ArticleOpen forum infectious diseases2020
Optimizing Screening for HIV.
Article in Open forum infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Systematic Review of Neighborhood Factors Impacting HIV Care Continuum Participation in the United States.Journal of urban health : bulletin of the New York Academy of Medicine · 2024Pooled it
- Dynamics and Dispersal of Local Human Immunodeficiency Virus Epidemics Within San Diego and Across the San Diego-Tijuana Border.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe HIV epidemic is unevenly distributed throughout the United States, even within neighborhoods. This study evaluated how effectively current testing approaches reached persons at risk for HIV infection across San Diego (SD) County, California.
methodsHIV case and testing data, sexually transmitted infection (STI) data, and sociodemographic data for SD County were collected from the SD Health and Human Services Agency and the "Early Test" community-based HIV screening program between 1998 and 2016. Relationships between HIV diagnoses, HIV prevalence, and STI diagnoses with screening at the ZIP code level were evaluated.
resultsOverall, 379 074 HIV tests were performed. The numbers of HIV tests performed on persons residing in a ZIP code or region overall strongly correlated with prevalent HIV cases (
conclusionsThis study supported the ability of a small number of standalone testing centers to reach at-risk populations dispersed across SD County. These methods can also be used to highlight geographic areas or demographic segments that may benefit from more intensive screening.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.