The United States Heart and Lung Transplant “Social” Network. Insights from the UNOS Database

Abstract

<h3>Purpose</h3> Although the demand for donor organs increased substantially, the number of organ donors remains relatively stable. With increasing availability of large-scale data and methodologies to decode complexity, it is possible to model connected systems as networks to improve their understanding. We hypothesized that the social structure of the Heart and Lung Transplant network can be modeled as a Geographical Social Network (GSN). <h3>Methods and Materials</h3> We studied a social structure of a network constructed using data of over 150,000 donors and recipients collected by the UNOS database between 1987 and 2010 to recreate a GSN. In this weighted network, geographical regions defined by US states or Zip Codes are nodes linked by organ transplants occurring between them, involving a social relation between two individuals. We used a weighed network reconstruction, community unfolding algorithms and a geo-graph theoretical approach to reconstruct the social network of the UNOS database. <h3>Results</h3> The social structure of the UNOS-database Heart and Lung Transplant Network (Figure 1A) reveals a community organization resembling UNOS regional divisions (1B). Regional organ sharing follows scale-free characteristics (1C) Within the heart transplant network (1D), African American and Hispanic donors show least defined communities and topology suggesting disparity in the distribution and a differential effect of organ donation practices in the minority. <h3>Conclusions</h3> Our study identifies the Social Network of organ donation in the US, links link demographic factors and patterns in the context of complex networks, identify disparity and opens a new chapter in understanding organ practices through the study of Complex Networks.