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    Chapter 16 Exposure Health Informatics Ecosystem

    Proposal review

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    Author(s)
    Gouripeddi, Ramkiran
    Lundrigan, Philip
    Kasera, Sneha
    Collingwood, Scott
    Cummins, Mollie
    Facelli, Julio C.
    Sward, Katherine
    Language
    English
    Show full item record
    Abstract
    There is a need for understanding an individual’s total exposure, including simultaneous, cumulative, and latent exposure to multiple environmental contaminants. While exact contributions differ, multiple studies suggest that the majority of a person’s health can be attributed to their environment, lifestyle, and behavior. This chapter describes the University of Utah’s Exposure Health Informatics Ecosystem (EHIE), a sensor-based, data-intensive infrastructure for measuring environmental, physiological, and behavioral factors for performing pediatric and adult epidemiological studies. EHIE is a generalizable multi-scale and multi-omics platform providing robust pipelines for reproducible exposomic research and uses real-time, low-cost sensors to provide spatio-temporal records of environmental exposures. Furthermore, this chapter provides details on how EHIE supports the Pediatric Research using Integrated Sensor Monitoring Systems (PRISMS) and the Environmental influences on Child Health Outcomes (ECHO) programs. Initial results from these pilots demonstrate the feasibility of using informatics ecosystems like EHIE to perform sensor-based longitudinal cohort studies.
    Book
    Total Exposure Health
    URI
    https://library.oapen.org/handle/20.500.12657/76045
    Keywords
    Health & safety in the workplace
    DOI
    10.1201/9780429263286-18
    ISBN
    9780367201395, 9780367505417, 9780429263286
    Publisher
    Taylor & Francis
    Publisher website
    https://taylorandfrancis.com/
    Publication date and place
    2020
    Grantor
    • University of Utah
    Imprint
    CRC Press
    Pages
    47
    Rights
    https://creativecommons.org/licenses/by-nc-nd/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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