Complex systems simulations for intervention development: Human trafficking and conflict-related violence

用于干预开发的复杂系统模拟：人口贩运和冲突相关暴力

• 批准号: ES/V006681/1
• 负责人: Ligia Kiss
• 金额: $ 20.55万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FV006681%2F1
• 关键词: Complex; systems; simulations; intervention; development

Overview & Aim. This project will develop interdisciplinary research methods at the intersection of complex systems, violence, public health interventions, and data visualisation. We aim to evaluate the use of dynamic complex systems modeling to develop interventions for hard-to-reach populations affected by human trafficking and conflict-related violence. The project will address the following questions: What contributions can these novel methods make to the global response to human trafficking and conficlt-related violence? How can evidence-based, accessible and visually powerful complex systems models inform decision-makers working on interventions? Project Justification. Crises, population mobility, violence and exploitation cause deleterious health consequences for millions of individuals, particularly for refugees, low-wage migrant workers and victims of human trafficking [4, 8-10]. Currently, there is limited evidence on effective interventions for these marginalised groups. Scholars emphasise the causal complexity of violence and exploitation, however, most analytical approaches have erroneously assumed linear, average effects of exposures on single outcomes. Experimental approaches to test interventions are often unethical or unfeasible to implement among these hard-to-reach populations. Reductionist research methods, such as traditional epidemiological studies, dangerously oversimplify complex problems, which frequently results in wasted resources and potential harm to already vulnerable groups.Methods. We will invite experts in complexity science, violence research, public health and data visualisation to join the Complexity & Violence Research Network. This Network will jointly design a complex intervention case study that will serve as an evaluated 'proof of concept' for these methods. In brief, our methods will include the following steps:1. Literature reviews on: 1) complex systems modelling for intervention development, 2) visualising complex systems, and 3) theoretical and epistemological underpinnings of complex systems methods. 2. Joint selection and design of an intervention case study using the Network's existent research on violence and other historical data, empirical data, and theory. 3. Calibrate, visualise and iterate a complex intervention model with dynamic multi-level interactions of exposures, associated harms, and simulated counterfactuals (e.g. intervention). 4. Collaboratively validate the model and evaluate the usefulness, feasibility and ethics of using complex systems methods for intervention development. Evaluation will include Network and Stakeholder reflections and critiques during small in-person meetings and a virtual two-wave Delphi Panel of funders and intervention developers to assess overall methods and usefulness. At every phase, we will critically examine and document the methodological and epistemological contributions, short-comings and risks, and best practice for adopting these methods in interdisciplinary research groups. Outputs. To contribute to our future work and advancements in the field, we will produce:-Academic papers on: 1) the case study findings; and 2) methodological recommendations-Lay guidance on the opportunities and limitations of these methods, with the aim of supporting intervention development, evaluation and policy decisions targeting populations affected by violence, conflict and human trafficking. -A web browser accessible version of the final case study model and visualisations to allow a wide user-audience to engage and play with the model inputs to understand how incorporating dynamic and complex characteristics of a system can explain causal mechanisms and potential effects of interventions. -Articulate future research priorities and identify funding opportunities to pursue longer-term sustainability of the Network and the development of future proposals.

概述和目标。该项目将在复杂系统，暴力，公共卫生干预和数据可视化的交叉点开发跨学科的研究方法。我们的目标是评估动态复杂系统建模的使用，为受人口贩运和冲突相关暴力影响的难以接触的人群制定干预措施。该项目将解决以下问题：这些新方法可以为全球应对人口贩运和冲突相关暴力做出哪些贡献？基于证据的、可访问的和视觉强大的复杂系统模型如何为制定干预措施的决策者提供信息？项目论证。危机、人口流动、暴力和剥削对数百万人造成有害的健康后果，特别是对难民、低工资移民工人和人口贩运受害者[4，8-10]。目前，对这些边缘化群体进行有效干预的证据有限。学者们强调暴力和剥削的因果关系的复杂性，然而，大多数分析方法都错误地假设了暴露对单一结果的线性平均影响。在这些难以接触到的人群中，测试干预措施的实验性方法往往是不道德的或不可行的。还原论的研究方法，如传统的流行病学研究，危险地过度简化复杂的问题，这往往导致浪费资源和潜在的伤害已经脆弱的群体。我们将邀请复杂性科学、暴力研究、公共卫生和数据可视化方面的专家加入复杂性与暴力研究网络。该网络将共同设计一个复杂的干预案例研究，作为这些方法的评估“概念证明”。简而言之，我们的方法将包括以下步骤：1.文献综述：1）用于干预开发的复杂系统建模，2）可视化复杂系统，以及3）复杂系统方法的理论和认识论基础。2.联合选择和设计一个干预案例研究，利用网络现有的暴力研究和其他历史数据、经验数据和理论。3.校准、可视化和模拟复杂的干预模型，包括暴露、相关危害和模拟反事实（例如干预）的动态多层次交互。4.协同验证模型，并评估使用复杂系统方法进行干预开发的有用性，可行性和道德性。评估将包括网络和利益攸关方在小型面对面会议上的反思和批评，以及由资助者和干预措施制定者组成的虚拟两波德尔菲小组，以评估整体方法和效用。在每一个阶段，我们将严格审查和记录的方法和认识论的贡献，短期和风险，以及在跨学科研究小组采用这些方法的最佳实践。产出为了促进我们未来的工作和在该领域的进步，我们将产生：-学术论文：1）案例研究结果;和2）方法论阐述-对这些方法的机会和局限性的指导，目的是支持针对受暴力，冲突和人口贩运影响的人群的干预发展，评估和政策决策。最终案例研究模型和可视化的网络浏览器可访问版本，允许广大用户参与和使用模型输入，以了解如何将系统的动态和复杂特征结合起来解释因果机制和干预措施的潜在影响。- 阐明未来的研究优先事项，并确定供资机会，以实现网络的长期可持续性和制定未来的提案。

项目成果

A Bayesian Analysis of Migration Pathways using Chain Event Graphs of Agent Based Models

使用基于代理的模型的链事件图进行迁移路径的贝叶斯分析

• DOI: 10.48550/arxiv.2111.04368
• 发表时间: 2021
• 作者: Strong P