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    NIOSH Centers of Excellence for Total Worker Health (U19)

    Forecasted

    NIOSH will fund Centers of Excellence for Total Worker Health to research and develop scalable solutions improving worker well-being, focusing on high-risk jobs, chronic disease, mental health, and new technologies.

    Funder: Centers for Disease Control and Prevention - ERA

    Due Dates (Anticipated): February 2027 (estimated application due date) | October 2027 (final submission deadline, projected)

    Funding Amounts: Estimated total program funding: $58,500,000 | Award ceiling: $1,400,000 per year | Award floor: $500,000 per year | Up to 10 awards expected

    Summary: Supports multi-component Centers conducting research and translation to improve worker well-being, prevent harmful exposures, and develop scalable workplace health solutions.

    Key Information: Forecasted opportunity—dates and requirements subject to change; check program page for updates.


    Description

    This opportunity supports the establishment and operation of Centers of Excellence in Total Worker Health® (TWH), funded by NIOSH through the CDC. The Centers will conduct rigorous research, translation, and dissemination activities aimed at preventing harmful workplace exposures, improving working conditions, and advancing overall worker well-being. Projects must utilize the NIOSH Worker Well-Being Questionnaire (WellBQ) and share data with the HERO Worker Well-Being Clearinghouse. Large research projects require an economic evaluation component.

    Priority research areas include:

    • High-risk occupations (e.g., first responders, vehicle mechanics, technicians)
    • Young workers and small-to-medium enterprises (SMEs)
    • Chronic disease, mental health, stress, substance use disorder
    • Artificial intelligence (AI) and digital technologies in occupational settings

    Applicants are expected to propose a mix of small and large research projects, with a structure that ensures strong coordination, scientific direction, and alignment across components.


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