Modeling and forecasting age-specific drug overdose mortality in the United States

被引:3
|
作者
Boettcher, Lucas [1 ]
Chou, Tom [2 ,3 ]
D'Orsogna, Maria R. [2 ,4 ]
机构
[1] Frankfurt Sch Finance & Management, Dept Computat Sci & Philosophy, D-60322 Frankfurt, Germany
[2] Univ Calif Los Angeles, Dept Computat Med, Los Angeles, CA 90095 USA
[3] Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USA
[4] Calif State Univ Northridge, Dept Math, Los Angeles, CA 91330 USA
来源
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
HEROIN EPIDEMIC MODEL; MATHEMATICAL-ANALYSIS; KALMAN FILTER;
D O I
10.1140/epjs/s11734-023-00801-z
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Drug overdose deaths continue to increase in the United States for all major drug categories. Over the past two decades the total number of overdose fatalities has increased more than fivefold; since 2013 the surge in overdose rates is primarily driven by fentanyl and methamphetamines. Different drug categories and factors such as age, gender, and ethnicity are associated with different overdose mortality characteristics that may also change in time. For example, the average age at death from a drug overdose has decreased from 1940 to 1990 while the overall mortality rate has steadily increased. To provide insight into the population-level dynamics of drug overdose mortality, we develop an age-structured model for drug addiction. Using an augmented ensemble Kalman filter (EnKF), we show through a simple example how our model can be combined with synthetic observation data to estimate mortality rate and an age-distribution parameter. Finally, we use an EnKF to combine our model with observation data on overdose fatalities in the United States from 1999 to 2020 to forecast the evolution of overdose trends and estimate model parameters.
引用
收藏
页码:1743 / 1752
页数:10
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