Evidence map›Paper›PMID 39968293›Full record

ArticleLancet regional health. Americas2025

Association between city-level sociodemographic and health factors and the prevalence of antimicrobial-resistant gonorrhea in the US, 2000-2019: a spatial-temporal modeling study.

Jingwen Li, Rachel E Murray-Watson, Sancta B St Cyr, Yonatan H Grad, Joshua L Warren, Reza Yaesoubi

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Article in Lancet regional health. Americas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jingwen LiDepartment of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.
Rachel E Murray-WatsonDepartment of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.
Sancta B St CyrDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Yonatan H GradDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Joshua L WarrenPublic Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
Reza YaesoubiDepartment of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.

Funding

Genomics approaches to elucidating pathways to antibiotic resistance in Neisseria gonorrhoeaeR01AI132606 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Yonatan H Grad · 2017 to 2026
$3.8M
Enhancing surveillance systems to slow the spread of antimicrobial-resistant gonorrhea in the United StatesR01AI153351 · NIAID · YALE UNIVERSITY · PI YAESOUBI, REZA · 2020 to 2024
$2.1M
NIAID NIH HHS R01 AI132606NIAID NIH HHS R01 AI153351
6 · The paper itself

Abstract

Background: Evidence from the surveillance systems of antimicrobial-resistant (AMR) gonorrhea suggests substantial variation in the prevalence of AMR gonorrhea across populations. However, little is known about the extent to which the population-level demographic, socioeconomic, and health factors (e.g., population density, poverty level, or the prevalence of other sexually-transmitted diseases) are associated with the burden of AMR gonorrhea. We developed a hierarchical Bayesian spatial-temporal logistic regression model to investigate the association between multiple spatially- and temporally-varying predictors and the proportion of isolates with resistance to each one of ciprofloxacin, penicillin, and tetracycline between 2000 and 2019 in the United States (US). Methods: The model was informed by data from the Gonococcal Isolate Surveillance Project (GISP), a sentinel surveillance system to monitor trends in the AMR gonorrhea in the US. During our study period, GISP included 112,487 isolates from the first 25 symptomatic men who have been diagnosed with urethral gonorrhea each month after attending participating sexually-transmitted disease clinics in one of about 30 select cities. Findings: Among 112,487 isolates collected between 2000 and 2019, 16.5%, 13.7%, and 22.2% were resistance to ciprofloxacin, penicillin, and tetracycline. Denser populations were associated with higher prevalence of ciprofloxacin and penicillin resistance (odd ratio (OR): 1.5, 95% with credible interval: [1.29, 1.74] and 1.36 [1.22, 1.52], respectively); West was associated with higher prevalence of ciprofloxacin resistance (OR with respect to Midwest: 14.42 [2.02, 59.27]) and Southeast was associated with higher prevalence of ciprofloxacin and penicillin resistance (OR with respect to Midwest: 6.66 [1.59, 18.20] and 7.59 [2.3, 22.94]); higher prevalence of HIV was associated with higher prevalence of ciprofloxacin and tetracycline resistance (OR: 1.18 [1.01, 1.37] and 1.14 [1.02, 1.28]); and higher incidence of gonorrhea was associated with higher prevalence of tetracycline resistance (OR: 1.08 [1.05, 1.11]). Interpretation: Geographic location and certain population-level characteristics including population density and HIV prevalence could provide insight about the population-level risk of AMR gonorrhea at a county-level. These results could guide the expansion of AMR surveillance systems or access to drug susceptibility testing in areas with characteristics associated with increased prevalence of AMR gonorrhea. Funding: US National Institutes of Health.

Indexed as

Antimicrobial resistanceGonococcal isolate surveillance projectGonorrheaLogistic regressionSpatialTemporal

Identifiers

PMID39968293
PMCPMC11834109

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