Collaborative Research: Unintended Consequences of Law Enforcement Disruptions to Illicit Drug Networks

合作研究：执法中断对非法毒品网络的意外后果

• 批准号: 2144382
• 负责人: Nicholas Richardson
• 金额: $ 30.83万
• 依托单位: Research Triangle Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2144382&HistoricalAwards=false
• 关键词: Collaborative; Research; Unintended; Consequences; Law

The use of illicit substances remains an ongoing and widespread part of society, with the illegal drug market estimated to be one percent of total global trade. Although the true scale of this market is unknown because of its illicit, underground nature, the overarching US drug policy and strategy has consistently been to allocate large amounts of resources to law enforcement agencies to dismantle illicit distribution networks. The motivation for narcotics enforcement is that it imposes negative consequences on the supply side that both deter people from distributing illicit drugs and decrease the drugs’ availability to vulnerable consumers. Yet little evidence suggests the negative consequences disrupt the macro-level drug supply to an extent that alters the price of drugs, and very little is known about the meso level effects of these interdictions on violence in the broader community and drug consumers at risk of fatal overdose. Therefore, the purpose of this Disrupting Operations of Illicit Supply Networks (D-ISN) project is to utilize national integrated data to develop an understanding of the impact of law enforcement disruptions to the illicit drug supply on both public health (e.g., overdoses) and public safety (e.g., violent crime) outcomes. In order to understand the relationship between drug market disruptions and outcomes of interest, the study team will construct a county level dataset across 10 diverse states using three sources of administrative data: (1) National Incident-Based Reporting System (NIBRS), (2) National Center for Health Statistics (NCHS) detailed Multiple Cause of Death (MCOD) data, and (3) the US Census. NIBRS captures characteristics of crime incidents, including detailed information on drug seizures, crime offenses, and other incident characteristics in a nationally systematic way. The MCOD data will provide unsuppressed, county-level, mortality information based on death certificates and include information on cause, decedent demographics, month of death, and county urbanicity. Data from the Census will be used to calculate rates of drug seizures and control for county level population characteristics and resource deprivation. The county-level integrated dataset will include the date of overdoses (by type of drug), public safety events (e.g., murder/nonnegligent manslaughter, robbery, and aggravated assault), and the county where the outcomes occurred. The study team will employ methods of spatial temporal causal modeling, which allows for the modeling of causal relationships between time- and space-persistent features. Lastly, the integrated datasets will be shared with researchers interested in utilizing these data with information on the data integration process, how to access the data, and how to customize it to fit the needs of their research. The team will also engage with relevant stakeholders to identify or create strategies that may mitigate the unintended consequences of drug market disruptions (e.g., reduce overdoses and community violence), reduce disparities in these outcomes in communities of color, inform local and state law enforcement drug interdiction strategies, and inform the allocation of resources for drug interdiction.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非法药物的使用仍然是社会中持续而广泛的一部分，非法药物市场估计占全球贸易总额的百分之一，尽管由于其非法、地下性质，该市场的真实规模尚不清楚，但美国最主要的毒品。政策和战略一贯是向执法机构分配大量资源，以摧毁非法毒品销售网络。禁毒执法的动机是它对供应方造成负面影响，既阻止人们分销非法毒品，又减少毒品销售。然而，几乎没有证据表明这些药物对宏观层面的药物供应造成了破坏，从而改变了药物的价格，而且人们对这些禁令对更广泛的暴力行为的中观影响知之甚少。因此，扰乱非法供应网络运作 (D-ISN) 项目的目的是利用国家综合数据来了解执法中断对非法药物供应的影响。无论是对公共卫生（例如，用药过量）和公共安全（例如，暴力犯罪）结果 为了了解毒品市场混乱与感兴趣的结果之间的关系，研究小组将使用三个来源的行政数据构建跨 10 个不同州的县级数据集。 ：(1) 国家基于事件的报告系统 (NIBRS)，(2) 国家卫生统计中心 (NCHS) 详细的多因死亡 (MCOD) 数据，以及 (3) 美国人口普查数据。犯罪事件的特征，包括以全国系统方式查获毒品、犯罪行为和其他事件特征的详细信息。 MCOD 数据将提供基于死亡证明的不受抑制的县级死亡信息，并包括死因、死者人口统计信息。 、死亡月份和县城市化数据将用于计算县级人口特征和资源匮乏的毒品缉获率和控制率。县级综合数据集将包括用药过量的日期（按类型）。毒品）、公共安全事件（例如谋杀/过失杀人、抢劫和严重攻击）以及结果发生的县。研究团队将采用时空因果建模方法，从而对因果关系进行建模。最后，集成数据集将与有兴趣利用这些数据的研究人员共享，并提供有关数据集成过程、如何访问数据以及如何定制数据以满足其研究需求的信息。 。这团队还将与相关利益攸关方合作，确定或制定战略，以减轻毒品市场混乱的意外后果（例如减少用药过量和社区暴力），减少有色人种社区中这些结果的差异，为地方和州执法部门禁毒提供信息该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。