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Learn More. Patterns of HIV transmission vary widely across demographic groups. Identifying and engaging these groups are necessary to prevent new infections and diagnose disease among people who are unaware of their infection. The objective of this study was to determine characteristics of newly diagnosed individuals across an entire state to determine patterns of HIV transmission.

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We performed a latent class analysis LCA to identify Rhode demographic and behavioral characteristics of people with newly diagnosed HIV. LCA revealed 2 major classes. HIV prevention approaches, including pre-exposure prophylaxis, should be adapted to the needs of specific groups. Rhode Island offers lessons for other states focused on eliminating HIV transmission. InRhode Island reported 65 new HIV diagnoses, down from a peak of inthe highest of diagnoses in the past decade.

We evaluated their demographic and behavioral characteristics and identified targets for HIV prevention and treatment efforts. We recruited people with new diagnoses from all major HIV outpatient clinics in the state. Those who provided informed consent participated in a one-time structured interview deed to collect demographic, behavioral, and clinical data. We collected the following data: 1 demographic characteristics, including age, sex, race, ethnicity, place of birth, education level, annual income, and insurance coverage; 2 behaviors in the 12 months before HIV diagnosis, including substance use, and sex of sex partners, frequency of condom use, and locations for meeting sexual partners eg, bar, club, bathhouse, online ; and 3 clinical data, hookup history of mental illness, history of other sexually transmitted diseases STDsdate of last negative HIV test result, when and where the person believed he or she acquired HIV, CD4 cell count, history of opportunistic infections, and s and symptoms consistent with acute retroviral syndrome.

Based on self-report and a review of medical records, we categorized HIV-infected people by likely HIV transmission risk behavior, including MSM, male who has sex with females, female who has sex with males, or person who injects drugs. We categorized the most likely place of residence at suspected time of HIV infection as follows: living in Rhode Island and infected in-state, living in Rhode Island but infected in another state or country, living and infected in another state, and living and infected in another country.

We conducted descriptive analyses of demographic and behavioral data stratified by sexual behavior and residence at suspected time the infection. We used latent class analysis LCA to identify distinct groups of newly diagnosed people based on demographic and behavioral characteristics.

LCA is a statistical approach that generates classes based on patterns of data with the goal of identifying clusters, or groupings, of people with similar characteristics. The BLRT tests the null hypothesis of no improvement in fit for the model under consideration compared with a model with 1 fewer class. The analysis also considered entropy, which measures the extent to which classes are distinct from each other, average posterior probability of class membership, and interpretability of the Island entropy values range from 0 no separation to 1 perfect separation.

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Outcomes of primary interest included route of transmission, substance use, lifetime STD history, frequency of condom use, of partners in the 12 months before HIV diagnosis, HIV testing, concurrent HIV and AIDS diagnoses, and where individuals met their sexual partners. MSM with newly diagnosed HIV were ificantly more likely to be younger, be white, have a higher education level and income, have more sexual partners, and use condoms more frequently than non-MSM in the sample.

Demographic and behavioral characteristics of a sample of individuals newly diagnosed with HIV in Rhode Island, Those who believed they acquired HIV in Rhode Island were more likely than those who believed they did not acquire HIV in Rhode Island to be white, born in the state, and report meeting sex partners online in the 12 months before diagnosis. In the LCA, comparison of overall model fit indices demonstrated that a 2-class solution was preferable Table 2.

Compared with the 1-class model and the 3-class model a 4-class model did not convergethe 2-class solution provided low BIC and AIC values and good entropy 0.

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The 2-class model also showed a substantial improvement in fit compared with the 1-class model, according to the BLRT. Although the AIC was slightly lower in the 3-class model than in the 2-class model, the BLRT suggested no substantial improvement in fit for the 3-class model compared with the 2-class model. The average probability of latent class membership was 0.

Fit indices for 1-class, 2-class, and 3-class models in a latent class analysis of a sample of individuals with newly diagnosed HIV in Rhode Island, Probabilities of variables used in the 2-class solution in a latent class analysis of people with newly diagnosed HIV in Rhode Island, Abbreviation: MSM, gay, bisexual, or other men who have sex with men. Latent class characteristics and logistic regression odds ratios for differences between classes in a latent class analysis of individuals with newly diagnosed HIV in Rhode Island, This comprehensive attempt to characterize all new HIV diagnoses in Rhode Island is among the first statewide efforts to evaluate detailed clinical, demographic, and behavioral characteristics of this population across an entire state.

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The analysis revealed 2 main classes of people who constitute most new HIV diagnoses in Rhode Island. Our study also demonstrated a low prevalence of injection drug use among those with a new diagnosis of HIV. The population density and close proximity of Rhode Island to neighboring New England states facilitate travel between states, which in turn creates opportunities for out-of-state HIV infections or in-state infections with an out-of-state origin. One reason for the high prevalence of in-state infections may be that, despite the ease of interstate travel, most US residents reside in their state of birth.

Statewide evaluation of new hiv diagnoses in rhode island: implications for prevention

In a study, more than half of MSM recruited from a Rhode Island sex venue were from out of state. In our study, MSM reported a high frequency of sexual and substance use risk behaviors, along with infrequent HIV testing.

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Together, these factors may contribute to an increased risk of local transmission among MSM. Among those likely infected outside of Rhode Island, the primary public health approach should include early diagnosis and linkage to care, via routine opt-out testing and outreach efforts. With only 65 new HIV diagnoses inRhode Island is among the states closest in the nation to achieving the goals and is surpassing national estimates for diagnosis, retention in care, and viral suppression.

These 2 groups require distinct interventions and public policy responses. At least half of newly diagnosed MSM in Rhode Island meet their partners online, 34 highlighting public health opportunities to reach this population before infection. Conversely, the findings from class 2 indicate a need for efforts to promote early diagnosis and engagement in HIV care, which may be more salient for immigrant populations who acquire HIV outside of Rhode Island.

Test-and-treat strategies would likely benefit both groups. Our study had several limitations.

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First, we were unable to interview all people with newly diagnosed HIV during the study period, which may have affected the demographic and behavioral. Second, we relied on self-report for data on residence at suspected time of HIV infection, which is subject to recall bias. Third, some Rhode Island population demographic characteristics may limit the generalizability of our findings to other settings.

However, our sample represents most HIV diagnoses statewide during the study period, an accomplishment facilitated in part by the small size and highly centralized HIV care system in the state. In addition, we attempted to verify approximate dates of diagnosis by collecting data about last HIV test date and date of immigration to help determine when a given person may have acquired HIV. Finally, the application of LCA was a novel approach to analyzing these data. Thus, although demographic characteristics of populations and HIV diagnoses vary by state, our findings from Rhode Island provide a model for characterizing risk groups to target public health interventions.

By informing the delivery of behavioral and biomedical interventions to groups most likely to benefit from them, our findings can help prioritize public health approaches in a state that is close to eliminating HIV transmission.

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National Center for Biotechnology InformationU. Journal List Public Health Rep v. Public Health Rep. Published online Jun 6. Philip A. NunnScD 5. Madeline C. Martha M. Amy S. Author information Copyright and information Disclaimer. : ude.

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Keywords: men who have sex with men, immigrants, HIV prevention, pre-exposure prophylaxis, Table 1. Characteristic Total, No. Open in a separate window. Table 2. Model a Log Likelihood No. Abbreviation: NA, not applicable. Table 3. Table 4.

A nearly 50% decrease in new hiv diagnoses in rhode island from – implications for policy development and prevention

Covariates Class 1, No. Discussion This comprehensive attempt to characterize all new HIV diagnoses in Rhode Island is among the first statewide efforts to evaluate detailed clinical, demographic, and behavioral characteristics of this population across an entire state. Limitations Our study had several limitations. References 1.

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HIV Surveill Rep. Ann Epidemiol.