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DIGITAL HEALTH SOLUTIONS FOR COVID-19: COVID-19 ONGOING MONITORING (COMMUNITY)

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 75N91020C00034-0-9999-1

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Key facts

  • Disease

    COVID-19

  • Start & end year

    2020
    2020

  • Known Financial Commitments (USD)

    $240,000

  • Funder

    National Institutes of Health (NIH)

  • Principal Investigator

    LUCA FOSCHINI

  • Research Location

    United States of America

  • Lead Research Institution

    EVIDATION HEALTH, INC.

  • Research Priority Alignment

    N/A

  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease susceptibility

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

The goal of this proposal is to develop a COVID-19 detection algorithm based on self-report survey data and wearable sensor data. Data from 25K COVID-19 Experiences participants and 25K Large-scale Flu Surveillance (COVID-19 Questions added March 2020) will be used with an existing machine learning model to develop this new detection algorithm, which will be validated in a large-scale pilot population to identify individuals with undiagnosed COVID-19. Evidation will incorporate the model into an established web and multi-platform (Android, iOS) smartphone platform called Achieve which allows users to share person-generated health data (PGD) from their everyday lives. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.