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D-ISN: Evolution of Global Illicit Kidney Trade Networks: Identification, Reconstruction, and Disruption

$1,015,941FY2022ENGNSF

George Mason University, Fairfax VA

Investigators

Abstract

The objective of this Disrupting Operations of Illicit Supply Networks (D-ISN) project is to understand the complex dynamics of global illicit kidney trade networks. Kidney trafficking is significantly understudied compared to other types of trafficking networks, despite the rising concern about this type of crime in recent years. Prior evidence, however, suggests that combating kidney trafficking in one country will inevitably raise organ trafficking in other countries. In this sense, understanding the course of kidney trafficking network evolution is particularly important for effective control of illegal transplants worldwide. Thus, the end goal of the project is to provide a general framework for modeling the evolution of transnational kidney trade networks, which, in turn, enables the exploration of effective disruption strategies. The project uses 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 to 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, as well as world statistics that are publicly available from international organizations. The analytical framework that integrates these methods will be used to: 1) predict the evolution of future transnational kidney tracking networks; 2) identify common patterns and mechanisms of actions of such networks; and 3) investigate optimal strategies to disrupt the growth of such networks. The collaboration with organ trafficking and transplant tourism experts will allow the project team to fine-tune the research outputs for real-world implementation of recommended strategies. 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.

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