CK22-008 Midwest Virtual Laboratory of Pathogen Transmission in Healthcare Settings (MVL-PATHS)

  • Funded by National Institutes of Health (NIH)
  • Total publications:2 publications

Grant number: 5U01CK000671-02

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Key facts

  • Disease

    Unspecified
  • Start & end year

    2022.0
    2025.0
  • Known Financial Commitments (USD)

    $183,028
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    . Majid Bani Yaghoub
  • Research Location

    United States of America
  • Lead Research Institution

    UNIVERSITY OF MISSOURI KANSAS CITY
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Pathogen genomics, mutations and adaptations

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Midwest Virtual Laboratory of Pathogen Transmission in Healthcare Settings (MVL-PATHS) Project Summary Antimicrobial Resistant (AMR) pathogens have become a significant public health threat. Also, the COVID-19 pandemic has further revealed disparities in healthcare settings. By developing and implementing novel mathematical and computation models, the long-term goals are to optimize AMR control and preventive interventions and to improve the health equity. The central hypothesis is that the outputs of mathematical and computation models will provide optimized and effective guidelines to reduce the threat of AMR pathogen spread and reduce health disparities in healthcare settings. The rationale underlying this project is to fill the critical gap in modeling workforce capacity and develop a new generation of mathematical models for healthcare research. The central hypothesis will be tested by pursuing three specific aims to develop and employ a, (i) One Health modeling approach to understand the source, distribution and spread of AMR Enterobacteriaceae with a focus on Extended- spectrum beta-lactamase (ESBL)-producing E. coli, (ii) a novel Real-Time modeling approach to identify AMR pathogen transmission by asymptomatic spreaders and contaminated medical devices in hospitals, (iii) a novel Agent-Based Nested modeling approach to identify the effects of caregivers as vectors of disease spread, and effects of limited staffing and specialized care on equitable quality of care in nursing homes. We will pursue these aims using an innovative combination of mathematical and computational modeling techniques. These include both recently developed techniques of including human behavior in models and more-established techniques that have been applied very little to the study of health equity and AMR pathogen spread. The workforce development objectives of this proposal are to (i) enhance mathematical and computational modeling research capabilities of the public health workforce and (ii) increase the number of junior modeling professionals that are trained and experienced in modeling transmission of pathogens in healthcare settings partly incorporated with health disparities. The expected outcomes of this work are the successful training of five predoctoral fellows and creating a virtual laboratory of enhanced mathematical models to identify strategies for reducing the threat AMR pathogen spread and reducing health disparities. The results will have an important positive impact immediately because the virtual laboratory can also be used by healthcare professionals to further investigate the drivers of disease spread and estimate the relative benefits of multiple control and prevention strategies in a timely and cost-effective manner. In addition, the research outputs of this project will expand and strengthen national one-health efforts to combat resistance and will have a direct impact on CDC and its public health partners' ability to reduce the costs, morbidity and mortality of healthcare associated infections.

Publicationslinked via Europe PMC

Last Updated:15 hours ago

View all publications at Europe PMC

Bayesian inference of nosocomial meticillin-resistant Staphylococcus aureus transmission rates in an urban safety-net hospital.

Estimating the Relative Risks of Spatial Clusters Using a Predictor-Corrector Method.