Differences in Risk Behavior and Demographic Factors Between Men Who Have Sex With Men With Acute and Nonacute Human Immunodeficiency Virus Infection in a Community-Based Testing Program in Los Angeles

Davey, Dvora Joseph; Beymer, Matthew R; Roberts, Chelsea; Bolan, Robert; Klausner, Jeffrey D.

doi:10.1097/qai.0000000000001233

Cited by 11 publications

(9 citation statements)

References 30 publications

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“…Studies in this systematic review included diverse MSM populations, including international studies in Asia [ 15 , 16 , 17 , 18 , 19 , 20 ], Africa [ 21 , 22 , 23 ], South America [ 24 , 25 ], and Europe [ 26 , 27 ] (41%); Black and Latino persons in the United States [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ] (25%); and young adults or adolescents [ 36 , 37 , 38 , 39 ] (13%). Half of studies (50%) used only community-based surveys [ 15 , 16 , 18 , 20 , 21 , 24 , 25 , 28 , 29 , 32 , 35 , 37 , 38 , 40 , 41 , 42 ], 38% ( n = 12) used population-based surveys [ 17 , 19 , 22 , 23 , 26 , 33 , 34 , 36 , 39 , 43 , …”

Section: Resultsmentioning

confidence: 99%

Bias Adjustment Techniques Are Underutilized in HIV Sexual Risk Estimation: A Systematic Review

Tran

Goldstein

Welles

2018

IJERPH

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Background: Valid measurement of determinants of HIV infection among men who have sex with men (MSM) is critical for intervention planning and resource allocation. However, sexual minority research concerning HIV risk often relies on proxy exposures of sexual behaviors such as sexual orientation and partner gender. Inferring high risk sexual behaviors (i.e., condomless anal intercourse) from these proxies inaccurately captures HIV risk, but few studies have attempted to correct for this bias. Methods: We performed a systematic review of methodological practices for estimating risk of HIV infection among MSM. Results: We identified 32 studies in which high risk sexual behavior was assessed: 82% (n = 26) measured and used sexual risk behaviors (e.g., condomless anal intercourse or sexual positioning) to assess risk of HIV infection; 9% (n = 3) used proxy measures; and 9% (n = 3) used both behavior and proxy variables. Various treatments of misclassification reported by investigators included the following: 82% (n = 26) discussed misclassification of sexual behavior as a potential limitation; however, among these studies, no attempts were made to correct misclassification; 12% (n = 4) did not report exposure misclassification, and 6% (n = 2) explicitly considered this information bias and conducted a Bayesian approach to correct for misclassification. Conclusions: Our systematic review indicates that a majority of studies engaging in collecting primary data have taken additional steps to acquire detailed information regarding sexual risk behaviors. However, reliance on population-based surveys may still lead to potentially biased estimates. Thus, bias analytic techniques are potential tools to control for any suspected biases.

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Section: Resultsmentioning

confidence: 99%

Bias Adjustment Techniques Are Underutilized in HIV Sexual Risk Estimation: A Systematic Review

Tran

Goldstein

Welles

2018

IJERPH

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“…The men in our study came from a site with a relatively high rate of recent infection; 15% of 1,082 men with new HIV diagnoses of 66,546 tested were acutely infected (Joseph Davey, Beymer, Roberts, Bolan, & Klausner, 2017) suggesting much potential for continuing transmission in this population. While our sample was limited by high loss to follow-up, it is clear that few men in our study of community testors were on ART soon after diagnosis and a significant percent remained off therapy during the year of follow-up yet continued to practice transmission behaviors reported at the time of their diagnosis.…”

Section: Discussionmentioning

confidence: 99%

Behavior change following HIV diagnosis: findings from a Cohort of Los Angeles MSM

2017

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The effect of an HIV diagnosis on subsequent behavior of men who have sex with men (MSM) remains unclear. From 2009 - 2012 he NIDA funded Metromates Study enrolled and followed for one year MSM seeking testing for HIV in Los Angeles, assessing those with new HIV diagnoses for acute/recent HIV infection. Behavioral data were collected via Computer-Assisted Self-Interview from 321 men of whom 125 were classified as recently HIV infected, 91 as not recently HIV infected, and 105 as HIV-negative. Differences over time between those with recent HIV infection, not recent HIV infection, and no HIV were evaluated using bivariate and multivariable analyses for repeat measures to assess associations between HIV group, behaviors and condomless receptive (CRAI), intersertive (CIAI), or any condomless anal intercourse (CAI). Participants were mostly young (59% < 30 years of age) and minority. Median number of partners reported in past year dropped significantly over time among recently infected MSM (10 to 5) and HIV negative men (5 to 3) but not for HIV not recently infected. No changes comparing baseline to follow-up were noted in reports of CAI within each HIV-group. Based on GEE multivariable analyses adjusting for age, and race/ethnicity post HIV testing recently HIV infected and not recently HIV infected practiced more CAI within serodiscordant partnerships than HIV negative MSM: more CIAI than the HIV negatives (AOR=4.90; 95% CI 1.80-13.29 and AOR= 5.01; 95% CI 1.77-14.16 among recently infected and not recently infected, respectively) but only more CIAI among not recently infected (AOR 3.48; 95% CI 1.31-9.24) when compared to HIV negatives. For MSM seeking HIV testing in Los Angeles at that time, there was little indication of behavior change following HIV diagnosis and continued CAI, suggesting that without rapid linkage to care and viral suppression significant transmissions may be ongoing.

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“…Individuals with HIV may go many years without diagnosis, during which time they may expose uninfected individuals to HIV. Efforts to improve the diagnosis rate include educational programs, as an individual’s perceived risk was shown to be highly correlated with the individual obtaining multiple HIV tests [ 5 – 8 ]. Several studies have found a 50% reduction in risky behaviors after diagnosis, including safer sex practices, reduction in partner number, and medications that reduce viral load [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…Various studies report between 50–96% of diagnosed individuals in the U.S. rely on public medical care to obtain their ART medications [ 10 , 20 , 24 – 26 ]. Access to care remains critical, but this has not been considered when modeling the dynamics of the epidemic [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Estimating epidemiological parameters of a stochastic differential model of HIV dynamics using hierarchical Bayesian statistics

Dale

Guo

2018

PLoS ONE

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Current estimates of the HIV epidemic indicate a decrease in the incidence of the disease in the undiagnosed subpopulation over the past 10 years. However, a lack of access to care has not been considered when modeling the population. Populations at high risk for contracting HIV are twice as likely to lack access to reliable medical care. In this paper, we consider three contributors to the HIV population dynamics: at-risk population exhaustion, lack of access to care, and usage of anti-retroviral therapy (ART) by diagnosed individuals. An extant problem in the mathematical study of this system is deriving parameter estimates due to a portion of the population being unobserved. We approach this problem by looking at the proportional change in the infected subpopulations. We obtain conservative estimates for the proportional change of the infected subpopulations using hierarchical Bayesian statistics. The estimated proportional change is used to derive epidemic parameter estimates for a system of stochastic differential equations (SDEs). Model fit is quantified to determine the best parametric explanation for the observed dynamics in the infected subpopulations. Parameter estimates derived using these methods produce simulations that closely follow the dynamics observed in the data, as well as values that are generally in agreement with prior understanding of transmission and diagnosis rates. Simulations suggest that the undiagnosed population may be larger than currently estimated without significantly affecting the population dynamics.

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Differences in Risk Behavior and Demographic Factors Between Men Who Have Sex With Men With Acute and Nonacute Human Immunodeficiency Virus Infection in a Community-Based Testing Program in Los Angeles

Cited by 11 publications

References 30 publications

Bias Adjustment Techniques Are Underutilized in HIV Sexual Risk Estimation: A Systematic Review

Bias Adjustment Techniques Are Underutilized in HIV Sexual Risk Estimation: A Systematic Review

Behavior change following HIV diagnosis: findings from a Cohort of Los Angeles MSM

Estimating epidemiological parameters of a stochastic differential model of HIV dynamics using hierarchical Bayesian statistics

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