Faculty
Michael Fu, Naoru Koizumi (PI from GMU), Monica Gentili (co-PI from University of Louisville), Hadi El-Amine (co-PI from GMUFunding Agency
National Science FoundationYear
2022Descriptions
Organ trafficking is a lesser known yet insidious form of human trafficking that predominantly preys upon the poor and vulnerable, whose desperate conditions are illegally exploited for quick profit, often leaving them with severely debilitated health. Kidneys are by far the most traded organ, exceeding 10,000 kidneys illegally traded annually. Refugees, who are approached to sell their kidneys in exchange for passage to other countries, are the most likely “donors.”
The transnational kidney trade is complex, involving multiple nations and entities. It typically consists of relatively young and healthy, but poor, sellers/“donors”; affluent but desperate buyers; transplant service providers such as surgeons, hospitals, and labs; brokers who often provide similar services for other illicit trades; and transnational crime networks that handle various types of illegal transactions across countries. Combating organ trafficking has been compared to playing “whack-a-mole”: controlling trafficking in one country inevitably raises the prevalence of trafficking in other countries.
A new four-year National Science Foundation grant is focused on understanding how these networks work and how they evolve—critical for effectively controlling illegal transplants worldwide.
The total project funding is close to $1M, with the University of Maryland’s portion expected to be about $244K.
The project goal is to produce a general framework that models and predicts the evolution of transnational kidney trade networks and identifies their common patterns and mechanisms. This framework will enable researchers to explore effective disruption strategies.
The framework will be developed using a multidisciplinary set of methods that include novel estimation procedures based on inverse optimization, dynamic link prediction models for handling unobserved activity in the networks, and stochastic simulation models to address the numerous sources of uncertainty and allow the testing of potential intervention strategies for disruption of future network evolution. These methods will be informed by data obtained from various sources including open and dark web, online news articles across countries, and publicly available world statistics from international organizations. A collaboration with experts in organ trafficking and transplant tourism will allow the project team to fine-tune the research for real-world implementation of the recommended strategies.
In his portion of the research, Fu will be developing simulation optimization algorithms that can handle the uncertain features and complex dynamic evolution of the networks. The resulting models will enable testing of various optimal intervention strategies to disrupt network growth. He also will be considering types of interventions that can effectively curtail the course of network evolution, and will research how the framework the researchers are developing could be extended to other organ trafficking networks and illicit supply networks in general.
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