development for Health (MDH)
Poster WP41; Contact: David A. Katz,
North Carolina Medical Monitoring Project
Summary Sheet Figures and Maps
Summary Sheet Figures and Maps
VACS Scientific Meeting Houston, TX February 2004
Summary Sheet Figures and Maps
M Javanbakht, S Guerry, LV Smith, P Kerndt
Summary Sheet Figures and Maps
Melissa Herrin, Jan Tate ScD, MPH & Amy Justice, MD, PhD
Summary Sheet Figures and Maps
Summary Sheet Figures and Maps
Finding Sex Partners On-Line: What’s the Risk for STI
Andreas D. Haas, PhD Postdoctoral fellow, ICAP at Columbia University
Knowledge of HIV Status in Kenya
Kyle T. Bernstein, Katherine Ahrens, Susan S. Philip, Jeffrey D
Share your thoughts on this presentation with #IAS2019
Share your thoughts on this presentation with #IAS2019
Public Health Implications
Presentation transcript:

Conclusions & Implications Factors associated with out-of-care or undiagnosed HIV infection at baseline among men who have sex with men—The Anza Mapema Study Colin Kunzweiler1, Robert Bailey1, Supriya Mehta1, Susan Graham2, Duncan Okall3, Fredrick Otieno3 1University of Illinois at Chicago, Epidemiology and Biostatistics, Chicago, IL, USA; 2University of Washington, Medicine, Epidemiology, and Global Health, Seattle, WA, USA; 3Nyanza Reproductive Health Society, Kisumu, Kenya Introduction Results Results The UNAIDS 90-90-90 targets have prioritized HIV testing and awareness of infection status among persons living with HIV. Men who have sex with men (MSM) are disproportionately burdened by HIV infection compared to men of the general population, and 15% of all new HIV infections in Kenya are attributed to male-male sex. However, recent estimates suggest only ~33% of MSM know that they are infected with HIV. There is an urgent need for programs that assist MSM to accept testing, to know their status, and to become engaged in treatment and care.   Sociodemographic and psychosocial characteristics Median age: 24 years (IQR: 21-28 years) 79.1% had completed >9 years of education 50.1% of all men reported harmful alcohol use (Alcohol Use Disorders Identification Test >8) Most (71.9%) had ever had sex with a female partner Most (63.9%) had transactional sex in the past 3 months Clinical characteristics of HIV-positive men 23 were virally suppressed (plasma viral load <1,000 copies/mL) 2 (both PDOC) reported previously taking antiretrovirals (ARVs) Median CD4 count: 486 (IQR: 338-664) 15 (20.6%) had advanced beyond WHO clinical stage 1 at baseline Multivariable multinomial logistic regression Adjusted relative risk ratio (aRRR) of PDOC status, relative to HIV-negative status, greater for men who experienced MSM trauma (aRRR=3.59), who did not report harmful alcohol use (aRRR=3.46), and who experienced upsetting sexual experiences during childhood (aRRR=3.42) NDOC infection status associated with older men (>30 years: aRRR=3.90), completing <8 years of education (aRRR=2.23) Figure 1: Study recruitment and enrollment. Figure 2: Clinical characteristics of HIV-positive men. Newly diagnosed out of care (n=54; 72%) Screened 1,012 Previously diagnosed out of care (n=21; 28%) 248 Ineligible 3 doubly enrolled 5 declined Consented 756 45 withdrawn Enrolled 711 Objectives To report the prevalence of HIV infection at baseline among all participants To identify sociodemographic characteristics and sexual behaviors associated with known and newly diagnosed HIV infections (relative to HIV-negative) at enrolment HIV-negative 636 (89.5%) PDOC 21 (3.0%) NDOC 54 (7.6%) Figure 3: Prevalence of HIV infection by predictor. Table 1: Distribution of participant characteristics by category of HIV infection status (*p<0.05). Age (years) Education (years) Harmful alcohol use MSM trauma Childhood sex. abuse Variable Total n (%) Negative PDOC NDOC Sample 711 (100.0) 636 (89.5) 21 (3.0) 54 (7.6) Age (years)* 18-19 77 (10.8) 72 (11.3) 2 (9.5) 3 (5.6) 20-24 321 (45.1) 296 (46.5) 7 (33.3) 18 (33.3) 25-29 177 (24.9) 159 (25.0) 5 (23.8) 13 (24.1) >30 136 (19.1) 109 (17.1) 20 (37.0) Education (years) 0 to 8 149 (21.0) 124 (19.5) 6 (28.6) 19 (35.2) 9 to 12 354 (49.8) 324 (50.9) 10 (47.6) 13 or more 208 (29.3) 188 (29.6) 15 (27.8) Harmful alcohol use (AUDIT>8) No 354 (49.9) 316 (49.8) 13 (61.9) 25 (46.3) Yes 356 (50.1) 319 (50.2) 8 (38.1) 29 (53.7) Harmful substance use (DAST>3) 169 (23.8) 150 (23.6) 12 (22.2) 542 (76.2) 486 (76.4) 14 (66.7) 42 (77.8) Social support (range: 0-100%) (median/IQR) 50 (34-64) 50 (36-64) 48 (32-66) 48 (32-55) Upsetting sexual experiences during childhood (childhood sexual abuse)* 220 (30.9) 189 (29.7) 491 (69.1) 447 (70.3) 36 (66.7) Physical abuse or verbal threats (MSM trauma)* 258 (39.1) 224 (37.7) 15 (71.4) 19 (42.2) 402 (60.9) 370 (62.3) 26 (57.8) Ever had sex with a female partner 511 (71.9) 458 (72.0) 12 (57.1) 41 (75.9) 200 (28.1) 178 (28.0) 9 (42.9) Transactional sex (last 3 months) 454 (63.9) 401 (63.1) 38 (70.4) 257 (36.1) 235 (36.9) 16 (29.6) Always protected anal intercourse with a man (last 3 months)* 421 (60.6) 367 (59.1) 17 (81.0) 37 (69.8) 274 (39.4) 254 (40.9) 4 (19.1) 16 (30.2) Methods Limitations Eligibility and Recruitment Aged >18 years Oral or anal sex with a man in the past 6 months Not enrolled in HIV care Not taken ART in the past 3 months Outcome variable HIV infection status—3 categories: HIV-negative Previously diagnosed HIV-positive and out of care (PDOC) Newly diagnosed HIV-positive and out of care (NDOC) Serial testing algorithm: two rapid tests (tie-breaker if necessary) Predictor variables Sociodemographic characteristics (6 variables) Sexual behaviors (9 variables) Psychosocial scales (9 variables), including alcohol use (Alcohol Use Disorders Identification Test-AUDIT), substance use (Drug Abuse Screening Test-DAST), and social support Clinical characteristics (4 variables among HIV-positive men) Statistical analyses Multinomial logistic regression analysis: Index categories: PDOC; NDOC Referent (base) category: HIV-negative Manual, backwards multivariable model building included predictors where p<0.05 for at least one comparison Unadjusted and adjusted relative risk ratios (RRR) and 95% confidence intervals (CI) are presented Cross-sectional analysis prohibits causal interpretation Participants not representative of MSM population in Kisumu Participation bias: MSM who participated may be different from those who declined or who were not assessed for eligibility Misclassification is possible: While validated in other populations, psychosocial scales are not validated specifically among Kenyan MSM Conclusions & Implications Table 2: Results of multivariable multinomial logistic regression analyses (n=660). Among 711 men enrolled, prevalence of HIV was 10.6% (n=75) and the majority of HIV-positive MSM (72%) were unaware of their infection. Greater efforts are necessary to reach MSM and engage them in HIV testing, care, and treatment. Histories of childhood sexual abuse and same-sex related trauma were more likely to be PDOC. Researchers and clinicians must screen and provide supportive counseling for these histories in order to improve engagement and retention of MSM in HIV care and treatment. Variable PDOC aRRR (95% CI) NDOC Age (years) (ref: 18-19) >30 2.71 (0.54-13.61) 3.90 (1.01-15.04) 25-29 1.59 (0.28-9.15) 1.33 (0.34-5.16) 20-24 0.98 (0.20-4.93) 1.27 (0.35-4.60) Education (years) (ref: >13) 0 to 8 1.32 (0.36-4.81) 2.23 (1.00-4.97) 9 to 12 1.02 (0.34-3.10) 1.00 (0.46-2.18) Harmful alcohol use (AUDIT>8) (ref: Yes) No 3.46 (1.63-7.37) 1.13 (0.58-2.22) Physical abuse or verbal threats (MSM trauma) (ref: No) Yes 3.59 (1.43-9.00) 0.97 (0.50-1.90) Childhood sexual abuse (ref: No) 3.42 (1.44-8.12) 1.31 (0.67-2.54) Acknowledgements The authors thank the study participants, the Nyanza Reproductive Health Society Team, the University of Illinois at Chicago, the University of Washington, the Centers for Disease Control and Prevention, and the Kenya Ministry of Health. The authors also thank Dr. Ross Slotten and the UIC Slotten Scholarship in Global Health for their support of this research.