Competitive revision to - Methods to estimate the effect of intervention on the incidence and transmission of Tuberculosis

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

Grant number: 3R01GM122876-04S1

Grant search

Key facts

  • Disease

    COVID-19
  • Start & end year

    2017
    2022
  • Known Financial Commitments (USD)

    $307,029
  • Funder

    National Institutes of Health (NIH)
  • Principle Investigator

    Pending
  • Research Location

    United States of America, Americas
  • Lead Research Institution

    BOSTON UNIVERSITY MEDICAL CAMPUS
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Disease transmission dynamics

  • Special Interest Tags

    Gender

  • Study Subject

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

The current pandemic due to Coronavirus Disease 2019 (COVID-19) has led to the unprecedented use of nonpharmaceutical interventions (NPI), including limiting travel, closing business and schools, and ordering peopleto shelter in place. While these extreme interventions are effective in slowing transmission of the disease, it isnot clear how they can best be implemented and how other local factors (such as population density, agestructure, timing in the outbreak, and smoking prevalence) might impact their efficacy. We are building a globaldatabase of these interventions in order to more carefully explore these questions and allow other researchersto use this data in their research. We will create models to better understand how NPI impact diseasetransmission and how the local context effects the impact of these NPI. We are working with colleagues in NYC,Spain, and Italy with more granular data to better explore these problems. We aim to develop a framework thatis applicable to widely available case notification data.As the disease spreads to vulnerable populations, such as people experiencing homelessness, persons livingwith HIV (PLWH) and TB, we anticipate that the impact on these populations will be more severe and with a higher force of infection. We will are involved in an effort to build a COVID-19 patient data warehouse at BostonMedical Center, the largest safety net hospital in New England. This will also include COVID-19 treatment andtesting data from Boston Healthcare for the Homeless. We will use this data to study the impact of COVID-19 onthese vulnerable populations. We will also leverage our strong relationships with collaborators in South Africa,the Philippines, and Ukraine, where the prevalence of these conditions is much higher, in order to better elucidatetransmission patterns and impact in the developing world. We will estimate the impact of potential treatmentdisruptions due to the pandemic response on HIV and TB populations.