Large Data Spatiotemporal Modeling of Optimal Combinations of Interventions to Reduce Opioid Harm in the United States

该项目的目标是通过以下方式预防和减少美国阿片类药物造成的死亡和伤害 确定州和地方减少危害和毒品用具法律的最佳组合 降低过量服药率和其他与阿片类药物相关的危害。为此，我们将：1)对以下法律进行原创审查 在836个拥有50,000人和 联系县；2)开展一年两次的减害法和毒品执行情况调查 3)通过合并州和州的数据，创建一个广泛的国家数据集 当地减少危害和毒品用具法律；执法部门实施法律；环境管理和死亡 数据；以及关于当地减少危害资源和社会经济指标的信息；4)使用合并后的 数据集，以确定哪些州和地方法律的组合导致了 过量和相关危害；以及(5)确定哪些地方特征增强了那些有效的 政策组合。自2001年以来，美国的服药过量死亡人数增加了六倍多， 现在造成的生命损失比高血压、艾滋病和肺炎更多。州、市和县 正在通过立法减少过量使用，并投资于获得减少危害的机会，以抗击这一流行病 服务。但这些努力往往是孤立地进行的，没有考虑到不同的国家和 当地法律的相互作用或当地因素，如执法和获得减少危害服务的机会如何影响 他们的效率。该项目将通过使用大量数据和强大的分析来帮助回答这些问题 收集关于这个复杂话题的所有证据。在项目结束时，我们将能够 以下问题：州和地方减少危害和毒品用具法律的哪种组合最多 在美国有效预防和减少阿片类药物死亡和伤害？我们如何才能最好地支持 地方努力确保这些有效的组合产生最大的影响？

The goal of this project is to prevent and reduce deaths and injuries due to opioids in the United States by determining the best combination of state and local harm reduction and drug paraphernalia laws needed to reduce overdose rates and other opioid-related harms. To do this, we will: 1) conduct original review of laws on relevant harm reduction and drug paraphernalia laws in the 836 municipalities with >50,000 people and associated counties; 2) conduct biannual surveys on implementation of harm reduction laws and drug paraphernalia laws by law enforcement; 3) create an extensive national dataset by merging data on state and local harm reduction and drug paraphernalia laws; implementation of laws by law enforcement; EMS and fatality data; and information on local harm reduction resources, and socioeconomic indicators; 4) use the merged dataset to determine which combinations of state and local laws have resulted in the biggest decreases in overdoses and related harms; and (5) determine which local characteristics enhanced those effective combinations of policies. Overdose deaths in the United States increased more than six-fold since 2001, and now account for more loss of life than high blood pressure, AIDS, and pneumonia. States, cities, and counties are combating this epidemic by passing laws to reduce overdoses, and by investing in access to harm reduction services. But these efforts are often undertaken in isolation and without considering how the different state and local laws interact or how local factors like enforcement of laws and access to harm reduction services influence their effectiveness. This project will help answer those questions by using large data and powerful analytics to bring together all the evidence on this complicated topic. At the end of the project, we will be able to anwer the following questions: What combinations of state and local harm reduction and drug paraphernalia laws most effectively prevent and reduce opioid deaths and injuries in the United States? And how can we best support local efforts to ensure that those effective combinations have the greatest impact?