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

项目总结/摘要 淋病是美国第二大最常见的应报告疾病， 2017.认识到淋病的高患病率和抗生素耐药性的增加，2013年，美国 疾病控制和预防中心将耐药性淋病（AMR）列为三种淋病之一 美国最紧迫的感染威胁。AMR淋病的持续演变突出了 监测系统必须提供及时和准确的数据，为公共卫生战略提供信息， 对抗AMR淋病的传播。在这种情况下，重要的问题仍然是如何最好地配置 监测系统：监测点应设在何处？应检测多少分离株 风险群体中的药物敏感性，如男男性行为者，男女性行为者， 女人呢应如何在感染的解剖部位（尿道、直肠， 和/或咽部）？该提案描述了一个严格的，基于模拟模型的调查，以评估 美国AMR淋病监测策略。为了实现这一目标，我们将制定一个 淋病在美国50个人口最多的大都市地区传播的模拟模型。 该模型将允许我们列举几个性能指标，包括：1）临床有效 抗生素的使用寿命，2）药物敏感性和AMR淋病的发病率，以及3） 淋病的监测、诊断和治疗。我们将使用这个模型来预测各种 AMR淋病的监测策略对这些性能指标的影响。本研究将提供 帮助决策者确定AMR淋病监测策略的基本信息， 既具有成本效益，又有望延长抗生素的临床有效寿命。确保 成功完成这些目标，我们已经组建了一个专家团队，在淋球菌抗菌 阻力，数学和计算机模拟建模，决策科学和卫生经济学谁是 致力于共同努力，通过识别 优化AMR淋病监测的战略。

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.