Cumulative burden of Chlamydia trachomatis and Mycoplasma genitalium in the US: implications for screening guidelines and antimicrobial resistance

摘要 沙眼衣原体（CT）和支原体的发病率和卫生保健费用显著相关 生殖器（MG）感染。每一种都与男性和女性生殖道综合征有关， 对控制提出了独特的挑战。CT是美国最常报告的全国性应报告疾病。 是盆腔炎（PID）和不孕症的已知原因。尽管长期控制 计划，CT率处于历史最高水平，CT预防工作的实用性和成本效益 辩论。由于大多数CT感染是无症状的，我们目前对流行病学和 CT控制计划的有效性完全依赖于通过筛查发现病例，这只是 针对特定人群（25岁以下妇女和其他高危人群）。对CT的了解要少得多， ≥25岁的女性很少接受筛查，不建议对与以下人群发生性关系的男性进行筛查： 妇女（MSW）。我们认识上的这些主要差距限制了我们有效地针对CT预防的能力 为感染风险最高的男性和女性提供方案。MG是最近出现的病原体，负责 20-30%的男性尿道炎。没有全国性的MG监测，尽管普遍认为MG 引起男性尿道炎，但是否会引起女性后遗症还没有共识。人口有限 泌尿生殖道MG患病率的估计存在，但流行感染往往是一个贫穷的预测寿命 缺乏盆腔炎和不孕症的经验，只能部分了解人群水平的流行病学。 MG的抗菌素耐药性（AMR）正在迅速扩大- MG是CDC 2019年 AMR威胁的观察列表-但AMR流行率估计来自高风险STD诊所人群 而且没有全国性的代表性数据。更好地了解艾滋病的人群流行病学 CT和MG对于改善各自的控制工作至关重要。为了实现这一目标，我们将进行血清流行病学调查， 2017-2018年国家健康和营养检查调查（NHANES）周期中的一项研究， CT的血清学检测，区分IgG同种型，以区分近期和远处感染，以及更多 敏感性和特异性的血清学检测MG。我们亦会在MG阳性人士的尿液样本中鉴定AMR 在NHANES 2017-2018。最后，我们将开发一个基于个人的CT和MG传输动力学模型。 使用这些输出，我们将（1）估计CT在美国男性中的终生患病率并描述影响因素 与男性和女性最近与过去感染相关;（2）估计血清阳性率， 美国男性和女性MG感染的相关性，确定既往MG感染与 自我报告的PID和不孕症，并估计患病率和大环内酯类和喹诺酮类耐药的相关性 （3）评估CT和MG筛查方案对生殖健康和治疗的影响 数学模型的结果。这些数据将提供关键信息，以支持或改变当前 CT筛查指南，并为MG的新生国家检测和治疗建议提供信息。

ABSTRACT Significant morbidity and health care costs are associated with Chlamydia trachomatis (CT) and Mycoplasma genitalium (MG) infections. Each is associated with male and female reproductive tract syndromes, yet each presents unique challenges for control. CT is the most commonly reported nationally notifiable condition in the US and is a known cause of pelvic inflammatory disease (PID) and infertility. Despite longstanding control programs, CT rates are at an all-time high and the utility and cost-effectiveness of CT prevention efforts are debated. As most CT infections are asymptomatic, our current understanding of the epidemiology and the effectiveness of CT control programs has depended entirely on case detection through screening, which is only targeted to select populations (women <25 years and other high risk persons). Much less is known about CT in women ≥25 who are infrequently screened, and screening is not recommended for men who have sex with women (MSW). These major gaps in our understanding have limited our ability to effectively target CT prevention programs to men and women at highest risk of infection. MG is a more recently emerged pathogen, responsible for 20-30% of male urethritis. There is no national MG surveillance and, despite general agreement that MG causes male urethritis, there is no consensus about whether it causes sequelae in women. Limited population based estimates of urogenital MG prevalence exist, yet prevalent infections are often a poor predictor of lifetime experience of PID and infertility and permit only partial understanding of population-level epidemiology. Antimicrobial resistance (AMR) in MG is rapidly expanding - MG is one of three bacteria on the CDC's 2019 Watch List of AMR threats - but AMR prevalence estimates are derived from high-risk STD clinic populations and there are no nationally representative data. A better understanding of the population-level epidemiology of CT and MG is critical to improving control efforts for each. To achieve this, we will conduct a seroepidemiologic study in the National Health and Nutrition Examinations Survey (NHANES) 2017-2018 cycle, using a novel serologic assay for CT that differentiates IgG isotypes to distinguish recent from distant infection, and a more sensitive and specific seroassay for MG. We will also identify AMR in urine specimens from MG-positive persons in NHANES 2017-2018. Finally, we will develop an individual-based CT and MG transmission dynamics model. Using these outputs, we will (1) estimate the lifetime prevalence of CT in US men and characterize factors associated with recent versus past infection among men and women; (2) estimate the seroprevalence and correlates of MG infection in US men and women, determine the association between prior MG infection and self-reported PID and infertility, and estimate prevalence and correlates of macrolide and quinolone resistance in MG; (3) evaluate the impact of CT and MG screening scenarios on reproductive health and treatment outcomes in mathematical models. These data will provide critical information to either support or change current CT screening guidelines, and to inform nascent national testing and treatment recommendations for MG.