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: 2145938
• 负责人: Osman Ozaltin
• 金额: $ 24.11万
• 依托单位: North Carolina State University
• 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 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145938&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持续和广泛的一部分，据估计，非法毒品市场占全球贸易总额的百分之一。尽管这个市场的真实规模因其非法、地下性质而不得而知，但美国的总体毒品政策和战略一直是向执法机构分配大量资源，以摧毁非法分销网络。禁毒执法的动机是，它对供应方造成负面后果，既阻止人们分发非法药物，又减少弱势消费者获得毒品的机会。然而，几乎没有证据表明，这些负面后果扰乱了宏观层面的毒品供应，以至于改变了药品价格，而且人们对这些禁令对更广泛社区的暴力和面临致命过量风险的毒品消费者的中观层面的影响知之甚少。因此，非法供应网络扰乱行动(D-ISN)项目的目的是利用国家综合数据，了解执法扰乱非法药物供应对公共健康(如吸毒过量)和公共安全(如暴力犯罪)结果的影响。为了了解药品市场中断和相关结果之间的关系，研究小组将使用三个行政数据来源构建一个横跨10个不同州的县级数据集：(1)基于事件的国家报告系统(NIBRS)，(2)国家卫生统计中心(NCHS)详细的多死因(MCOD)数据，以及(3)美国人口普查。NIBRS以国家系统的方式捕捉犯罪事件的特征，包括关于毒品缴获、犯罪和其他事件特征的详细信息。MCOD数据将根据死亡证明提供未受抑制的县级死亡信息，包括死因、死亡人口统计、死亡月份和县城市化信息。人口普查的数据将用于计算毒品缉获率和县级人口特征和资源匮乏的控制。县级综合数据集将包括吸毒过量的日期(按毒品类型)、公共安全事件(例如，谋杀/非过失杀人罪、抢劫和严重殴打)，以及结果发生的县。研究小组将采用时空因果建模的方法，这允许对时间和空间持久特征之间的因果关系进行建模。最后，整合后的数据集将与有兴趣利用这些数据的研究人员共享，其中包括关于数据整合过程、如何访问数据以及如何定制数据以适应其研究需要的信息。该团队还将与相关利益攸关方合作，确定或制定战略，以减轻毒品市场中断的意外后果(例如，减少过量用药和社区暴力)，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提供禁毒战略，并为禁毒资源的分配提供信息。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。