建模和预测美国特定年龄的药物过量死亡率
Lucas Böttcher1, Tom Chou2,3, Maria R D'Orsogna2,4
1Department of Computational Science and Philosophy, Frankfurt School of Finance and Management, 60322 Frankfurt am Main, Germany.
概括
药物过量死亡人数正在上升,主要原因是芬太尼和甲基胺. 一个年龄结构化的模型预测了过量使用的趋势,并使用集成卡尔曼波器估计了死亡率.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 公共卫生 公共卫生
背景情况:
- 美国的药物过量死亡人数在20年内增加了五倍,芬太尼和甲基胺导致了最近的激增.
- 过量死亡的特征因药物类别,年龄,性别和种族而异,并且随着时间的推移而变化,包括死亡年龄的下降.
- 了解人口层面的动态对于解决不断发展的药物过量危机至关重要.
研究的目的:
- 为药物成开发一个年龄结构化的数学模型.
- 用现实数据估计关键参数,包括死亡率和年龄分布.
- 预测美国未来的过量使用趋势.
主要方法:
- 对药物成动态的年龄结构模型的开发.
- 增强组合卡尔曼波器 (EnKF) 的应用用于参数估计.
- 利用1999年至2020年的美国过量使用死亡数据进行模型校准和预测.
主要成果:
- 该模型与合成数据相结合,成功估计了死亡率和年龄分布参数.
- EnKF方法将模型与观察数据集成在一起,以预测过量趋势.
- 参数估计和趋势预测是使用1999-2020年美国过量剂量数据实现的.
结论:
- 开发的年龄结构模型和EnKF方法论为药物过量死亡率动态提供了宝贵的见解.
- 该方法可以有效预测过量使用趋势,并估计关键流行病学参数.
- 这一框架可以为旨在减轻药物过量影响的公共卫生战略提供信息.
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