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: 10302741
• 负责人: Jennifer Leigh Syvertsen
• 金额: $ 23.29万
• 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 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10302741
• 关键词: Address; Age; Applications Grants; Area; Attention; 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; Location; Maps; Methods; Modeling; Native Americans; Opioid; Overdose; Pattern; Pharmaceutical Preparations; Policies; Population; Research; Resource Allocation; Resources; Risk; Rural Community; Sampling; Services; Shapes; Structure; Surface; Testing; United States; Work; analytical method; contextual factors; disadvantaged population; disparity reduction; ethnographic method; experience; health disparity; injury-related death; innovation; 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.

项目摘要 在美国，药物过量是伤害相关死亡的主要原因。在全国范围内， 阿片类药物过量作为一个主要的白色郊区危机只告诉一个部分的故事，掩盖了 地方地理社会背景在边缘化和服务不足人群中产生过度差异方面的重要性 社区.例如，滨江县是加州人口第三大县， 社会经济、种族和地理上多样化的地区，其特点是普遍存在健康差距 以及医疗服务提供者的短缺。十多年来，过量服用率一直在上升;近一半的人 所有的过量都是在非白人人群中，黑人的死亡人数增加了30%， 美国人为47%，拉丁美洲人为52%，而5年平均过量率在几个国家中最高。 主要是少数民族和农村社区以外的县的城市中心，城市的滨江。我们 将滨江县视为"风险环境"，定义为社会和物理空间， 各种因素相互作用，对弱势群体造成伤害。然而， 由于目前的空间模型缺乏人种学，过量用药风险环境没有得到很好的表征 结构性因素如何塑造阿片类药物使用的生活经历。因此，我们要问：我们如何更好地 描述阿片类药物过量的差异，以加强我们在不同社会地理的反应？ 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）将人种志与空间分析相结合，以描述阿片类药物过量并指导研究 和资源分配，以减少服务不足社区的过量差异。该委员会的具体目标 项目是：1）开发与阿片类药物过量的流行病学指标有关的空间明确模型（即， 过量死亡率，EMS呼叫）与假设影响过量风险的空间背景变量相关联。 这些模型将联合收割机一起创建滨江县的"风险面"地图，并确定 空间背景与阿片类药物过量的差异，通过使用正式的空间分析 方法. 2)检查结构，社会和空间背景的过量之间的不同样本的人 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。 这项工作将建立在目标1中开发的风险表面图的基础上，将其置于背景中，并重新考虑风险表面图， 基础数据来解释观察到的阿片类药物过量差异。3)整合地理空间和人种学数据 根据目标1和2，开发一个描述阿片类药物特征的民族地理信息系统（EGIS） 过度的差距，以指导资源分配和未来的研究工作侧重于减少差距。 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赠款提案中，社区一级的干预措施，以减少过量用药的发生率和死亡率， 并将提供一个新的工具，供全国各地的社区使用，以解决阿片类药物过量的差异。