Surveillance of HIV in the United States and England, Wales, and Northern Ireland
Bibliographic record
Abstract
This issue of sexually transmitted disease includes 2 important articles focused on the detection of HIV, one from the United States1 and the second from England, Wales, and Northern Ireland.2 Together, they provide a sobering account of the status of HIV among men who have sex with men (MSM) and the pervasiveness of late HIV diagnosis. The first article used data from the National Health and Nutrition Examination Survey (NHANES) on a serial cross-sectional probability sample of the US population since 1999.3 The overall prevalence of HIV in the United States based on these data was 0.4%, consistent with earlier reports.4 The authors emphasize a higher prevalence of HIV within large metropolitan areas in the United States, twice as high relative to other areas. However, perhaps the most striking aspect of the report is the extreme risk for HIV in MSM and bisexual men. HIV prevalence among MSM was 10.1% and 13.4% in large metropolitan and metropolitan fringe areas, respectively, but remained high at 7% in medium and small metropolitan/nonmetropolitan areas. In contrast, HIV prevalence among heterosexuals in the United States did not vary by urbanicity, except among heterosexuals of low socioeconomic status in whom HIV prevalence was higher in large central metropolitan and fringe metropolitan areas. The prevalence of HIV among MSM in NHANES is similar to (but slightly lower) than that reported in the National HIV Behavioral Surveillance System, likely due to use of respondent driven sampling and HIV testing among high-risk populations in the latter.5 The report underscores the very high prevalence of HIV in MSM the United States. Although certainly not surprising, the results emphasize the truly urgent need for more resources and ideas about how to stop the spread of HIV in this patently vulnerable population. In addition, it must be noted that NHANES’ methods limit use of these data for the development of public health policy to prevent HIV infection. The NHANES samples only the civilian, noninstitutionalized US population in households, de facto missing substantial proportions of the nation’s HIV among individuals institutionalized in correctional facilities and psychiatric hospitals. Although the NHANES data support prior findings on the aggregation of HIV in large metropolitan centers, it does not account for regional variations and highly variable HIV prevalence in rural areas.6 For several years, HIV prevalence in the rural South and Midwest has been higher compared with the rural Northeast and West. In addition, the most rapid growth of HIV now occurs in the Southeastern United States, where HIV-infected individuals often reside in smaller towns, especially among African American men and some African American women.6 Finally, the survey is conducted in only 15 counties each year, and although data are aggregated, variations in HIV prevalence across regions and urbanicity (as reflected in the article) cannot be overlooked and limit the degree to which the findings from this report can inform HIV testing and care programs. The article from England, Wales, and Northern Ireland focuses on HIV prevalence and care in individuals reporting heterosexual behaviors. The results derive from data obtained from the National HIV and AIDS Reporting System, which has collected information on HIV-infected individuals older than 15 years since 1992, supplemented by complementary report of CD4 cell counts at diagnosis in 81% of the study population.2 The authors noted a rise in new diagnoses of HIV from 1992 through 2006, and a large fall in new HIV diagnoses in 2011. Most (72%) of HIV cases in heterosexuals occurred in blacks, 99% of whom had migrated from abroad. Importantly, the decrease in HIV diagnoses among black African adults over time was primarily due to declines in immigration of foreign born adults and not the success of HIV prevention within the region. As reflected in the report, linkage to care and treatment has improved in the United Kingdom. However, such improvement is perhaps overshadowed by the degree to which late diagnosis remains a major problem, with 60% of new cases presenting with a CD4 count less than 350 cells/mm3 in 2011. This degree of late diagnosis likely accounts for the static short-term mortality in the region, despite overall declines in mortality due to ART.2 It should be noted that the prevalence of late diagnosis in England, Wales, and Northern Ireland is not so different from that found by the North American–AIDS Cohort Collaboration on Research and Design, which reported that 54% of participating patients from the United States and Canada presented with a CD4 count less than 350 cells/mm3 in 2007.7 Because HIV treatment now requires only 1 pill once a day, the delay in treatment emphasized by these and other results8–10 represents an especially disturbing failure to address such findings. Although not a focus in this report, the number of new HIV diagnoses among MSM in England, Wales, and Northern Ireland steadily increased over the study period and represented 50% of new cases in 2011, emphasized in other recent work by the UK research group where steady increases of HIV in MSM paralleled reports from the United States and Western Europe.11 These articles amplify our understanding of the distribution of HIV in the US and United Kingdom. However, how can we use the data they present to halt the spread of infection? In the absence of a vaccine, we have only 2 options. First, we must commit to widespread and, where appropriate, repeated HIV testing to allow prompt initiation of antiretroviral treatment (ART) for infected people. Because early ART preserves health and stops HIV transmission, maximizing treatment for individuals’ personal health as well as to prevent transmission is entirely justified and essential.12 Second, most people tested for HIV will be uninfected. Our biggest challenge is preventing those at highest risk for acquiring HIV. In recent years, we have seen the development of new behavioral tools13 and long-acting formulations of ART agents for preexposure prophylaxis, which, although still nascent, have great promise.14 These interventions, along with early ART as above, must be deployed with attention to the surveillance articles published in this issue of sexually transmitted disease. The most important purpose of this surveillance is to use the data as a baseline to monitor the interventions we deploy. Now is the time to use the data to justify the deployment of the best prevention strategies available and to make predictions about the degree of benefit possible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".