Evidence map›Paper›PMID 40526386›Full record

ArticleJAMA network open2025

Enhanced Surveillance of Sexually Transmitted Infections to Foster a Learning Public Health System.

Harry Reyes Nieva, Jason Zucker, Emma Tucker, Delivette Castor, Michael T Yin, Peter Gordon, Noémie Elhadad

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Harry Reyes NievaDepartment of Biomedical Informatics, Columbia University, New York, New York.
Jason ZuckerDepartment of Biomedical Informatics, Columbia University, New York, New York.
Emma TuckerCollege of Physicians and Surgeons, Columbia University, New York, New York.
Delivette CastorDivision of Infectious Diseases, NewYork-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York.
Michael T YinDepartment of Biomedical Informatics, Columbia University, New York, New York.
Peter GordonDivision of Infectious Diseases, NewYork-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York.
Noémie ElhadadDepartment of Biomedical Informatics, Columbia University, New York, New York.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Harnessing Bioinformatics for HIV Prevention: Understanding Persistence in Comprehensive HIV Prevention ServicesK23AI150378 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ZUCKER, JASON · 2020 to 2024
$960k
NIAID NIH HHS K23 AI150378NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Importance: Sexually transmitted infections (STIs) pose a substantial public health challenge, but fragmented reporting systems have limited capacity for disease surveillance approaches that might support a learning public health system, where near real-time data-driven insights are integrated to inform, evaluate, and adapt public health strategies. Objective: To examine how health information exchanges and open government data can be leveraged to foster a learning public health system by characterizing and comparing patterns in diagnosis vs testing at a scale commensurate with regional public health agencies. Design, Setting, and Participants: In this cross-sectional study, chlamydia, gonorrhea, and HIV testing and diagnosis between January 1, 2018, and June 30, 2023, were assessed to study concurrent testing and coinfections and estimate correlates of laboratory testing and positive results. Patient-level electronic health record data from 4 767 322 patients aged 18 years or older spanning multiple health systems in New York City and collected by the public health information exchange Healthix were linked with neighborhood-level information from the American Community Survey. Exposures: Age, sex, race and ethnicity, socioeconomic status, residential neighborhood, and concurrent STI testing. Main Outcomes and Measures: Primary outcomes were performance of a laboratory test and test positivity. The viability of using clinical data from public health information exchange to enhance disease surveillance to identify testing gaps, disparities, and important trends, key characteristics of a learning public health system was assessed. Results: The dataset included 4 767 322 patients (mean [SD] age, 46 [18] years; 61% women) with approximately 33% living in areas of high or very high poverty levels and 66% in areas of low or medium poverty levels. Among 1 519 121 tests for chlamydia, 2% were positive; among 1 574 772 tests for gonorrhea, 1% were positive; and among 1 200 560 tests for HIV, 0.3% were positive. Chlamydia and gonorrhea co-occurred in 1854 cases, representing 7% of chlamydia cases and 21% of gonorrhea cases. Testing behavior was often incongruent with geographic and sociodemographic patterns of incident cases. For example, people living in areas with the highest poverty levels were less likely to be tested for gonorrhea (adjusted odds ratio [AOR], 0.90 [95% CI, 0.89-0.91]; P < .001) but almost twice as likely to test positive for gonorrhea (AOR, 1.91 [95% CI, 1.72-2.12]; P < .001) compared with those in low poverty areas. Conclusions and Relevance: This cross-sectional study suggests that health information exchanges and open government data sources may support regional disease surveillance by contributing information not typically available through public health reporting to elucidate inefficiencies and disparities in testing given positivity and coinfection patterns. These and similar insights could be used to continuously drive public health improvements and foster a learning public health system.

Indexed as

Population SurveillancePublic HealthSexually Transmitted DiseasesAdolescentAdultChlamydia InfectionsCross-Sectional StudiesFemaleGonorrheaHIV InfectionsHumansMaleMiddle AgedNew York CityYoung Adult

Identifiers

PMID40526386
PMCPMC12175029

What OpenQuestion holds

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Registered trials

None linked

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.