Sabounchi Nasim S, Thompson Rachel L, Lootens Matthew R, Lounsbury David W, Hirsch Gary, Blevins Derek, Canty Turner C, El-Bassel Nabila, Gilbert Louisa, Mateu-Gelabert Pedro, Feaster Daniel J, Rapkin Bruce D, Huang Terry T-K
Center for Systems and Community Design, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA; Department of Health Policy and Management, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
Center for Systems and Community Design, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.
Int J Drug Policy. 2025 Aug;142:104843. doi: 10.1016/j.drugpo.2025.104843. Epub 2025 May 27.
As part of the New York HEALing Communities Study, we modeled the opioid epidemic in New York State (NYS) to help coalition members understand short- and long-term capacity-building needs and trade-offs in choosing the optimal mix of harm reduction, treatment, and prevention strategies.
We built and validated a system dynamics simulation model of the interdependent effects of exposure to opioids, opioid supply and overdose risk, community awareness of overdose risk, naloxone supply and use, and treatment for opioid use disorder (OUD). We simulated overdose and fatality rates, OUD prevalence, and related measures from 2012 to 2032 for the NYS population aged ≥12 and tested policy scenarios for reducing future overdose deaths.
Increasing naloxone distribution by 50 % led to a 10 % decrease in overdose deaths, but only minimally reduced OUD prevalence (1 %) by 2032. Enhancing by 50 % medications for OUD (MOUD) initiations and prevention efforts each led to substantial decreases in deaths (29 % and 25 %, respectively) and OUD prevalence (27 % and 6 %) by 2032. Simultaneously increasing naloxone distribution and MOUD initiations by 50 % resulted in 38 % fewer deaths, while adding prevention efforts alongside resulted in 56 % fewer fatalities. Sensitivity analyses of the models' feedback loops demonstrated similar relative impacts.
A combination of evidence-based strategies while also promoting prevention should be prioritized to reduce overdose fatality. Sustained community awareness and prevention efforts are needed even as overdoses and deaths decline due to the significant effects of the community awareness feedback loop on the epidemic trends.
作为纽约治愈社区研究的一部分，我们对纽约州的阿片类药物流行情况进行了建模，以帮助联盟成员了解短期和长期的能力建设需求，以及在选择减少伤害、治疗和预防策略的最佳组合时的权衡。
我们构建并验证了一个系统动力学模拟模型，该模型用于模拟阿片类药物暴露、阿片类药物供应和过量用药风险、社区对过量用药风险的认识、纳洛酮供应和使用以及阿片类药物使用障碍（OUD）治疗之间的相互依存效应。我们模拟了2012年至2032年纽约州12岁及以上人群的过量用药和死亡率、OUD患病率以及相关指标，并测试了减少未来过量用药死亡的政策情景。
将纳洛酮分发量增加50%可使过量用药死亡人数减少10%，但到2032年，OUD患病率仅略有降低（1%）。将用于OUD的药物（MOUD）启动量和预防工作分别提高50%，到2032年，死亡人数（分别为29%和25%）和OUD患病率（分别为27%和6%）都大幅下降。同时将纳洛酮分发量和MOUD启动量增加50%，死亡人数减少38%，而同时增加预防工作则可使死亡人数减少56%。对模型反馈回路的敏感性分析显示了类似的相对影响。
应优先采用基于证据的策略组合，并同时促进预防工作，以减少过量用药死亡。即使由于社区意识反馈回路对流行趋势的显著影响，过量用药和死亡人数有所下降，仍需要持续的社区意识和预防工作。
