Building an innovative Ethno-Geographic Information System (EGIS) to address opioid overdose disparities in Inland So Ca

建立创新的民族地理信息系统 (EGIS)，以解决内陆 So Ca 的阿片类药物过量问题

• 批准号: 10447815
• 负责人: Jennifer Leigh Syvertsen
• 金额: $ 18.93万
• 依托单位: UNIVERSITY OF CALIFORNIA RIVERSIDE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10447815
• 关键词: Address; Age; Applications Grants; Area; Attention; Black Populations; California; Cessation of life; Characteristics; Cities; Communities; Country; County; Data; Development; Disadvantaged; Emergency medical service; Environment; Epidemiology; Ethnography; Fentanyl; Foundations; Geographic Information Systems; Geography; Goals; Health Personnel; Health Services; Heroin; Incidence; Individual; Intervention; Interview; Latino Population; Location; Maps; Methods; Modeling; Native Americans; Opioid; Overdose; Overdose reduction; Pattern; Pharmaceutical Preparations; Policies; Population; Research; Resource Allocation; Resources; Risk; Rural Community; Sampling; Services; Shapes; Surface; Testing; United States; Work; analytical method; contextual factors; disadvantaged population; disparity reduction; ethnographic method; experience; health disparity; injury-related death; innovation; marginalized community; minority communities; mortality; novel; opioid epidemic; opioid overdose; opioid use; opioid user; overdose prevention; overdose risk; pill; resource guides; response; social; socioeconomic disadvantage; socioeconomics; suburb; tool; underserved community; urban area

PROJECT SUMMARY In the United States, drug overdose is the leading cause of injury-related death. Nationally, narratives of opioid overdose as a predominantly White suburban crisis tell only a partial story, overshadowing the importance of local geosocial contexts in producing overdose disparities in marginalized and underserved communities. As one example, Riverside County is California’s third-largest in population, representing a socioeconomically, racially, and geographically diverse region characterized by widespread health disparities and a shortage of healthcare providers. Overdose rates have been rising for more than a decade; nearly half of all overdoses are among non-White populations, and deaths have increased among Blacks by 30%, Native Americans by 47%, and Latinos by 52%, while 5-year average overdose rates are highest in several predominantly minority and rural communities beyond the county’s urban hub, the City of Riverside. We consider Riverside County as a “risk environment,” defined as the social and physical spaces where contextual factors interact to cluster harms among disadvantaged populations. However, the spatial characteristics of overdose risk environments are not well characterized because current spatial models lack ethnographic granularity on how structural factors shape lived experiences of opioid use. Thus, we ask: how do we better characterize opioid overdose disparities to enhance our response across diverse social geographies? The overall goal of this project is to develop an innovative Ethno-Geographic Information System (EGIS) that combines ethnography with spatial analytics to characterize opioid overdose and guide research and resource allocation to reduce overdose disparities in underserved communities. The specific aims of the project are to: 1) Develop spatially-explicit models relating epidemiologic indicators of opioid overdose (i.e., overdose mortality, EMS calls) to spatial contextual variables hypothesized to influence the risk of overdose. These models will combine to create a “risk surface” map of Riverside County and identify which aspects of spatial context are associated with opioid overdose disparities through the use of formal spatial analytical methods. 2) Examine the structural, social, and spatial contexts of overdose among a diverse sample of people who use opioids via ethnographic methods (observations, in-depth interviews, and ethnographic mapping). This work will build upon, contextualize, and reconsider the risk surface map developed in Aim 1 using on-the- ground data to explain observed opioid overdose disparities. 3) Integrate the geospatial and ethnographic data from Aims 1 and 2 to develop an Ethno-Geographic Information System (EGIS) that characterizes opioid overdose disparities to guide resource allocation and future research efforts focused on reducing disparities. Our research will provide an innovative new method, EGIS, to serve as a foundation for developing and testing community-level interventions to reduce overdose incidence and mortality in subsequent R01 grant proposals, and will provide a new tool for use by communities around the country to address opioid overdose disparities.

项目概要 在美国，药物过量是全国范围内伤害相关死亡的主要原因。 阿片类药物过量作为一场以白人为主的郊区危机只讲述了部分故事，掩盖了 当地地理社会背景对于少数群体和服务不足的地区造成用药过量差异的重要性 例如，河滨县是加州人口第三多的社区。 社会经济、种族和地理多样化的地区，其特点是广泛的健康差异 十多年来，医疗服务提供者的用药过量率一直在上升； 所有过量用药均发生在非白人群体中，黑人的死亡人数增加了 30%，原住民 美国人增加了 47%，拉丁美洲人增加了 52%，而 5 年平均用药过量率在几个国家中最高 主要是县城中心河滨市以外的少数民族和农村社区。 将河滨县视为“风险环境”，定义为与环境相关的社会和物理空间 然而，弱势群体的集群危害存在相互作用的因素。 由于当前的空间模型缺乏人种学，因此药物过量风险环境没有得到很好的表征 结构性因素如何影响阿片类药物使用的生活体验因此，我们要问：我们如何才能做得更好。 描述阿片类药物过量差异的特征，以加强我们在不同社会地理区域的反应？ 该项目的总体目标是开发一个创新的民族地理信息系统 (EGIS) 将人种学与空间分析相结合，以描述阿片类药物过量的特征并指导研究 以及资源分配，以减少服务不足社区的用药过量差异。 项目的目标是： 1) 开发与阿片类药物过量流行病学指标相关的空间明确模型（即 过量死亡率（EMS 调用）与空间背景变量相结合，用于影响过量风险。 这些模型将结合起来创建河滨县的“风险面”地图，并确定哪些方面 通过使用正式的空间分析，空间背景与阿片类药物过量差异相关 2) 检查不同人群样本中药物过量的结构、社会和空间背景。 通过人种学方法（观察、深入访谈和人种学绘图）使用阿片类药物的人。 这项工作将基于目标 1 中开发的风险面图，并对其进行背景化和重新考虑。 解释阿片类药物过量差异的地面数据 3) 整合地理空间和人种学数据。 目标 1 和 2 开发描述阿片类药物特征的民族地理信息系统 (EGIS) 药物过量差异来指导资源分配和未来研究工作的重点是减少差异。 我们的研究将提供一种创新的新方法，EGIS，作为开发和测试的基础 在随后的 R01 拨款提案中采取社区一级的干预措施来降低用药过量发生率和死亡率， 并将为全国各地的社区提供一个新工具，以解决阿片类药物过量的问题。