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Modeling and forecasting age-specific drug overdose mortality in the United States
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 dru...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132445/ https://www.ncbi.nlm.nih.gov/pubmed/37359186 http://dx.doi.org/10.1140/epjs/s11734-023-00801-z |
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author | Böttcher, Lucas Chou, Tom D’Orsogna, Maria R. |
author_facet | Böttcher, Lucas Chou, Tom D’Orsogna, Maria R. |
author_sort | Böttcher, Lucas |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10132445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-101324452023-04-27 Modeling and forecasting age-specific drug overdose mortality in the United States Böttcher, Lucas Chou, Tom D’Orsogna, Maria R. Eur Phys J Spec Top Regular Article 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. Springer Berlin Heidelberg 2023-04-26 /pmc/articles/PMC10132445/ /pubmed/37359186 http://dx.doi.org/10.1140/epjs/s11734-023-00801-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Regular Article Böttcher, Lucas Chou, Tom D’Orsogna, Maria R. Modeling and forecasting age-specific drug overdose mortality in the United States |
title | Modeling and forecasting age-specific drug overdose mortality in the United States |
title_full | Modeling and forecasting age-specific drug overdose mortality in the United States |
title_fullStr | Modeling and forecasting age-specific drug overdose mortality in the United States |
title_full_unstemmed | Modeling and forecasting age-specific drug overdose mortality in the United States |
title_short | Modeling and forecasting age-specific drug overdose mortality in the United States |
title_sort | modeling and forecasting age-specific drug overdose mortality in the united states |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132445/ https://www.ncbi.nlm.nih.gov/pubmed/37359186 http://dx.doi.org/10.1140/epjs/s11734-023-00801-z |
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