Health Applications of Social Network Analysis and Computational Social Science

Social network analysis has proliferated across the social and behavioral sciences, shifting our analytical focus from individuals to the patterns of social ties that connect them. This perspective 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 physicians’ professional networks, the dynamics of patient transfers on networks of clinics, and the spread of weight-related behaviors among adolescents at risk for obesity. The advent of the era of computational social science has augmented the contributions of this perspective, by moving beyond expensive and laborious methods of questionnaires and direct observation to incorporate new techniques of data collection and analysis. For example, these include analysis of electronic health records or other time-stamped communication traces among healthcare practitioners; streams of behavioral data from wearable sensors, location-aware devices, or electronic calendars; automated analysis of text in documents; and mapping networks of interaction by citations and collaboration in clinical research literatures. Whereas much of computational social science has offered new ways of monitoring health behavior and healthcare behavior, or for analyzing those data, a further contribution has been to directly analyze these social processes in system dynamics models, microsimulation, and agent-based models. These approaches allow for computational experiments that assist in predicting and interpreting outcomes from health interventions. This poster will highlight some of my recent and pending work in this domain, aiming to identify potential collaborators in UMCCTS for projects that involve social networks or computational social science

The Annual Demography of a Population of Antelope Ground Squirrels in Curlew Valley, Utah

The annual demography of a population of antelope ground squirrels in Curlew Valley, Utah was studied by measuring population density, natality, and mortality. Capture- recapture techniques yielded lower estimates than the Hayne strip- census. The estimates suggested 1968 was a year of population decline. One hundred seventy- three squirrels were collected and autopsied to obtain sex ratio , age structure, natality, and mortality data . The seasonal sex ratios for adult and yearling squirrels showed 82 percent females in spring 1968, this gradually changed to 56 percent by winter . The seasonal sex ratios of the young squirrels showed 59 percent females upon emergence from natal burrows in summer 1968, increasing to 79 percent by winter. The squirrels collected were aged by cementum annuli . The oldest were believed to be 5 years old . They composed 1.2 percent of the collection while young- of- the-year composed 38. 7 percent. The estimate of mean corpora lutea was 7.6, the mean embryo count was 7.2, and the mean post-partum placental scar count was 5.8. The mean corpora lutea count for yearlings was statistically lower than the count for adults and the mean ovulation rate for 1968 statistically lower than the rate for 1969. An estimate of litter size from four nests gave a mean of 4.5. In 1968, the conception rate was 91 percent with yearlings comprising 75 percent of those not conceiving. In 1969, the rate was 100 percent. Pre-Emergence mortality of the young was 41 percent. post-emergence mortality was 86 percent, and mortality, March - November, 1968 was 92 percent. Adult and yearling spring-to-spring mortality for study area squirrels calculated from retrap data was 81 percent. Spring-to-spring mortality calulated from age distribution data and Ricker\u27s formula was 71 percent. The spring-to-fall mortality for 1968 calculated from density estimates and age distribution data was 53 percent

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

Moles

1 online resource (PDF, 2 pages)This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu

Rabbits and hares

1 online resource (PDF, 2 pages)This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu

Shrews

1 online resource (PDF, 1 page)This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu

Bats

1 online resource (PDF, 2 pages)This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu

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

Infrastructure for Internet-Based Operations

Global access to remote systems is becoming a reality through advances in the Internet. Applied to spacecraft operations, this provides the opportunity for spacecraft operators to access remote system resources from any location with Internet access. As part of its space operations research, Stanford University\u27s Space Systems Development Laboratory (SSDL) is exploring the ability of Internet based operations to improve the cost effectiveness of space mission operation. It is developing a ground station control system to provide computer assisted console control, remote operation, and software agent-based autonomous control. Known as Mercury, the system has been implemented on SSDL\u27s OSCAR-class amateur radio ground station and is in use to conduct operations on SSDL\u27s first orbiting microsatellite, OPAL. This paper outlines various Internet based operation techniques and discusses the design of the Mercury prototype

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