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

Large Data Spatiotemporal Modeling of Optimal Combinations of Interventions to Reduce Opioid Harm in the United States
美国减少阿片类药物危害的最佳干预措施组合的大数据时空建模
批准号:
10708823
负责人:
Magdalena Cerda
金额:
$62.9万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-30 至 2027-06-30

项目摘要

项目成果

Magdalena Cerda的其他基金

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中文摘要
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英文摘要
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?
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