Health Applications of Network Science and Computational Social Science

Social network analysis has proliferated rapidly across the social and behavioral sciences, with increasingly apparent implications for human health. Shifting our focus from individuals to the patterns of social ties that connect them has enriched our understanding of a great variety of health-related phenomena, including the spread of STDs on contact networks, the spread of health care practices on practitioners’ professional networks, the dynamics of patient transfers on networks of clinics, and the spread of health behaviors on adolescent friendship networks. The advent of computational social science has augmented such contributions by introducing scalable methods of automatically monitoring and rigorously modeling these phenomena. Sample applications include analysis of electronic health records and other time-stamped communication traces among health care practitioners; streams of behavioral and biometric data from wearable sensors, location-aware devices, or electronic calendars; automated analysis of text in documents using natural language processing; and mapping networks of scientific collaboration by citations and co-authorships in clinical research literatures. Whereas much work in computational social science has offered new ways of empirically monitoring health behavior and health care behavior, a further contribution has been to directly model these social processes using system dynamics, microsimulation, discrete event simulation, and agent-based models. These approaches allow for computational ‘virtual’ experiments that assist in predicting, interpreting, and evaluating outcomes from health interventions. This poster will highlight some of my recent and pending work in this broad domain, aiming to identify potential collaborators in UMCCTS for projects that involve social networks or computational social science

Investigating the temporal dynamics of inter-organizational exchange: patient transfers among Italian hospitals

Previous research on interaction behavior among organizations (resource exchange, collaboration, communication) has typically aggregated records of those behaviors over time to constitute a ‘network’ of organizational relationships. We instead directly study structural-temporal patterns in organizational exchange, focusing on the dynamics of reciprocation. Applying this lens to a community of Italian hospitals during the period 2003-2007, we observe two mechanisms of interorganizational reciprocation: organizational embedding and resource dependence. We flesh out these two mechanisms by showing how they operate in distinct time frames: Dependence operates on contemporaneous exchange structures, whereas embedding develops through longer-term historical patterns. We also show how these processes operate differently in competitive and noncompetitive contexts, operationalized in terms of market differentiation and geographic space. In noncompetitive contexts, we observe both logics of reciprocation, dependence in the short term and embedding over the long term, developing into patterns of generalized exchange in this population. In competitive contexts, we observe neither form of reciprocation and instead observe the microfoundations of status hierarchies in exchange

Initial sequencing and analysis of the human genome

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62798/1/409860a0.pd

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Dynamics and stability of collective action norms

A set of computational experiments investigated a model of formal and informal control, showing how selective incentives to work for the collective good may paradoxically lead to enforcement of antisocial norms that oppose the collective good. In these conditions, the widely cited effects of selective incentives, group cohesiveness, and second-order free riding on collective action may be inverted. Mathematical analysis provides some certain bounds on the model's behavior and relaxes several restrictive assumptions used in the simulation research. This complementary view deepens our understanding of second order social control as a solution to problems of collective action

Greed and Fear in the Spatial Dilemmas Model: Implications for Cooperation Among Organizations

Organizational populations engage in institutional entrepreneurship – including both public and private (e.g., ‘self-’) regulation – to facilitate inter-organizational cooperation. We investigate the consequences of this regulation, distinguishing two dimensions of social dilemmas: the gains for exploiting cooperative partners (Greed) and the cost of cooperating with exploitive partners (Fear). Specifically, we model an embedded social dilemma in which organizations exchange with partners and strategies diffuse through networks by social learning. Our analysis and computational experiment show that embedding exchange in social networks leads Greed and Fear to have divergent and highly nonlinear effects at the macro level. ‘Virtual interventions’ demonstrate that resulting cascades of cooperation may persist even after the intervention is reversed. These analyses suggest deeper insights into the dynamics of strategic alliances that may be valuable to policy makers, industry self-regulatory institutions, corporate strategists, and researchers interested in the evolution of cooperation under different conditions

\u3ci\u3ePseudomonas Aeruginosa\u3c/i\u3e Strain MA01 Aerobically Metabolizes the Aminodinitrotoluenes Produced by 2,4,6-Trinitrotoluene Nitro Group Reduction

Many microbes reduce the nitro substituents of 2,4,6-trinitrotoluene (TNT), producing aminodinitrotoluenes (ADNTs). These compounds are recalcitrant to further breakdown and are acutely toxic. In a search for organisms capable of metabolizing ADNTs, a bacterial strain was isolated for the ability to use 2-aminobenzoate (anthranilate) as sole C-source. This isolate, Pseudomonas aeruginosa MAO1, metabolized TNT by first reducing one nitro group to form either 2-amino-4,6-dinitrotoluene (2ADNT) or 4 -amino-2,6-dinitrotoluene(4ADNT). However, strain MA01 was distinct from other TNT-reducing organisms in that it transformed these compounds into highly polar metabolites through an 02-dependent process. Strain MAOl was able to cometabolize TNT, 2ADNT, and 4ADNT in the presence of a variety of carbon and energy sources. During aerobic cometabolism with succinate, 45% of uniformly ring-labeled [14C]TNT was transformed to highly polar compounds. Aerobic cometabolism of purified [14C]2ADNT and [14C]4ADNT with succinate as C-source produced similar amounts of these polar metabolites. During O2-limited cometabolism with succinate as C-source and nitrate as electron acceptor, less than 8% of the [14C]TNT was transformed to polar metabolites. Purified 2,6-diamino-4 -nitrotoluene was not metabolized, and while 2,4-diamino-6-nitrotoluenewas acetylated, the product (N-acetyl-2,4-diamino-6-nitrotoluene) was not further metabolized. Therefore, strain MA0l metabolized TNT by oxidation of the ADNTs and not by reduction the remaining nitro groups on the ADNTs