8 research outputs found

    Diagnoses of HIV infection among black/African American MSM and non-MSM, by age at diagnosis, 2005–2009—17 areas.

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    <p>Note. Data include persons with diagnosed HIV infection regardless of stage of disease at diagnosis. HIV diagnosis data were statistically adjusted for missing transmission category, but not for reporting delays or incomplete reporting.</p><p>MSM, men who reported ever having had sexual contact with other men.</p>a<p>Rates are per 100,000 population.</p><p>Diagnoses of HIV infection among black/African American MSM and non-MSM, by age at diagnosis, 2005–2009—17 areas.</p

    HIV diagnosis rate ratios among black/African American MSM and non-MSM, by selected census tract–level social determinants of health, 2005–2009—17 areas.

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    <p>Note. Data include persons with diagnosed HIV infection regardless of stage of disease at diagnosis. HIV diagnosis data were statistically adjusted for missing transmission category, but not for reporting delays or incomplete reporting. All results for each outcome of interest in the models are based on controlling for all other variables.</p><p>MSM, men who reported ever having had sexual contact with other men.</p><p>CI, confidence interval.</p><p>HIV diagnosis rate ratios among black/African American MSM and non-MSM, by selected census tract–level social determinants of health, 2005–2009—17 areas.</p

    sj-docx-1-phr-10.1177_00333549231208488 – Supplemental material for Interstate Mobility of People With Diagnosed HIV in the United States, 2011-2019

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    Supplemental material, sj-docx-1-phr-10.1177_00333549231208488 for Interstate Mobility of People With Diagnosed HIV in the United States, 2011-2019 by Amanda Okello, Ruiguang Song, H. Irene Hall, André Dailey and Anna Satcher Johnson in Public Health Reports</p

    Prevalence odds ratios<sup>a</sup> of HIV infection diagnosis for black/African American MSM vs. non-MSM, by selected census tract-level social determinants of health (SDH), 2005–2009—17 areas.

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    <p>Note. Data include persons with diagnosed HIV infection regardless of stage of disease at diagnosis. HIV diagnosis data were statistically adjusted for missing transmission category, but not for reporting delays or incomplete reporting. All results for each outcome of interest in the models are based on controlling for all other variables.</p><p>MSM, men who reported ever having had sexual contact with other men.</p><p>CI, confidence interval.</p>a<p>Black non-MSM is the reference group.</p>b<p>The prevalence odds is defined as (#MSM+1)/(#non-MSM+1), where adding 1 to both the numerator and the denominator avoids the prevalence odds undefined when there are no diagnosed HIV infections among black non-MSM. PORs>1 indicates that among black males, as the proportion of a SDH variable of interest increases, the probability of black MSM diagnosed with HIV is higher compared to black non-MSM.</p><p>Prevalence odds ratios<sup><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107701#nt110" target="_blank">a</a></sup> of HIV infection diagnosis for black/African American MSM vs. non-MSM, by selected census tract-level social determinants of health (SDH), 2005–2009—17 areas.</p

    Mean Recency Period for Estimation of HIV-1 Incidence with the BED-Capture EIA and Bio-Rad Avidity in Persons Diagnosed in the United States with Subtype B

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    <div><p>HIV incidence estimates are used to monitor HIV-1 infection in the United States. Use of laboratory biomarkers that distinguish recent from longstanding infection to quantify HIV incidence rely on having accurate knowledge of the average time that individuals spend in a transient state of recent infection between seroconversion and reaching a specified biomarker cutoff value. This paper describes five estimation procedures from two general statistical approaches, a survival time approach and an approach that fits binomial models of the probability of being classified as recently infected, as a function of time since seroconversion. We compare these procedures for estimating the mean duration of recent infection (MDRI) for two biomarkers used by the U.S. National HIV Surveillance System for determination of HIV incidence, the Aware BED EIA HIV-1 incidence test (BED) and the avidity-based, modified Bio-Rad HIV-1/HIV-2 plus O ELISA (BRAI) assay. Collectively, 953 specimens from 220 HIV-1 subtype B seroconverters, taken from 5 cohorts, were tested with a biomarker assay. Estimates of MDRI using the non-parametric survival approach were 198.4 days (SD 13.0) for BED and 239.6 days (SD 13.9) for BRAI using cutoff values of 0.8 normalized optical density and 30%, respectively. The probability of remaining in the recent state as a function of time since seroconversion, based upon this revised statistical approach, can be applied in the calculation of annual incidence in the United States.</p></div

    Estimated days of mean duration of recent infection (MDRI) and standard error, in parentheses, for BED and BRAI incidence bioassays.

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    <p>A total of 858 measurements from 209 subjects of 4 cohorts and 749 measurements from 162 subjects of 3 cohorts were used to estimate BED and BRAI MDRI, respectively. Results for five estimation procedures are given.</p

    The probability of remaining in the recent state as a function of time since seroconversion for BED and BRAI bioassays.

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    <p>Model predicted probabilities from five estimation methods are given; blue lines represent the survival methods, green dashed lines the binomial logit, and red dotted line the GAM method. Subject-specific increasing trends in normalized OD or avidity are graphed in the background on the secondary vertical axis. The horizontal dashed line represents the bioassay threshold for classification of recency/non-recency (BED threshold 0.8; BRAI threshold 30%).</p

    Characteristics of data used in estimation of MDRI by data source.

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    <p>The median and interquartile range of distributions are given for the HIV-negative seroconversion interval, i.e., time between last HIV-negative and first HIV-positive tests; the HIV-positive follow-up, reflecting the total duration of observation after testing positive; the number of HIV-positive samples; and the HIV-positive sampling intervals or times between consecutive samples.</p
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