Estimated HIV incidence in the United States, 2006-2009.
TL;DR: Overall, HIV incidence in the United States was relatively stable 2006–2009; however, among young MSM, particularly black/African American MSM, incidence increased and expanded, improved, and targeted prevention is necessary to reduce HIV incidence.
Abstract: Background
The estimated number of new HIV infections in the United States reflects the leading edge of the epidemic. Previously, CDC estimated HIV incidence in the United States in 2006 as 56,300 (95% CI: 48,200–64,500). We updated the 2006 estimate and calculated incidence for 2007–2009 using improved methodology.
Methodology
We estimated incidence using incidence surveillance data from 16 states and 2 cities and a modification of our previously described stratified extrapolation method based on a sample survey approach with multiple imputation, stratification, and extrapolation to account for missing data and heterogeneity of HIV testing behavior among population groups.
Principal Findings
Estimated HIV incidence among persons aged 13 years and older was 48,600 (95% CI: 42,400–54,700) in 2006, 56,000 (95% CI: 49,100–62,900) in 2007, 47,800 (95% CI: 41,800–53,800) in 2008 and 48,100 (95% CI: 42,200–54,000) in 2009. From 2006 to 2009 incidence did not change significantly overall or among specific race/ethnicity or risk groups. However, there was a 21% (95% CI:1.9%–39.8%; p = 0.017) increase in incidence for people aged 13–29 years, driven by a 34% (95% CI: 8.4%–60.4%) increase in young men who have sex with men (MSM). There was a 48% increase among young black/African American MSM (12.3%–83.0%; p<0.001). Among people aged 13–29, only MSM experienced significant increases in incidence, and among 13–29 year-old MSM, incidence increased significantly among young, black/African American MSM. In 2009, MSM accounted for 61% of new infections, heterosexual contact 27%, injection drug use (IDU) 9%, and MSM/IDU 3%.
Conclusions/Significance
Overall, HIV incidence in the United States was relatively stable 2006–2009; however, among young MSM, particularly black/African American MSM, incidence increased. HIV continues to be a major public health burden, disproportionately affecting several populations in the United States, especially MSM and racial and ethnic minorities. Expanded, improved, and targeted prevention is necessary to reduce HIV incidence.
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TL;DR: Sexually transmitted infections are common in the United States, with a disproportionate burden among young adolescents and adults, and public health efforts should focus on prevention among at-risk populations to reduce the number and impact of STIs.
Abstract: BackgroundMost sexually active people will be infected with a sexually transmitted infection (STI) at some point in their lives. The number of STIs in the United States was previously estimated in 2000. We updated previous estimates to reflect the number of STIs for calendar year 2008.MethodsWe revi
1,179 citations
Cites background or methods from "Estimated HIV incidence in the Unit..."
...Of these, an estimated 41,400 incident HIV infections were attributed to sexual transmission (26,900 to male-to-male sexual contact and 14,500 to heterosexual contact).(29) Among black/African American, Hispanic/Latino, and white males, an estimated 30,100 incident HIV infections were attributed to male-to-male sexual contact and heterosexual contact....
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...HIV incidence was estimated using a stratified extrapolation approach based on concepts borrowed from sample survey methodology; details are described elsewhere.(29,31,32) Incidence estimates were adjusted to account for reporting delay, but not incomplete reporting....
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...Overall, these 3 racial/ethnic groups accounted for 96% (45,700/47,800) of all incident HIV infections.(29) Among persons aged 13 to 29 years, an estimated 18,600 incident HIV infections occurred in 2008; we were unable to stratify by sex or estimate infections attributed to sexual transmission for this age group....
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...New diagnoses were classified as of recent or long-standing duration based on STARHS results; information on history of HIV testing and antiretroviral use was used to classify individuals as those testing HIV positive on their first HIV test and those testing negative for HIV before HIV diagnosis.(29) Multiple imputation was used to assign a transmission category to those reported without risk information,(30) and imputed transmission category values were used to impute missing STARHS results and testing history information....
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...Estimated incidence within the 18 jurisdictions was extrapolated to the remaining US areas and the District of Columbia to obtain a population-based national HIV incidence estimate.(29) An estimated 47,800 incident HIV infections occurred in United States in 2008....
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TL;DR: For outcomes associated with HIV infection, disparities were greatest for US black MSM versus other MSM for structural barriers, sex partner demographics, and HIV care outcomes, whereas disparities were least for sexual risk outcomes.
656 citations
01 Jul 2017
TL;DR: A diagnosis-based HIV continuum monitors key steps needed for a person living with diagnosed HIV infection to reach viral suppression, which leads to improved health outcomes and reduced risk for transmission to others.
Abstract: CDC monitors progress on selected national human immunodeficiency virus (HIV) prevention and care objectives using surveillance data (1) and has released two HIV care continuums for 2014: a diagnosis-based continuum and a prevalence-based continuum (2,3). A diagnosis-based HIV continuum monitors key steps needed for a person living with diagnosed HIV infection to reach viral suppression, which leads to improved health outcomes and reduced risk for transmission to others. To determine a diagnosisbased HIV continuum, CDC uses the number of persons living with diagnosed HIV infection as the denominator. CDC monitors engagement in medical care and viral suppression in 38 jurisdictions that have complete reporting of CD4 and viral load laboratory results. Among persons living with diagnosed HIV infection at year-end 2014 in 38 jurisdictions, 73% received HIV medical care in 2014, 57% were retained in continuous care, and 58% were virally suppressed (1). Because the first step in entering HIV care is receiving a diagnosis, CDC has also estimated an HIV prevalence-based continuum, which uses the estimated number of all persons living with diagnosed or undiagnosed HIV infection as the denominator. Among the estimated 1.1 million persons living with HIV infection in the United States in 2014, 85% had received a diagnosis (1). Extrapolating from 38 jurisdictions with complete reporting, an estimated 62% of persons living with HIV infection received HIV medical care in 2014, 48% were retained in continuous care, and 49% were virally suppressed (2). More information is available in the Division of HIV/AIDS Prevention report and accompanying fact sheet and slide set (1–3).
597 citations
TL;DR: The identification of effective interventions to reduce stigma and discrimination that can be integrated into national responses is crucial to the success of the global AIDS response.
Abstract: Introduction : HIV-related stigma and discrimination continue to hamper efforts to prevent new infections and engage people in HIV treatment, care and support programmes. The identification of effective interventions to reduce stigma and discrimination that can be integrated into national responses is crucial to the success of the global AIDS response. Methods : We conducted a systematic review of studies and reports that assessed the effectiveness of interventions to reduce HIV stigma and discrimination between 1 January 2002 and 1 March 2013. Databases searched for peer-reviewed articles included PubMed, Scopus, EBSCO Host -CINAHL Plus, Psycinfo, Ovid, Sociofile and Popline. Reports were obtained from the www.HIVAIDSClearinghouse.eu , USAID Development Experience Clearinghouse, UNESCO HIV and AIDS Education Clearinghouse, Google, WHO and UNAIDS. Ancestry searches for articles included in the systematic review were also conducted. Studies of any design that sought to reduce stigma as a primary or secondary objective and included pre- and post-intervention measures of stigma were included. Results : Of 2368 peer-reviewed articles and reports identified, 48 were included in our review representing 14 different target populations in 28 countries. The majority of interventions utilized two or more strategies to reduce stigma and discrimination, and ten included structural or biomedical components. However, most interventions targeted a single socio-ecological level and a single domain of stigma. Outcome measures lacked uniformity and validity, making both interpretation and comparison of study results difficult. While the majority of studies were effective at reducing the aspects of stigma they measured, none assessed the influence of stigma or discrimination reduction on HIV-related health outcomes. Conclusions : Our review revealed considerable progress in the stigma-reduction field. However, critical challenges and gaps remain which are impeding the identification of effective stigma-reduction strategies that can be implemented by national governments on a larger scale. The development, validation, and consistent use of globally relevant scales of stigma and discrimination are a critical next step for advancing the field of research in this area. Studies comparing the effectiveness of different stigma-reduction strategies and studies assessing the influence of stigma reduction on key behavioural and biomedical outcomes are also needed to maximize biomedical prevention efforts. Keywords : systematic review; HIV; stigma reduction; discrimination reduction; interventions; measurement. (Published: 13 November 2013) To access the supplementary material to this article please see Supplementary Files in the column to the right (under Article Tools). Citation : Stangl AL et al. Journal of the International AIDS Society 2013, 16 (Suppl 2):18734 http://www.jiasociety.org/index.php/jias/article/view/18734 | http://dx.doi.org/10.7448/IAS.16.3.18734
529 citations
TL;DR: In this paper, a multistep, static, deterministic model was used to estimate the rate and number of HIV transmissions attributable to persons at each of the following 5 HIV care continuum steps: HIV infected but undiagnosed, HIV diagnosed but not retained in medical care, retained in care but not prescribed antiretroviral therapy, prescribed antirrhoehrgical therapy but not virally suppressed, and virally suppressing.
Abstract: Importance Human immunodeficiency virus (HIV) transmission risk is primarily dependent on behavior (sexual and injection drug use) and HIV viral load. National goals emphasize maximizing coverage along the HIV care continuum, but the effect on HIV prevention is unknown. Objectives To estimate the rate and number of HIV transmissions attributable to persons at each of the following 5 HIV care continuum steps: HIV infected but undiagnosed, HIV diagnosed but not retained in medical care, retained in care but not prescribed antiretroviral therapy, prescribed antiretroviral therapy but not virally suppressed, and virally suppressed. Design, Setting, and Participants A multistep, static, deterministic model that combined population denominator data from the National HIV Surveillance System with detailed clinical and behavioral data from the National HIV Behavioral Surveillance System and the Medical Monitoring Project to estimate the rate and number of transmissions along the care continuum. This analysis was conducted January 2013 to June 2014. The findings reflect the HIV-infected population in the United States in 2009. Main Outcomes and Measures Estimated rate and number of HIV transmissions. Results Of the estimated 1 148 200 persons living with HIV in 2009, there were 207 600 (18.1%) who were undiagnosed, 519 414 (45.2%) were aware of their infection but not retained in care, 47 453 (4.1%) were retained in care but not prescribed ART, 82 809 (7.2%) were prescribed ART but not virally suppressed, and 290 924 (25.3%) were virally suppressed. Persons who are HIV infected but undiagnosed (18.1% of the total HIV-infected population) and persons who are HIV diagnosed but not retained in medical care (45.2% of the population) were responsible for 91.5% (30.2% and 61.3%, respectively) of the estimated 45 000 HIV transmissions in 2009. Compared with persons who are HIV infected but undiagnosed (6.6 transmissions per 100 person-years), persons who were HIV diagnosed and not retained in medical care were 19.0% (5.3 transmissions per 100 person-years) less likely to transmit HIV, and persons who were virally suppressed were 94.0% (0.4 transmissions per 100 person-years) less likely to transmit HIV. Men, those who acquired HIV via male-to-male sexual contact, and persons 35 to 44 years old were responsible for the most HIV transmissions by sex, HIV acquisition risk category, and age group, respectively. Conclusions and Relevance Sequential steps along the HIV care continuum were associated with reduced HIV transmission rates. Improvements in HIV diagnosis and retention in care, as well as reductions in sexual and drug use risk behavior, primarily for persons undiagnosed and not receiving antiretroviral therapy, would have a substantial effect on HIV transmission in the United States.
474 citations
References
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01 Jan 1978TL;DR: In this article, the authors compare two straight line regression models and conclude that the Straight Line Regression Equation does not measure the strength of the Straight-line Relationship, but instead is a measure of the relationship between two straight lines.
Abstract: 1. CONCEPTS AND EXAMPLES OF RESEARCH. Concepts. Examples. Concluding Remarks. References. 2. CLASSIFICATION OF VARIABLES AND THE CHOICE OF ANALYSIS. Classification of Variables. Overlapping of Classification Schemes. Choice of Analysis. References. 3. BASIC STATISTICS: A REVIEW. Preview. Descriptive Statistics. Random Variables and Distributions. Sampling Distributions of t, ?O2, and F. Statistical Inference: Estimation. Statistical Inference: Hypothesis Testing. Error Rate, Power, and Sample Size. Problems. References. 4. INTRODUCTION TO REGRESSION ANALYSIS. Preview. Association versus Causality. Statistical versus Deterministic Models. Concluding Remarks. References. 5. STRAIGHT-LINE REGRESSION ANALYSIS. Preview. Regression with a Single Independent Variable. Mathematical Properties of a Straight Line. Statistical Assumptions for a Straight-line Model. Determining the Best-fitting Straight Line. Measure of the Quality of the Straight-line Fit and Estimate ?a2. Inferences About the Slope and Intercept. Interpretations of Tests for Slope and Intercept. Inferences About the Regression Line ?YY|X = ?O0 + ?O1X . Prediction of a New Value of Y at X0. Problems. References. 6. THE CORRELATION COEFFICIENT AND STRAIGHT-LINE REGRESSION ANALYSIS. Definition of r. r as a Measure of Association. The Bivariate Normal Distribution. r and the Strength of the Straight-line Relationship. What r Does Not Measure. Tests of Hypotheses and Confidence Intervals for the Correlation Coefficient. Testing for the Equality of Two Correlations. Problems. References. 7. THE ANALYSIS-OF-VARIANCE TABLE. Preview. The ANOVA Table for Straight-line Regression. Problems. 8. MULTIPLE REGRESSION ANALYSIS: GENERAL CONSIDERATIONS. Preview. Multiple Regression Models. Graphical Look at the Problem. Assumptions of Multiple Regression. Determining the Best Estimate of the Multiple Regression Equation. The ANOVA Table for Multiple Regression. Numerical Examples. Problems. References. 9. TESTING HYPOTHESES IN MULTIPLE REGRESSION. Preview. Test for Significant Overall Regression. Partial F Test. Multiple Partial F Test. Strategies for Using Partial F Tests. Tests Involving the Intercept. Problems. References. 10. CORRELATIONS: MULTIPLE, PARTIAL, AND MULTIPLE PARTIAL. Preview. Correlation Matrix. Multiple Correlation Coefficient. Relationship of RY|X1, X2, !KXk to the Multivariate Normal Distribution. Partial Correlation Coefficient. Alternative Representation of the Regression Model. Multiple Partial Correlation. Concluding Remarks. Problems. References. 11. CONFOUNDING AND INTERACTION IN REGRESSION. Preview. Overview. Interaction in Regression. Confounding in Regression. Summary and Conclusions. Problems. References. 12. DUMMY VARIABLES IN REGRESSION. Preview. Definitions. Rule for Defining Dummy Variables. Comparing Two Straight-line Regression Equations: An Example. Questions for Comparing Two Straight Lines. Methods of Comparing Two Straight Lines. Method I: Using Separate Regression Fits to Compare Two Straight Lines. Method II: Using a Single Regression Equation to Compare Two Straight Lines. Comparison of Methods I and II. Testing Strategies and Interpretation: Comparing Two Straight Lines. Other Dummy Variable Models. Comparing Four Regression Equations. Comparing Several Regression Equations Involving Two Nominal Variables. Problems. References. 13. ANALYSIS OF COVARIANCE AND OTHER METHODS FOR ADJUSTING CONTINUOUS DATA. Preview. Adjustment Problem. Analysis of Covariance. Assumption of Parallelism: A Potential Drawback. Analysis of Covariance: Several Groups and Several Covariates. Comments and Cautions. Summary Problems. Reference. 14. REGRESSION DIAGNOSTICS. Preview. Simple Approaches to Diagnosing Problems in Data. Residual Analysis: Detecting Outliers and Violations of Model Assumptions. Strategies of Analysis. Collinearity. Scaling Problems. Diagnostics Example. An Important Caution. Problems. References. 15. POLYNOMIAL REGRESSION. Preview. Polynomial Models. Least-squares Procedure for Fitting a Parabola. ANOVA Table for Second-order Polynomial Regression. Inferences Associated with Second-order Polynomial Regression. Example Requiring a Second-order Model. Fitting and Testing Higher-order Model. Lack-of-fit Tests. Orthogonal Polynomials. Strategies for Choosing a Polynomial Model. Problems. 16. SELECTING THE BEST REGRESSION EQUATION. Preview. Steps in Selecting the Best Regression Equation. Step 1: Specifying the Maximum Model. Step 2: Specifying a Criterion for Selecting a Model. Step 3: Specifying a Strategy for Selecting Variables. Step 4: Conducting the Analysis. Step 5: Evaluating Reliability with Split Samples. Example Analysis of Actual Data. Issues in Selecting the Most Valid Model. Problems. References. 17. ONE-WAY ANALYSIS OF VARIANCE. Preview. One-way ANOVA: The Problem, Assumptions, and Data Configuration. for One-way Fixed-effects ANOVA. Regression Model for Fixed-effects One-way ANOVA Fixed-effects Model for One-way ANOVA. Random-effects Model for One-way ANOVA. -comparison Procedures for Fixed-effects One-way ANOVA. a Multiple-comparison Technique. Orthogonal Contrasts and Partitioning an ANOVA Sum of Squares. Problems. References. 18. RANDOMIZED BLOCKS: SPECIAL CASE OF TWO-WAY ANOVA. Preview. Equivalent Analysis of a Matched-pairs Experiment. Principle of Blocking. Analysis of a Randomized-blocks Experiment. ANOVA Table for a Randomized-blocks Experiment. Models for a Randomized-blocks Experiment. Fixed-effects ANOVA Model for a Randomized-blocks Experiment. Problems. References. 19. TWO-WAY ANOVA WITH EQUAL CELL NUMBERS. Preview. Using a Table of Cell Means. General Methodology. F Tests for Two-way ANOVA. Regression Model for Fixed-effects Two-way ANOVA. Interactions in Two-way ANOVA. Random- and Mixed-effects Two-way ANOVA Models. Problems. References. 20. TWO-WAY ANOVA WITH UNEQUAL CELL NUMBERS. Preview. Problem with Unequal Cell Numbers: Nonorthogonality. Regression Approach for Unequal Cell Sample Sizes. Higher-way ANOVA. Problems. References. 21. THE METHOD OF MAXIMUM LIKELIHOOD. Preview. The Principle of Maximum Likelihood. Statistical Inference Using Maximum Likelihood. Summary. Problems. 22. LOGISTIC REGRESSION ANALYSIS. Preview. The Logistic Model. Estimating the Odds Ratio Using Logistic Regression. A Numerical Example of Logistic Regression. Theoretical Considerations. An Example of Conditional ML Estimation Involving Pair-matched Data with Unmatched Covariates. Summary. Problems. References. 23. POLYTOMOUS AND ORDINAL LOGISTIC REGRESSION. Preview. Why Not Use Binary Regression? An Example of Polytomous Logistic Regression: One Predictor, Three Outcome Categories. An Example: Extending the Polytomous Logistic Model to Several Predictors. Ordinal Logistic Regression: Overview. A "Simple" Hypothetical Example: Three Ordinal Categories and One Dichotomous Exposure Variable. Ordinal Logistic Regression Example Using Real Data with Four Ordinal Categories and Three Predictor Variables. Summary. Problems. References. 24. POISSON REGRESSION ANALYSIS. Preview. The Poisson Distribution. Example of Poisson Regression. Poisson Regression: General Considerations. Measures of Goodness of Fit. Continuation of Skin Cancer Data Example. A Second Illustration of Poisson Regression Analysis. Summary. Problems. References. 25. ANALYSIS OF CORRELATED DATA PART 1: THE GENERAL LINEAR MIXED MODEL. Preview. Examples. General Linear Mixed Model Approach. Example: Study of Effects of an Air Polluion Episode on FEV1 Levels. Summary!XAnalysis of Correlated Data: Part 1. Problems. References. 26. ANALYSIS OF CORRELATED DATA PART 2: RANDOM EFFECTS AND OTHER ISSUES. Preview. Random Effects Revisited. Results for Random Effects Models Applied to Air Pollution Study Data. Second Example!XAnalysis of Posture Measurement Data. Recommendations about Choice of Correlation Structure. Analysis of Data for Discrete Outcomes. Problems. References. 27. SAMPLE SIZE PLANNING FOR LINEAR AND LOGISTIC REGRESSION AND ANALYSIS OF VARIANCE. Preview. Review: Sample Size Calculations for Comparisons of Means and Proportions. Sample Size Planning for Linear Regression. Sample Size Planning for Logistic Regression. Power and Sample Size Determination for Linear Models: A General Approach. Sample Size Determination for Matched Case-control Studies with a Dichotomous Outcome. Practical Considerations and Cautions. Problems. References. Appendix A. Appendix B. Appendix C. Solutions to Exercises. Index.
9,433 citations
Journal Article•
TL;DR: The objectives of these recommendations are to increase HIV screening of patients, including pregnant women, in health-care settings; foster earlier detection of HIV infection; identify and counsel persons with unrecognized HIV infection and link them to clinical and prevention services; and further reduce perinatal transmission of HIV in the United States.
Abstract: These recommendations for human immunodeficiency virus (HIV) testing are intended for all health-care providers in the public and private sectors, including those working in hospital emergency departments, urgent care clinics, inpatient services, substance abuse treatment clinics, public health clinics, community clinics, correctional health-care facilities, and primary care settings. The recommendations address HIV testing in health-care settings only. They do not modify existing guidelines concerning HIV counseling, testing, and referral for persons at high risk for HIV who seek or receive HIV testing in nonclinical settings (e.g., community-based organizations, outreach settings, or mobile vans). The objectives of these recommendations are to increase HIV screening of patients, including pregnant women, in health-care settings; foster earlier detection of HIV infection; identify and counsel persons with unrecognized HIV infection and link them to clinical and prevention services; and further reduce perinatal transmission of HIV in the United States. These revised recommendations update previous recommendations for HIV testing in health-care settings and for screening of pregnant women (CDC. Recommendations for HIV testing services for inpatients and outpatients in acute-care hospital settings. MMWR 1993;42[No. RR-2]:1-10; CDC. Revised guidelines for HIV counseling, testing, and referral. MMWR 2001;50[No. RR-19]:1-62; and CDC. Revised recommendations for HIV screening of pregnant women. MMWR 2001;50[No. RR-19]:63-85). Major revisions from previously published guidelines are as follows: For patients in all health-care settings HIV screening is recommended for patients in all health-care settings after the patient is notified that testing will be performed unless the patient declines (opt-out screening). Persons at high risk for HIV infection should be screened for HIV at least annually. Separate written consent for HIV testing should not be required; general consent for medical care should be considered sufficient to encompass consent for HIV testing. Prevention counseling should not be required with HIV diagnostic testing or as part of HIV screening programs in health-care settings. For pregnant women HIV screening should be included in the routine panel of prenatal screening tests for all pregnant women. HIV screening is recommended after the patient is notified that testing will be performed unless the patient declines (opt-out screening). Separate written consent for HIV testing should not be required; general consent for medical care should be considered sufficient to encompass consent for HIV testing. Repeat screening in the third trimester is recommended in certain jurisdictions with elevated rates of HIV infection among pregnant women.
2,958 citations
Journal Article•
TL;DR: The Advisory Committee on Immunization Practices recommends routine vaccination of U.S. infants with 3 doses of this rotavirus vaccine administered orally at ages 2, 4, and 6 months.
Abstract: Rotavirus is the most common cause of severe gastroenteritis in infants and young children worldwide. Before initiation of the rotavirus vaccination program in the United States in 2006, approximately 80% of U.S. children had rotavirus gastroenteritis by age 5 years. Each year during the 1990s and early 2000s, rotavirus resulted in approximately 410,000 physician visits, 205,000272,000 emergency department visits, and 55,00070,000 hospitalizations among U.S. infants and children, with total annual direct and indirect costs of approximately $1 billion. In February 2006, a live, oral, human-bovine reassortant rotavirus vaccine (RotaTeq(R) [RV5]) was licensed as a 3-dose series for use among U.S. infants for the prevention of rotavirus gastroenteritis, and the Advisory Committee on Immunization Practices (ACIP) recommended routine use of RV5 among U.S. infants (CDC. Prevention of rotavirus gastroenteritis among infants and children: recommendations of the Advisory Committee on Immunization Practices [ACIP]. MMWR 2006;55[No. RR-12]). In April 2008, a live, oral, human attenuated rotavirus vaccine (Rotarix(R) [RV1]) was licensed as a 2-dose series for use among U.S. infants, and in June 2008, ACIP updated its rotavirus vaccine recommendations to include use of RV1. This report updates and replaces the 2006 ACIP statement for prevention of rotavirus gastroenteritis. ACIP recommends routine vaccination of U.S. infants with rotavirus vaccine. RV5 and RV1 differ in composition and schedule of administration. RV5 is to be administered orally in a 3-dose series, with doses administered at ages 2, 4, and 6 months. RV1 is to be administered orally in a 2-dose series, with doses administered at ages 2 and 4 months. ACIP does not express a preference for either RV5 or RV1. The recommendations in this report also address the maximum ages for doses, contraindications, precautions, and special situations for the administration of rotavirus vaccine.
1,619 citations
01 Jan 1998
1,365 citations
"Estimated HIV incidence in the Unit..." refers methods in this paper
...We also calculated the estimated annual percentage change (EAPC) in the estimated number of new HIV infections by fitting a logistic regression model to the natural logarithm of the incidence estimate using calendar year as the regressor [12]....
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TL;DR: This study provides the first direct estimates of HIV incidence in the United States using laboratory technologies previously implemented only in clinic-based settings and indicated that HIV incidence increased in the mid-1990s, then slightly declined after 1999 and has been stable thereafter.
Abstract: Context Incidence of human immunodeficiency virus (HIV) in the United States has not been directly measured. New assays that differentiate recent vs long-standing HIV infections allow improved estimation of HIV incidence. Objective To estimate HIV incidence in the United States. Design, Setting, and Patients Remnant diagnostic serum specimens from patients 13 years or older and newly diagnosed with HIV during 2006 in 22 states were tested with the BED HIV-1 capture enzyme immunoassay to classify infections as recent or long-standing. Information on HIV cases was reported to the Centers for Disease Control and Prevention through June 2007. Incidence of HIV in the 22 states during 2006 was estimated using a statistical approach with adjustment for testing frequency and extrapolated to the United States. Results were corroborated with back-calculation of HIV incidence for 1977-2006 based on HIV diagnoses from 40 states and AIDS incidence from 50 states and the District of Columbia. Main Outcome Measure Estimated HIV incidence. Results An estimated 39 400 persons were diagnosed with HIV in 2006 in the 22 states. Of 6864 diagnostic specimens tested using the BED assay, 2133 (31%) were classified as recent infections. Based on extrapolations from these data, the estimated number of new infections for the United States in 2006 was 56 300 (95% confidence interval [CI], 48 200-64 500); the estimated incidence rate was 22.8 per 100 000 population (95% CI, 19.5-26.1). Forty-five percent of infections were among black individuals and 53% among men who have sex with men. The back-calculation (n = 1.230 million HIV/AIDS cases reported by the end of 2006) yielded an estimate of 55 400 (95% CI, 50 000-60 800) new infections per year for 2003-2006 and indicated that HIV incidence increased in the mid-1990s, then slightly declined after 1999 and has been stable thereafter. Conclusions This study provides the first direct estimates of HIV incidence in the United States using laboratory technologies previously implemented only in clinic-based settings. New HIV infections in the United States remain concentrated among men who have sex with men and among black individuals.
1,317 citations
"Estimated HIV incidence in the Unit..." refers background or methods in this paper
...but within the confidence interval of that estimate [4]....
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...first national HIV incidence estimate based on a direct measure of recency of infection [4]....
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...The increase in HIV incidence in young MSM is in line with the increase seen in new diagnoses in MSM in recent years in the United States [16] and internationally [17] as well as with increases in HIV incidence seen in the United States using an extended back-calculation model [4] and with international trends in incidence in MSM [18–19]....
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...Next, an assumption of the model is that HIV testing behavior has not changed over several years [4]....
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...We previously estimated that we may have overestimated HIV incidence by as much as 7% as a result of excluding motivation from the model to calculate incidence [4]....
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