Estimating the population size of persons who inject drugs in New York

摘要 在美国，注射是阿片类药物和其他药物越来越常见的给药途径。 注射吸毒（IDU）行为威胁着最近在减少艾滋病毒和丙型肝炎病毒（HCV）方面取得的进展 注射毒品者中的感染，这是实现雄心勃勃的目标的一个主要障碍。 减少新的艾滋病毒感染的国家目标。在过去的十年里，纽约州经历了 阿片类药物使用障碍的比例不断上升，从而导致与注射吸毒有关的传染病增加。新 约克有强烈的政治意愿来减轻PWID中这些感染的负担，并且是美国第一个 致力于"结束艾滋病流行"和消除丙型肝炎病毒战略。然而，纽约和其他 没有一个目前的，全州范围内的估计有多少PWID需要传染病预防 服务在纽约和其他地方，需要对PWID人口规模进行可靠的估计， 稀缺资源的最佳分配，衡量PWID中风险特定的传染病负担，以及 评估预防干预措施的覆盖面。我们建议估计PWID人口规模和相关的 使用多系统估计法的纽约特定风险疾病和预防干预覆盖率 (MSE)结合现有的行政和PWID调查数据。MSE是捕获的应用程序- 重新捕获方法，允许使用观测的联合概率来估计潜在的种群规模 个人在链接的行政数据集中与他们接受服务或诊断。我们将应用MSE 方法链接，全州数据集在纽约，包括索赔数据，住院和急诊室 电子医院记录、药物治疗计划数据和传染病监测数据。我们还将 通过解决关键统计假设的潜在违规问题，提高MSE方法的严谨性， 增强估计模型，部分由研究小组目前正在收集的调查数据提供信息。 我们的具体目标是：（1）使用MSE估计纽约州的PWID人口规模， 从链接的管理数据集，整体和按地区，性别和年龄的当前IDU行为;（2）创建 精确的PWID群体大小估计值，解释了由于观察概率不相等而导致的偏倚 （3）使用标准化方法将州PWID人口规模分配给所有62个县 计算衡量传染病风险所需的关键流行病学指标 在PWID中：风险特异性HIV和HCV诊断率，注射器服务计划利用率，以及 （5）利用艾滋病和艾滋病毒/艾滋病受害者u数据传播估计数和方法 可视化平台这项工作的全国影响，以纽约为榜样，将建立一个 一种可靠的、可复制的方法，用于生成估计值，以指导改善PWID健康状况和减少 HIV和HCV在这个高风险、研究不足的群体中的负担。

ABSTRACT Injection is an increasingly common route of administration for opioids and other drugs in the U.S. Unsafe injection drug use (IDU) behavior threatens recent progress made in reducing HIV and hepatitis C virus (HCV) infections among persons who inject drugs (PWID), which is a major impediment to achieving ambitious national goals for reducing new HIV infections. During the past decade, New York State has experienced growing rates of opioid use disorder and, consequently, increases in IDU-related infectious diseases. New York has strong political will to reduce the burden of these infections among PWID and is the first U.S. state to commit to both “Ending the AIDS Epidemic” and HCV elimination strategies. However, New York, like other states, does not have a current, statewide estimate of how many PWID need infectious disease prevention services. Robust estimates of PWID population sizes are needed in New York and elsewhere to facilitate optimal allocation of scarce resources, measure risk-specific infectious disease burden among PWID, and assess coverage of prevention interventions. We propose to estimate PWID population size and associated risk-specific disease and prevention intervention coverage rates in New York using multiple systems estimation (MSE) with a combination of extant administrative and PWID survey data. MSE is an application of capture- recapture methods that allows estimation of underlying population size using joint probabilities of observing individuals in linked administrative datasets vis-à-vis their receipt of a service or diagnosis. We will apply MSE methods to linked, statewide datasets in New York including claims data, inpatient and emergency room electronic hospital records, drug treatment program data, and infectious disease surveillance data. We will also improve the rigor of MSE methods by addressing potential violations of key statistical assumptions through augmented estimation models, partially informed by survey data currently being collected by the study team. Our Specific Aims are: (1)To estimate PWID population size in New York State using MSE with indications of current IDU behavior from linked administrative datasets, overall and by region, sex, and age; (2) To create refined PWID population size estimates accounting for bias due to unequal probabilities of observing individuals in datasets; (3) To allocate state PWID population size to all 62 counties using a standardization modeling approach; (4) To compute key epidemiologic indicators needed to measure infectious disease risk among PWID: risk-specific HIV and HCV diagnosis rates, syringe service program utilization rates, and number of PWID initiating IDU during past year; (5) To disseminate estimates and methodology using the AIDSVu data visualization platform. The national impact of this work, using New York as a model, will be to establish a robust, replicable method for producing estimates that can guide efforts to improve PWID health and reduce the burden of HIV and HCV in this high-risk, under-studied group.