Incident and Prevalent HIV Infections Attributed to Sexual Transmission in the United States, 2018.

BACKGROUND: The Ending the HIV Epidemic: A Plan for America initiative aims to reduce new infections by 2030. Routine assessment of incident and prevalent HIV by transmission risk is essential for monitoring the impact of national, state, and local efforts to end the HIV epidemic. METHODS: Data reported to the National HIV Surveillance System were used to estimate numbers of incident and prevalent HIV infection attributed to sexual transmission in the United States in 2018. The first CD4 result after diagnosis and a CD4 depletion model were used to generate estimates by transmission category, sex at birth, age group, and race/ethnicity. RESULTS: In 2018, there were an estimated 32,600 (50% confidence interval [CI], 31,800-33,400) incident and 984,000 (50% CI, 977,000-990,900) prevalent HIV infections attributed to sexual transmission in the United States. Male-to-male sexual contact comprised 74.8% and 69.1% of incident and prevalent HIV infections, respectively. Persons aged 25 to 34 years comprised 39.6% (12,900; 50% CI, 12,400-13,400) of incident infections; however, the number of prevalent infections was highest among persons 55 years and older (29.3%; 288,300 [50% CI, 285,600-291,000]). There were racial/ethnic differences in numbers of incident and prevalent infections among both men who have sex with men and persons with HIV attributable to heterosexual contact. CONCLUSIONS: In 2018, most incident sexually transmitted HIV infections occurred in men who have sex with men, and the burden was disproportionate for persons aged 24 to 35 years, and Black/African American and Hispanic/Latino adults and adolescents. Efforts to increase the use of effective biomedical and behavioral prevention methods must be intensified to reach the goal to end the HIV epidemic in the United States.

The Estimated Number and Lifetime Medical Cost of HIV Infections Attributable to Sexually Transmitted Infections Acquired in the United States in 2018: A Compilation of Published Modeling Results.

BACKGROUND: The purpose of this study was to estimate the number and lifetime medical cost of HIV infections attributable to incident sexually transmitted infections (STIs) in the United States in 2018. METHODS: We combined data from published models regarding the number or percentage of HIV infections attributable to STIs with updated estimates of the lifetime medical cost per HIV infection. We used 2 distinct calculation methods. Our first calculation used recent estimates of the percentage of HIV infections in men who have sex with men (MSM) attributable to gonorrhea and chlamydia. Our second calculation, based on older studies, used estimates of the expected number of STI-attributable HIV infections per new STI infection, for gonorrhea, chlamydia, syphilis, and trichomoniasis. RESULTS: Our first calculation method suggested that 2489 (25th-75th percentiles, 1895-3000) HIV infections in 2018 among MSM could be attributed to gonorrhea and chlamydia, at an estimated lifetime medical cost of $1.05 billion (25th-75th percentiles, $0.79-$1.26 billion). Our second calculation method suggested that 2349 (25th-75th percentiles, 1948-2744) HIV infections in the general population (including MSM) could be attributed to chlamydia, gonorrhea, syphilis, and trichomoniasis acquired in 2018, at an estimated lifetime medical cost of $0.99 billion (25th-75th percentiles, $0.80-$1.16 billion). CONCLUSIONS: Despite ambiguity regarding the degree to which STIs affect HIV transmission, our combination of data from published STI/HIV transmission models and an HIV lifetime medical cost model can help to quantify the estimated burden of STI-attributable HIV infections in the United States.

Sexually Transmitted Infections Among US Women and Men: Prevalence and Incidence Estimates, 2018.

BACKGROUND: The most recent estimates of the number of prevalent and incident sexually transmitted infections (STIs) in the United States were for 2008. We provide updated estimates for 2018 using new methods. METHODS: We estimated the total number of prevalent and incident infections in the United States for 8 STIs: chlamydia, gonorrhea, trichomoniasis, syphilis, genital herpes, human papillomavirus, sexually transmitted hepatitis B, and sexually transmitted HIV. Updated per-capita prevalence and incidence estimates for each STI were multiplied by the 2018 full resident population estimates to calculate the number of prevalent and incident infections. STI-specific estimates were combined to generate estimates of the total number of prevalent and incident STIs overall, and by sex and age group. Primary estimates are represented by medians, and uncertainty intervals are represented by the 25th (Q1) and 75th (Q3) percentiles of the empirical frequency distributions of prevalence and incidence for each STI. RESULTS: In 2018, there were an estimated 67.6 (Q1, 66.6; Q3, 68.7) million prevalent and 26.2 (Q1, 24.0; Q3, 28.7) million incident STIs in the United States. Chlamydia, trichomoniasis, genital herpes, and human papillomavirus comprised 97.6% of all prevalent and 93.1% of all incident STIs. Persons aged 15 to 24 years comprised 18.6% (12.6 million) of all prevalent infections; however, they comprised 45.5% (11.9 million) of all incident infections. CONCLUSIONS: The burden of STIs in the United States is high. Almost half of incident STIs occurred in persons aged 15 to 24 years in 2018. Focusing on this population should be considered essential for national STI prevention efforts.

A Surveillance Data-Based Model System for Assessing the Effects of HIV Intervention and Prevention Strategies.

OBJECTIVE: Build a dynamic model system to assess the effects of HIV intervention and prevention strategies on future annual numbers of new HIV infections, newly diagnosed cases of HIV infection, and deaths among persons infected with HIV. DESIGN AND SETTING: Model parameters are defined to quantify the putative effects of HIV prevention strategies that would increase HIV testing, thereby diagnosing infection earlier; increase linkage to care and viral suppression, thereby reducing infectiousness; and increase the use of preexposure prophylaxis, thereby protecting persons at risk of infection. Surveillance data are used to determine the initial values of the model system's variables and parameters, and the impact on the future course of various outcome measures of achieving either specified target values or specified rates of change for the model parameters is examined. PARTICIPANTS: A hypothetical population of persons with HIV infection and persons at risk of acquiring HIV infection. MAIN OUTCOME MEASURES: HIV incidence, HIV prevalence, proportion of persons infected with HIV whose infection is diagnosed, and proportion of persons with diagnosed HIV infection who are virally suppressed. RESULTS: A model system based on the basic year-to-year algebraic relationships among the model variables and relying almost exclusively on HIV surveillance data was developed to project the course of HIV disease over a specified time period. Based on the most recent HIV surveillance data in the United States-which show a relatively high proportion of infections having been diagnosed but a relatively low proportion of diagnosed persons being virally suppressed-increasing the proportion of diagnosed persons who are virally suppressed and increasing preexposure prophylaxis use appear to be the most effective ways of reducing new HIV infections and accomplishing national HIV prevention and care goals. CONCLUSIONS: Both having current and accurate information regarding the epidemiologic dynamics of HIV infection and knowing the potential impact of prevention strategies are critical in order for limited HIV prevention resources to be optimally allocated.

An Innovative Approach to Assess Similarity Between Sex Partners.

We present a simple, comprehensive method for assessing similarity between sex partners of a participant and demonstrate its application using data collected in 2015 as part of CDC's National HIV behavioral surveillance (NHBS) among persons who inject drugs (PWID). We found that the pairwise similarity between sex partners of a survey participant was high. The similarity between second-to-last and third-to-last partners in the past 3 months was significantly higher than that between last and second-to-last partner in partner type, frequency of sex acts, and the contextual characteristics of sex behavior at last sexual encounter. The proposed approach provides an innovative measure of the added value of multi-partner series. The empirical analysis suggests that querying additional sex partners contributes limited data to characterize a participant's sexual behaviors among NHBS PWID. Future studies should apply the proposed method to evaluate the added value of data on multiple sex partners among other populations.

HIV Incidence, Prevalence, and Undiagnosed Infections in U.S. Men Who Have Sex With Men.

Background: HIV infection is a persistent health concern in the United States, and men who have sex with men (MSM) continue to be the most affected population. Objective: To estimate HIV incidence and prevalence and the percentage of undiagnosed HIV infections overall and among MSM. Design: Cross-sectional analysis. Setting: National HIV Surveillance System. Participants: Persons aged 13 years or older with diagnosed HIV infection. Measurements: Data on HIV diagnoses and the first CD4 test result after diagnosis were used to model HIV incidence and prevalence and the percentage of undiagnosed HIV infections from 2008 to 2015 on the basis of a well-characterized CD4 depletion model. Results: Modeled HIV incidence decreased 14.8% overall, from 45 200 infections in 2008 to 38 500 in 2015, and among all transmission risk groups except MSM. The incidence of HIV increased 3.1% (95% CI, 1.6% to 4.5%) per year among Hispanic/Latino MSM (6300 infections in 2008, 7900 in 2015), decreased 2.7% (CI, -3.8% to -1.5%) per year among white MSM (8800 infections in 2008, 7100 in 2015), and remained stable among black MSM at about 10 000 infections. The incidence decreased by 3.0% (CI, -4.2% to -1.8%) per year among MSM aged 13 to 24 years and by 4.7% (CI, -6.2% to -3.1%) per year among those aged 35 to 44 years. Among MSM aged 25 to 34 years, HIV incidence increased 5.7% (CI, 4.4% to 7.0%) per year and among MSM aged 55 years and older, HIV increased 4.1% (CI, 0.8% to 7.4%). The percentage of undiagnosed HIV infections was higher among black, Hispanic/Latino, and younger MSM than white and older MSM, respectively. Limitation: Assumptions of the CD4 depletion model and variability of CD4 values. Conclusion: Expansion of HIV screening to reduce undiagnosed infections and increased access to care and treatment to achieve viral suppression are critical to reduce HIV transmission. Access to prevention methods, such as condoms and preexposure prophylaxis, also is needed, particularly among MSM of color and young MSM. Primary Funding Source: None.

Vital Signs: Human Immunodeficiency Virus Testing and Diagnosis Delays - United States.

BACKGROUND: Persons unaware of their human immunodeficiency virus (HIV) infection account for approximately 40% of ongoing transmissions in the United States. Persons are unaware of their infection because of delayed HIV diagnoses that represent substantial missed opportunities to improve health outcomes and prevent HIV transmission. METHODS: Data from CDC's National HIV Surveillance System were used to estimate, among persons with HIV infection diagnosed in 2015, the median interval (and range) from infection to diagnosis (diagnosis delay), based on the first CD4 test after HIV diagnosis and a CD4 depletion model indicating disease progression and, among persons living with HIV in 2015, the percentage with undiagnosed infection. Data from CDC's National HIV Behavioral Surveillance were analyzed to determine the percentage of persons at increased risk for HIV infection who had tested in the past 12 months and who had missed opportunities for testing. RESULTS: An estimated 15% of persons living with HIV in 2015 were unaware of their infection. Among the 39,720 persons with HIV infection diagnosed in 2015, the estimated median diagnosis delay was 3.0 years (interquartile range = 0.7-7.8 years); diagnosis delay varied by race/ethnicity (from 2.2 years among whites to 4.2 years among Asians) and transmission category (from 2.0 years among females who inject drugs to 4.9 years among heterosexual males). Among persons interviewed through National HIV Behavioral Surveillance, 71% of men who have sex with men, 58% of persons who inject drugs, and 41% of heterosexual persons at increased risk for HIV infection reported testing in the past 12 months. In each risk group, at least two thirds of persons who did not have an HIV test had seen a health care provider in the past year. CONCLUSIONS: Delayed HIV diagnoses continue to be substantial for some population groups and prevent early entry to care to improve health outcomes and reduce HIV transmission to others. IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: Health care providers and others providing HIV testing can reduce HIV-related adverse health outcomes and risk for HIV transmission by implementing routine and targeted HIV testing to decrease diagnosis delays.

HIV Testing Experience Before HIV Diagnosis Among Men Who Have Sex with Men - 21 Jurisdictions, United States, 2007-2013.

Gay, bisexual, and other men who have sex with men (MSM) continue to be the population most affected by human immunodeficiency virus (HIV) in the United States. In 2014, 81% of diagnoses of HIV infection were among adult and adolescent males, and among these, 83% of infections were attributable to male-to-male sexual contact (1). Since 2006, CDC has recommended HIV testing at least annually for sexually active MSM to foster early detection of HIV infection and prevent HIV transmission (2,3). Several initiatives and strategies during the past decade have aimed to expand HIV testing among MSM to increase early diagnosis and treatment and reduce transmission. To better understand HIV testing patterns among MSM with diagnosed HIV infection, CDC analyzed data for 2007-2013 from jurisdictions conducting HIV incidence surveillance as part of CDC's National HIV Surveillance System (NHSS). Findings from this analysis suggest that increasing percentages of MSM have had a negative HIV test during the 12 months before diagnosis (48% in 2007, 56% in 2013, among those with a known date of previous negative HIV test), indicating a trend toward increased HIV testing and earlier HIV diagnosis among persons most at risk for HIV.

A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates.

Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA.

Prevalence of Diagnosed and Undiagnosed HIV Infection--United States, 2008-2012.

Persons unaware of their human immunodeficiency virus (HIV) infection contribute nearly one third of ongoing transmission in the United States. Among the estimated 1.2 million persons living with HIV in the United States in 2011, 14% had undiagnosed infections. To accelerate progress toward reducing undiagnosed HIV infection, CDC and its partners have pursued an approach that includes expanding HIV testing in communities with high HIV infection rates. To measure the prevalence of diagnosed and undiagnosed HIV infection for the 50 states and the District of Columbia (DC), CDC analyzed data from the National HIV Surveillance System. In 42 jurisdictions with numerically stable estimates, HIV prevalence in 2012 ranged from 110 per 100,000 persons (Iowa) to 3,936 per 100,000 (DC). The percentage of persons living with diagnosed HIV ranged from 77% in Louisiana to ≥90% in Colorado, Connecticut, Delaware, Hawaii, and New York. In 39 jurisdictions with numerically stable estimates, the percentage of HIV cases with diagnosed infection among men who have sex with men (MSM) ranged from 75% in Louisiana to ≥90% in Hawaii and New York. These data demonstrate the need for interventions and public health strategies to reduce the prevalence of undiagnosed HIV infection. Because the percentage of persons with undiagnosed HIV varies by geographic area, efforts tailored to each area's unique circumstances might be needed to increase the percentage of persons aware of their infection.

Vital Signs: HIV diagnosis, care, and treatment among persons living with HIV--United States, 2011.

In the United States, an estimated 1.2 million persons are living with human immunodeficiency virus (HIV), a serious infection that, if untreated, leads to illness and premature death. Persons living with HIV who use antiretroviral therapy (ART) and achieve very low levels of the virus (suppressed viral load) can have a nearly normal life expectancy and have very low risk for transmitting HIV to others. However, each year in the United States, nearly 50,000 persons become infected with HIV. Each step along the HIV care continuum (HIV diagnosis, prompt and sustained HIV medical care, and ART) is essential for achieving a suppressed viral load.

Mortality Among Persons With HIV in the United States During the COVID-19 Pandemic: A Population-Level Analysis.

BACKGROUND: Whether the COVID-19 pandemic has had a disproportionate impact on mortality among persons with diagnosed HIV (PWDH) in the United States is unclear. Through our macroscale analysis, we seek to better understand how the COVID-19 pandemic affected mortality among PWDH. METHODS: We obtained mortality and population data for the years 2018-2020 from the National HIV Surveillance System for the US PWDH population and from publicly available data for the general population. We computed mortality rates and excess mortality for both the general and PWDH populations. Stratifications by age, race/ethnicity, and sex were considered. For each group, we determined whether the 2020 mortality rates and mortality risk ratio showed a statistically significant change from 2018 to 2019. RESULTS: Approximately 1550 excess deaths occurred among PWDH in 2020, with Black, Hispanic/Latino, and PWDH aged 55 years and older comprising the majority of excess deaths. Mortality rates increased in 2020 from 2018-2019 across the general population in all groups. Among PWDH, mortality rates either increased or showed no statistically significant change. These increases were similar to, or smaller than, those observed in the general population, resulting in a 7.7% decrease in the mortality risk ratio between PWDH and the general population. CONCLUSIONS: While mortality rates among PWDH increased in 2020 relative to 2018-2019, the increases were smaller, or of similar magnitude, to those observed in the general population. We thus do not find evidence of elevated mortality risk from the COVID-19 pandemic among PWDH. These findings held across subpopulations stratified by age, sex, and racial/ethnic group.

COVID-19-related excess missed HIV diagnoses in the United States in 2021.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) and related disruptions led to a significant decline in HIV diagnoses in the United States in 2020. A previous analysis estimated 18% fewer diagnoses than expected among persons with HIV (PWH) acquiring infection in 2019 or earlier, suggesting that the decline in overall diagnoses cannot be attributed solely to decreased transmission. This analysis evaluates the progress made towards closing the 2020 diagnosis deficit in 2021. METHODS: We apply previously developed methods analyzing 2021 diagnosis data from the National HIV Surveillance System to determine whether 2021 diagnosis levels of PWH infected pre-2020 are above or below the expected pre-COVID trends. Results are stratified by assigned sex at birth, transmission group, geographic region, and race/ethnicity. RESULTS: In 2021, HIV diagnoses returned to pre-COVID levels among all PWH acquiring infection 2011-2019. Among Hispanic/Latino PWH and male individuals, diagnoses returned to pre-COVID levels. White PWH, MSM, and PWH living in the south and northeast showed higher-than-expected levels of diagnosis in 2021. For the remaining populations, there were fewer HIV diagnoses in 2021 than expected. CONCLUSION: Although overall diagnoses among persons acquiring HIV pre-2020 returned to pre-COVID levels, the diagnosis gap observed in 2020 remained unclosed at the end of 2021. Fewer than expected diagnoses among certain populations indicate that COVID-19-related disruptions to HIV diagnosis trends remained in 2021. Although some groups showed higher-than-expected levels of diagnoses, such increases were smaller than corresponding 2020 decreases. Expanded testing programs designed to close these gaps are essential.

Interstate Mobility of People With Diagnosed HIV in the United States, 2011-2019.

OBJECTIVE: Assessing mobility among people with HIV is an important consideration when measuring HIV incidence, prevalence, and the care continuum in the United States. Our aims were to measure mobility among people with HIV compared with the general population and to examine factors associated with migration among people with HIV. METHODS: We calculated state-to-state move-in and move-out migration rates for 2011 through 2019 using National HIV Surveillance System data for people with HIV and using US Census data for the general population. For people with HIV, we also assessed the association between migration and HIV care outcomes. RESULTS: From 2011 through 2019, the US general population had stable migration, whereas migration rates among people with HIV fluctuated and were higher than among the general population. Among people with HIV, migration rates in 2019 were higher among people assigned male sex at birth versus female sex at birth, among people aged ≤24 years versus ≥25 years, among people with HIV infection attributed to male-to-male sexual contact versus other transmission categories, and among non-Hispanic Other people (ie, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, or multiple races) versus Hispanic, non-Hispanic Black, and non-Hispanic White people. Receipt of HIV medical care (90.3% vs 75.5%) and achieving viral suppression (72.1% vs 65.3%) were higher among people with HIV who migrated versus those who did not. CONCLUSIONS: People with HIV in the United States are more mobile than the general population. Determining the mobility of people with HIV can help with strategic allocation of HIV prevention and care resources.

Isolating the Effect of COVID-19-Related Disruptions on HIV Diagnoses in the United States in 2020.

BACKGROUND: Diagnoses of HIV in the United States decreased by 17% in 2020 due to COVID-related disruptions. The extent to which this decrease is attributable to changes in HIV testing versus HIV transmission is unclear. We seek to better understand this issue by analyzing the discrepancy in expected versus observed HIV diagnoses in 2020 among persons who acquired HIV between 2010 and 2019 because changes in diagnosis patterns in this cohort cannot be attributed to changes in transmission. METHODS: We developed 3 methods based on the CD4-depletion model to estimate excess missed diagnoses in 2020 among persons with HIV (PWH) infected from 2010 to 2019. We stratified the results by transmission group, sex assigned at birth, race/ethnicity, and region to examine differences by group and confirm the reliability of our estimates. We performed similar analyses projecting diagnoses in 2019 among PWH infected from 2010 to 2018 to evaluate the accuracy of our methods against surveillance data. RESULTS: There were approximately 3100-3300 (approximately 18%) fewer diagnoses than expected in 2020 among PWH infected from 2010 to 2019. Females (at birth), heterosexuals, persons who inject drugs, and Hispanic/Latino PWH missed diagnoses at higher levels than the overall population. Validation and stratification analyses confirmed the accuracy and reliability of our estimates. CONCLUSIONS: The substantial drop in number of previously infected PWH diagnosed in 2020 suggests that changes in testing played a substantial role in the observed decrease. Levels of missed diagnoses differed substantially across population subgroups. Increasing testing efforts and innovative strategies to reach undiagnosed PWH are needed to offset this diagnosis gap. These analyses may be used to inform future estimates of HIV transmission during the COVID-19 pandemic.

An estimate of excess deaths among people with HIV during the coronavirus disease 2019 pandemic in the United States, 2020.

We developed an ad hoc method to estimate the number of excess deaths among persons with HIV (PWH) during the coronavirus disease 2019 (COVID-19) pandemic in the United States. Using this method, we estimated approximately 1448 excess deaths from COVID-19 among PWH in 2020 in the United States. We also developed an Excel workbook for use as a tool to quickly assess excess deaths among PWH in settings with limited surveillance data.

Identifying the impact of social determinants of health on disease rates using correlation analysis of area-based summary information.

OBJECTIVES: We developed a statistical tool that brings together standard, accessible, and well-understood analytic approaches and uses area-based information and other publicly available data to identify social determinants of health (SDH) that significantly affect the morbidity of a specific disease. METHODS: We specified AIDS as the disease of interest and used data from the American Community Survey and the National HIV Surveillance System. Morbidity and socioeconomic variables in the two data systems were linked through geographic areas that can be identified in both systems. Correlation and partial correlation coefficients were used to measure the impact of socioeconomic factors on AIDS diagnosis rates in certain geographic areas. RESULTS: We developed an easily explained approach that can be used by a data analyst with access to publicly available datasets and standard statistical software to identify the impact of SDH. We found that the AIDS diagnosis rate was highly correlated with the distribution of race/ethnicity, population density, and marital status in an area. The impact of poverty, education level, and unemployment depended on other SDH variables. CONCLUSIONS: Area-based measures of socioeconomic variables can be used to identify risk factors associated with a disease of interest. When correlation analysis is used to identify risk factors, potential confounding from other variables must be taken into account.

Estimated time from HIV infection to diagnosis and diagnosis to first viral suppression during 2014-2018.

OBJECTIVE: To examine changes in the lengths of time from HIV infection to diagnosis (Infx-to-Dx) and from diagnosis to first viral suppression (Dx-to-VS), two periods during which HIV can be transmitted. DESIGN: Data from the National HIV Surveillance System (NHSS) for persons who were aged at least 13 years at the time of HIV diagnosis during 2014-2018 and resided in one of 33 United States jurisdictions with complete laboratory reporting. METHODS: The date of HIV infection was estimated based on a CD4+-depletion model. Date of HIV diagnosis, and dates and results of first CD4+ test and first viral suppression (<200 copies/ml) after diagnosis were reported to NHSS through December 2019. Trends for Infx-to-Dx and Dx-to-VS intervals were examined using estimated annual percentage change. RESULTS: During 2014-2018, among persons aged at least 13 years, 133 413 HIV diagnoses occurred. The median length of infx-to-Dx interval shortened from 43 months (2014) to 40 months (2018), a 1.5% annual decrease (7% relative change over the 5-year period). The median length of Dx-to-VS interval shortened from 7 months (2014) to 4 months (2018), an 11.4% annual decrease (42.9% relative change over the 5-year period). Infx-to-Dx intervals shortened in only some subgroups, whereas Dx-to-VS intervals shortened in all groups by sex, transmission category, race/ethnicity, age, and CD4+ count at diagnosis. CONCLUSION: The shortened Infx-to-Dx and Dx-to-VS intervals suggest progress in promoting HIV testing and earlier treatment; however, diagnosis delays continue to be substantial. Further shortening both intervals and eliminating disparities are needed to achieve Ending the HIV Epidemic goals.

Analyzing digital vector waveforms of 0-3000 Hz magnetic fields for health studies.

To improve the assessment of magnetic field exposures for occupational health studies, the Multiwave System III (MW3) was developed to capture personal exposures to the three-dimensional magnetic field vector B(t) in the 0-3000 Hz band. To process hundreds of full-shift MW3 measurements from epidemiologic studies, new computer programs were developed to calculate the magnetic field's physical properties and its interaction with biological systems through various mechanisms (magnetic induction, radical pair interactions, ion resonance, etc.). For automated calculations in the frequency domain, the software uses new algorithms that remove artifacts in the magnetic field's Fourier transform due to electronic noise and the person's motion through perturbations in the geomagnetic field from steel objects. These algorithms correctly removed the Fourier transform artifacts in 92% of samples and have improved the accuracy of frequency-dependent metrics by as much as 3300%. The output of the MwBatch software is a matrix of 41 exposure metrics calculated for each 2/15 s sample combined with 8 summary metrics for the person's full-period exposure, giving 294 summary-exposure metrics for each person monitored. In addition, the MwVisualizer software graphically explores the magnetic field's vector trace, its component waveforms, and the metrics over time. The output was validated against spreadsheet calculations with pilot data. This software successfully analyzed full-shift MW3 monitoring with 507 electric utility workers, comprising over 1 million vector waveforms. The software's output can be used to test hypotheses about magnetic field biology and disease with biophysical models and also assess compliance with exposure limits.

A passive and inclusive strategy to impute missing values of a composite categorical variable with an application to determine HIV transmission categories.

PURPOSE: Multiple imputation (MI) is a widely acceptable approach to missing data problems in epidemiological studies. Composite variables are often used to summarize information from multiple, correlated items. This study aims to assess and compare different MI methods for handling missing categorical composite variables. METHODS: We investigate the problem in the context of a real application: estimating the prevalence of HIV transmission category, which is a composite variable generated by applying a hierarchical algorithm to a group of binary risk source variables from a national program data set. We use simulation studies to compare and assess the performance of alternative MI strategies. These methods include the active imputation, just another variable, and the passive imputation approaches. RESULTS: Our study suggests that the passive imputation approach performs better than the direct imputation approach and the inclusive and general imputation model (i.e. passive imputation with interactions) performs the best. There is no need to embed the information from the variable-combining algorithm in the passive imputation modeling. CONCLUSION: We recommend practitioners adopting an inclusive and general passive imputation modeling strategy.