5 research outputs found
A Survey of Operations Research and Analytics Literature Related to Anti-Human Trafficking
Human trafficking is a compound social, economic, and human rights issue
occurring in all regions of the world. Understanding and addressing such a
complex crime requires effort from multiple domains and perspectives. As of
this writing, no systematic review exists of the Operations Research and
Analytics literature applied to the domain of human trafficking. The purpose of
this work is to fill this gap through a systematic literature review. Studies
matching our search criteria were found ranging from 2010 to March 2021. These
studies were gathered and analyzed to help answer the following three research
questions: (i) What aspects of human trafficking are being studied by
Operations Research and Analytics researchers? (ii) What Operations Research
and Analytics methods are being applied in the anti-human trafficking domain?
and (iii) What are the existing research gaps associated with (i) and (ii)? By
answering these questions, we illuminate the extent to which these topics have
been addressed in the literature, as well as inform future research
opportunities in applying analytical methods to advance the fight against human
trafficking.Comment: 28 pages, 6 Figures, 2 Table
Improving Access to Housing and Supportive Services for Runaway and Homeless Youth: Reducing Vulnerability to Human Trafficking in New York City
Recent estimates indicate that there are over 1 million runaway and homeless
youth and young adults (RHY) in the United States (US). Exposure to trauma,
violence, and substance abuse, coupled with a lack of community support
services, puts homeless youth at high risk of being exploited and trafficked.
Although access to safe housing and supportive services such as physical and
mental healthcare is an effective response to youths vulnerability towards
being trafficked, the number of youth experiencing homelessness exceeds the
capacity of available housing resources in most US communities. We undertake a
RHY-informed, systematic, and data driven approach to project the collective
capacity required by service providers to adequately meet the needs of homeless
youth in New York City, including those most at risk of being trafficked. Our
approach involves an integer linear programming model that extends the multiple
multidimensional knapsack problem and is informed by partnerships with key
stakeholders. The mathematical model allows for time-dependent allocation and
capacity expansion, while incorporating stochastic youth arrivals and length of
stays, services provided in a periodic fashion, and service delivery time
windows. Our RHY and service provider-centered approach is an important step
toward meeting the actual, rather than presumed, survival needs of vulnerable
youth, particularly those at-risk of being trafficked
On the Optimization of Benefit to Cost Ratios for Public Sector Decision Making
Decision making in the public sector centers on delivering resources and
services for the common good, emphasizing an expansive set of objectives such
as equity and efficiency, beyond immediate short term returns to reflect the
broader cares of society and public beneficiaries. Cost-benefit analysis is a
prevailing decision-making framework in the public sector that often uses the
benefit to cost ratio (BCR) to compare viable alternatives, yet no systematic
framework exists for evaluating many alternatives beyond the status quo of
doing nothing. We propose a new framework to maximize the BCR for public sector
decisions, seeking the largest improvement per marginal deployment of capacity.
Requiring a status quo representable through (constrained) decision variables,
the framework is generally applicable and useful to a broad set of decision
contexts that involve maximizing the BCR for marginal deployments of resources.
We demonstrate the applicability of our framework on a compelling case study
for the New York City runaway and homeless youth shelter system, an area of
high societal need. We represent this problem as a mixed integer linear
fractional program (MILFP) and employ Dinkelbach's algorithm that converts the
MILFP to a series of linearized mixed-integer optimization problems, making our
approach tractable for fairly large problem instances. Our optimization-based
algorithmic framework yields data-informed recommendations for making New York
City shelter expansion decisions to better serve runaway and homeless youth,
and generalizes to reveal managerial insights for optimizing the BCR. More
broadly, our algorithmic decision making framework allows for iteration and
comparison across multiple potential constraints ensuring action away from the
status quo, thereby empowering effective assessment of marginal deployment of
additional resources
Estimating Effectiveness of Identifying Human Trafficking via Data Envelopment Analysis
Transit monitoring is a preventative approach used to identify possible cases
of human trafficking while an individual is in transit or before one crosses a
border. Transit monitoring is often conducted by non-governmental organizations
(NGOs) who train staff to identify and intercept suspicious activity. Love
Justice International (LJI) is one such NGO that has been conducting transit
monitoring for 14 years along the Nepal-India border at approximately 25-30
monitoring stations. In partnership with LJI, we developed a system that uses
data envelopment analysis (DEA) to help LJI decision-makers evaluate the
performance of these stations and make specific operational improvement
recommendations. We identified efficient stations, compared rankings of station
performance, and recommended strategies to improve efficiency. To the best of
our knowledge, this is the first application of DEA in the anti-human
trafficking domain
Life and expectations post-kidney transplant: a qualitative analysis of patient responses
Abstract
Background
The effect of a kidney transplant on a recipient extends beyond the restoration of kidney function. However, there is limited qualitative analysis of recipient perspectives on life following transplantation, particularly in the United States. To understand the full patient experience, it is necessary to understand recipient views on life adjustments after kidney transplantation, medical management, and quality of life. This could lead to improvements in recipient care and sense of well-being.
Methods
We conducted a paper-based survey from March 23 to October 1, 2015 of 476 kidney transplant recipients at the University of Michigan Health System in Ann Arbor, Michigan. We analyzed their open-ended responses using qualitative research methods. This is a companion analysis to a previous quantitative report on the closed-ended responses to that survey.
Results
Common themes relating to changes following transplantation included: improvements in quality of life, a return to normalcy, better health and more energy. Concerns included: duration of graft survival, fears about one day returning to dialysis or needing to undergo another kidney transplant, comorbidities, future quality of life, and the cost and quality of their healthcare. Many recipients were grateful for their transplant, but some were anxious about the burdens transplantation placed on their loved ones.
Conclusions
While most recipients reported meaningful improvements in health and lifestyle after kidney transplantation, a minority of participants experienced declines in energy or health status. Worries about how long the transplant will function, future health, and cost and quality of healthcare are prevalent. Future research could study the effects of providing additional information, programs, and interventions following transplantation that target these concerns. This may better prepare and support kidney recipients and lead to improvements in the patient experience.https://deepblue.lib.umich.edu/bitstream/2027.42/149149/1/12882_2019_Article_1368.pd