# Enhancing surveillance systems to slow the spread of antimicrobial-resistant gonorrhea in the United States

> **NIH NIH R01** · YALE UNIVERSITY · 2022 · $416,735

## Abstract

PROJECT SUMMARY/ABSTRACT
Gonorrhea is the second most common notifiable disease in the United States with 555,608 cases reported in
2017. In recognition of the high prevalence of gonorrhea and increasing antibiotic resistance, in 2013, the U.S.
Centers for Disease Control and Prevention named antimicrobial-resistant (AMR) gonorrhea among the three
most urgent infection threats in the United States. The continued evolution of AMR gonorrhea highlights the
importance of surveillance systems that provide timely and accurate data to inform public health strategies to
combat the spread of AMR gonorrhea. In this context, important questions remain on how best to configure a
surveillance system: Where should the surveillance sites be located? How many isolates should be tested for
drug susceptibility among risk groups, such as men who have sex with men, men who have sex with women,
and women? How should sampling be distributed among the anatomical sites of infection (urethra, rectum,
and/or pharynx)? This proposal describes a rigorous, simulation model-based investigation to evaluate
strategies for the surveillance of AMR gonorrhea in the United States. Toward this goal, we will develop a
simulation model of gonorrhea transmission in the 50 most populous metropolitan areas in the United States.
The model will allow us to enumerate several performance measures including: 1) the clinically-effective
lifespan of antibiotics, 2) the incidence of drug-susceptible and AMR gonorrhea, and 3) the overall cost of
surveillance, diagnosis, and treatment of gonorrhea. We will use this model to project the impact of various
strategies for the surveillance of AMR gonorrhea on these performance measures. This study will provide
essential information to help policy makers identify strategies for the surveillance of AMR gonorrhea that are
both cost-effective and expected to extend the clinically-effective lifespan of antibiotics. To ensure the
successful completion of these aims, we have assembled a team of experts in gonococcal antimicrobial
resistance, mathematical and computer simulation modeling, decision science, and health economics who are
committed to working together to slow the spread of AMR gonorrhea in the United States by identifying
strategies to optimize the surveillance of AMR gonorrhea.

## Key facts

- **NIH application ID:** 10415148
- **Project number:** 5R01AI153351-03
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Reza YAESOUBI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $416,735
- **Award type:** 5
- **Project period:** 2020-06-23 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10415148

## Citation

> US National Institutes of Health, RePORTER application 10415148, Enhancing surveillance systems to slow the spread of antimicrobial-resistant gonorrhea in the United States (5R01AI153351-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10415148. Licensed CC0.

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