Eric Tatara, John Schneider, Madeline Quasebarth, Nicholson Collier, Harold Pollack, Basmattee Boodram, Sam Friedman, Elizabeth Salisbury-Afshar, Mary Ellen Mackesy-Amiti, Jonathan Ozik
{"title":"应用基于分布式代理的建模来调查司法介入人群中阿片类药物的使用结果。","authors":"Eric Tatara, John Schneider, Madeline Quasebarth, Nicholson Collier, Harold Pollack, Basmattee Boodram, Sam Friedman, Elizabeth Salisbury-Afshar, Mary Ellen Mackesy-Amiti, Jonathan Ozik","doi":"10.1109/ipdpsw52791.2021.00157","DOIUrl":null,"url":null,"abstract":"<p><p>Criminal justice involved (CJI) individuals with a history of opioid use disorder (OUD) are at high risk of overdose and death in the weeks following release from jail. We developed the Justice-Community Circulation Model (JCCM) to investigate OUD/CJI dynamics post-release and the effects of interventions on overdose deaths. The JCCM uses a synthetic agent-based model population of approximately 150,000 unique individuals that is generated using demographic information collected from multiple Chicago-area studies and data sets. We use a high-performance computing (HPC) workflow to implement a sequential approximate Bayesian computation algorithm for calibrating the JCCM. The calibration results in the simulated joint posterior distribution of the JCCM input parameters. The calibrated model is used to investigate the effects of a naloxone intervention for a mass jail release. The simulation results show the degree to which a targeted intervention focusing on recently released jail inmates can help reduce the risk of death from opioid overdose.</p>","PeriodicalId":90848,"journal":{"name":"IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum : [proceedings]. IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum","volume":" ","pages":"989-997"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297575/pdf/nihms-1820884.pdf","citationCount":"0","resultStr":"{\"title\":\"Application of Distributed Agent-based Modeling to Investigate Opioid Use Outcomes in Justice Involved Populations.\",\"authors\":\"Eric Tatara, John Schneider, Madeline Quasebarth, Nicholson Collier, Harold Pollack, Basmattee Boodram, Sam Friedman, Elizabeth Salisbury-Afshar, Mary Ellen Mackesy-Amiti, Jonathan Ozik\",\"doi\":\"10.1109/ipdpsw52791.2021.00157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Criminal justice involved (CJI) individuals with a history of opioid use disorder (OUD) are at high risk of overdose and death in the weeks following release from jail. We developed the Justice-Community Circulation Model (JCCM) to investigate OUD/CJI dynamics post-release and the effects of interventions on overdose deaths. The JCCM uses a synthetic agent-based model population of approximately 150,000 unique individuals that is generated using demographic information collected from multiple Chicago-area studies and data sets. We use a high-performance computing (HPC) workflow to implement a sequential approximate Bayesian computation algorithm for calibrating the JCCM. The calibration results in the simulated joint posterior distribution of the JCCM input parameters. The calibrated model is used to investigate the effects of a naloxone intervention for a mass jail release. 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Application of Distributed Agent-based Modeling to Investigate Opioid Use Outcomes in Justice Involved Populations.
Criminal justice involved (CJI) individuals with a history of opioid use disorder (OUD) are at high risk of overdose and death in the weeks following release from jail. We developed the Justice-Community Circulation Model (JCCM) to investigate OUD/CJI dynamics post-release and the effects of interventions on overdose deaths. The JCCM uses a synthetic agent-based model population of approximately 150,000 unique individuals that is generated using demographic information collected from multiple Chicago-area studies and data sets. We use a high-performance computing (HPC) workflow to implement a sequential approximate Bayesian computation algorithm for calibrating the JCCM. The calibration results in the simulated joint posterior distribution of the JCCM input parameters. The calibrated model is used to investigate the effects of a naloxone intervention for a mass jail release. The simulation results show the degree to which a targeted intervention focusing on recently released jail inmates can help reduce the risk of death from opioid overdose.