{"title":"Agent-Based Modeling: an Underutilized Tool in Community Violence Research.","authors":"Jason E Goldstick, Jonathan Jay","doi":"10.1007/s40471-022-00292-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>Community violence is a serious public health problem, and generational investments are being made to address it. Agent-based models (ABMs) are computational tools that can help to optimize allocation of those investments, analogous to how computer simulation models, broadly, have informed decision making in other fields, such as infectious disease control. In this review, we describe ABMs, explain their potential role in community violence research, discuss recent studies that have applied ABMs to community violence, and point to opportunities for further progress.</p><p><strong>Recent findings: </strong>We identified three recent studies that applied ABMs to community violence research, which points to the paucity of this line of work. Each of these works leverages a major advantage of ABMs-their ability to study the natural evolution of a process governed by the actions of autonomous agents, and how that evolution changes under counterfactual conditions, such as different intervention strategies (e.g., violence interruption), and policy changes (e.g., alcohol outlet licensing policies).</p><p><strong>Summary: </strong>ABMs continue to be an underutilized tool for the study of community violence. Their increased use could add important information to help stakeholders decide between competing intervention strategies in terms of their costs and the overall resulting changes in violence rates. In addition, ABMs have value in identifying unintended changes/diffusions resulting from interventions. Regardless of the application, ABMs can only be impactful if stakeholders believe and use the information, pointing to the importance of engaging policy makers and other stakeholders in the model formulation process when possible.</p>","PeriodicalId":48527,"journal":{"name":"Current Epidemiology Reports","volume":" ","pages":"135-141"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263807/pdf/","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Epidemiology Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40471-022-00292-x","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/7/8 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Purpose of review: Community violence is a serious public health problem, and generational investments are being made to address it. Agent-based models (ABMs) are computational tools that can help to optimize allocation of those investments, analogous to how computer simulation models, broadly, have informed decision making in other fields, such as infectious disease control. In this review, we describe ABMs, explain their potential role in community violence research, discuss recent studies that have applied ABMs to community violence, and point to opportunities for further progress.
Recent findings: We identified three recent studies that applied ABMs to community violence research, which points to the paucity of this line of work. Each of these works leverages a major advantage of ABMs-their ability to study the natural evolution of a process governed by the actions of autonomous agents, and how that evolution changes under counterfactual conditions, such as different intervention strategies (e.g., violence interruption), and policy changes (e.g., alcohol outlet licensing policies).
Summary: ABMs continue to be an underutilized tool for the study of community violence. Their increased use could add important information to help stakeholders decide between competing intervention strategies in terms of their costs and the overall resulting changes in violence rates. In addition, ABMs have value in identifying unintended changes/diffusions resulting from interventions. Regardless of the application, ABMs can only be impactful if stakeholders believe and use the information, pointing to the importance of engaging policy makers and other stakeholders in the model formulation process when possible.