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

Sexual Behavior Transition and Acute and Early HIV Infection Among Men Who Have Sex With Men: Evidence from an Open Cohort in China, 2011-2019

The present study examined how sexual behaviors transit over time among men who have sex with men (MSM) and whether these transitions were associated with acute and early HIV (AEH) infection. An open cohort study was conducted using snowball sampling to recruit MSM via physical venues and Internet venues from 2011 to 2019, in China. Cox models were used to estimate the correlates of risk factors and AEH infection. We used Latent Transition Analysis (LTA) to describe behavioral profile and explore latent behavioral "trans-phenotypes," then examined the effect between different "trans-phenotypes" and AEH infection risk and explored the effect of characteristics as possible predictors of sexual behavior transition. Of 6502 MSM, a total of 1974 individuals with negative human immunodeficiency virus (HIV) tests at baseline and at least 2 visit records were included in the final analysis from 2011 to 2019. During an average 1.84 years of follow-up, 64 AEH infections were documented. In the multivariable Cox model, the association between condom use in last anal sex (HR: 0.095, 0.038-0.205), fewer sexual partners (HR: 0.375, 0.205-0.712), low frequency of condom use (HR: 3.592, 1.186-11.272), and AEH acquisition were found. The percentage of MSM with "maintain/develop safety-profile," "consistent risky-profile," and "safety-profile to risky-profile" were 52.48, 40.17, and 7.35%, respectively. Compared with "maintain\develop safety-profile," "consistent or develop risky-profile" had an increasing likelihood of AEH infection. Meanwhile, male sex workers (MSWs) or older MSM were more likely to consist or transit in "risky-profile." Having middle education is a risk factor to transit in "risky-profile" for MSM with "safety-profile" at baseline. In addition, MSM who accept health services in the past year engaged in higher proportion of developing safety-profile. Approximately half of MSM maintain or develop risky behavior with the increasing likelihood of AEH acquisition in China, which suggested that targeted and intensive interventions should be prioritized to maintain safety-profile. Clinical Trial Number: ChiCTR2000039500.

Patient acceptance of HIV rapid testing in the dental care setting

Dental settings are untapped venues to identify patients with undiagnosed HIV who may otherwise lack testing opportunities. Perceived lack of patient acceptance has been a significant barrier limiting dentists' willingness to offer HIV testing. This study implemented rapid HIV testing in dental settings located in an HIV prevalent region to evaluate patient acceptance. Two South Florida community health centers implemented routine oral rapid HIV testing as part of clinical practice, followed by exit interviews with patients immediately after to determine patient acceptance. The binary primary outcome was patient's acceptance of the rapid HIV test. Multivariable logistic regression assessed associations between patient characteristics and acceptance. Overall acceptance by dental patients (N = 600) was 84.5%. Patients who were more likely to participate in other medical screenings in dental settings were more than twice as likely to accept the test compared to those who were neutral/less likely (OR: 2.373; 95% CI: 1.406-4.004). Study findings highlight the high patient acceptance of HIV testing in dental settings. Widespread implementation of such testing will require an expanded societal view of the traditional role of the dentist that will embrace the potentially valuable role of dentistry in preventive health screenings and population health.

Brief Report: The Amsterdam Symptom and Risk-Based Score Predicts for Acute HIV Infection in Men Who Have Sex With Men in San Diego

OBJECTIVE

Dijkstra et al recently described a risk- and symptom-based score moderately predictive for HIV seroconversion in the preceding 6-12 months in men who have sex with men (MSM) in Amsterdam. Our objective was to determine whether this "Amsterdam Score" could also predict for acute HIV infection (AHI) in MSM.

DESIGN AND SETTING

This study is a case-control analysis of a prospectively enrolled cohort of MSM who voluntarily presented for HIV testing in San Diego. The study sample was composed of MSM who screened HIV antibody-negative and then either tested positive with AHI [HIV nucleic acid test (NAT)-positive] or tested HIV NAT-negative.

METHODS

The Amsterdam Score was calculated for each participant in the study sample. Score performance was assessed using receiver operating characteristic curves and their area under the curve (AUC). An optimal cutoff was determined using the Youden index.

RESULTS

Seven hundred fifty-seven MSM (110 AHI and 647 HIV NAT-negative) were included in the analysis. AHI and HIV-negative cases were similar in age [median 32 years (interquartile range 26-42) vs 33 (27-45), respectively, P = 0.082]. The Amsterdam Score yielded a receiver operating characteristic curve with an AUC of 0.88 (95% confidence interval: 0.84 to 0.91). An optimal cutoff of ≥1.6 was 78.2% sensitive and 81.0% specific.

CONCLUSIONS

The risk- and symptom-based Amsterdam Score was highly predictive (AUC of 0.88) of AHI in MSM in San Diego. The Amsterdam Score could be used to target NAT utilization in resource-poor settings among MSM who test HIV antibody-negative, although the potential cost-savings must be balanced with the risk of missing AHI diagnoses.

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

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.

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

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.

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

The effect of an HIV diagnosis on subsequent behavior of men who have sex with men (MSM) remains unclear. From 2009 to 2012 the 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 not recently HIV 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 after HIV testing recently HIV infected and not recently HIV infected men practiced more CAI within serodiscordant partnerships than HIV negative MSM: more CRAI 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 have been ongoing.