ISN2: Disrupting Human Trafficking via Needs Matching and Capacity Expansion

该奖项将通过研究如何长期有效地分配资源以瓦解人口贩运网络，为促进国家健康、繁荣和福利作出贡献。打击人口贩运的一个关键手段是，通过更好地了解住房在个人脆弱性中所起的关键作用，减少潜在受害者的供应，这在很大程度上尚未得到充分研究。为了减少面临被拐卖（或再拐卖）风险的人口，该项目提供了一个基于需求的纽约市无家可归青年患病率估计，并提供了一个基于优化的方法，以确定最有效地利用稀缺的住所和服务资源。庇护所和相关的康复服务通过减少那些有被贩运风险的人未来的脆弱性和累犯，破坏了人口贩运网络。该奖项将通过制定部署边际临时住房和服务能力的最佳政策，帮助指导长期的、具有成本效益的干预方法。项目小组的跨学科和协作性质确保这项研究的结果将产生实际影响，并在更广泛的反人口贩运研究界广泛传播。该项目为一个由运筹学、数据科学和犯罪学领域的博士生组成的多元化团队提供了一个机会，让他们共同研究一个紧迫的社会问题。该奖项将支持一种混合方法的研究方法，包括数据收集和分析模型制定，以分析减少潜在人口贩运受害者供应所需的能力。该项目将采用一种创新的“捕获-再捕获”抽样策略，以了解住房在住房不稳定、易被贩运的青年群体中的重要性。与服务提供者提供的数据一起，该项目将建立对弱势群体集体需求的基线评估。根据这一需求评估，制定了一个多维背包问题，允许随时间变化的容量扩展和分配，并纳入随机到达和停留时间。该项目确定了有限的住房容量的边际部署，以优化社会效益-成本比。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award will contribute to the advancement of national health, prosperity and welfare by studying the efficient allocation of resources over time to disrupt human trafficking networks. A key, and largely understudied, means to disrupt human trafficking is by reducing the supply of potential victims through a better understanding of the critical role that housing plays in individual vulnerability. In order to reduce the population at risk of being trafficked (or re-trafficked), this project provides a need-based prevalence estimation of homeless youth in New York City and an optimization-based approach to determine the most efficient use of scarce shelter and service resources. Shelter and associated rehabilitative services disrupt human trafficking networks by decreasing future vulnerability and recidivism for those at-risk of trafficking. This award will help guide a long-term, cost-effective intervention approach by developing an optimal policy for deployment of marginal temporal housing and services capacity. The interdisciplinary and collaborative nature of the project team ensures that the results of this research will have a practical impact and be disseminated widely within the broader anti-human trafficking research community. The project provides an opportunity for a diverse team of doctoral students in operations research, data science, and criminology to work together on a pressing societal problem. This award will support a mixed-methods research approach that involves both data collection and analytical model formulation to analyze capacity needed to reduce the supply of potential human trafficking victims. The project will employ an innovative capture-recapture sampling strategy to understand the importance of shelter in a population of unstably housed youth at high risk for trafficking. Together with data from their service providers, the project will establish a baseline assessment of the collective needs of vulnerable populations. With this needs assessment, a multiple multidimensional knapsack problem is formulated that allows for time-dependent capacity expansion and allocation and incorporates stochastic arrivals and length of stay. The project determines the marginal deployment of limited shelter capacity to optimize the societal benefit-to-cost ratio.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.