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

> **NIH NIH R01** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2020 · $307,029

## Abstract

PROJECT SUMMARY
The current pandemic due to Coronavirus Disease 2019 (COVID-19) has led to the unprecedented use of non
pharmaceutical interventions (NPI), including limiting travel, closing business and schools, and ordering people
to shelter in place. While these extreme interventions are effective in slowing transmission of the disease, it is
not clear how they can best be implemented and how other local factors (such as population density, age
structure, timing in the outbreak, and smoking prevalence) might impact their efficacy. We are building a global
database of these interventions in order to more carefully explore these questions and allow other researchers
to use this data in their research. We will create models to better understand how NPI impact disease
transmission 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 that
is applicable to widely available case notification data.
As the disease spreads to vulnerable populations, such as people experiencing homelessness, persons living
with 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 Boston
Medical Center, the largest safety net hospital in New England. This will also include COVID-19 treatment and
testing data from Boston Healthcare for the Homeless. We will use this data to study the impact of COVID-19 on
these 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 elucidate
transmission patterns and impact in the developing world. We will estimate the impact of potential treatment
disruptions due to the pandemic response on HIV and TB populations.

## Key facts

- **NIH application ID:** 10142680
- **Project number:** 3R01GM122876-04S1
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** Laura Forsberg White
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $307,029
- **Award type:** 3
- **Project period:** 2017-04-15 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10142680

## Citation

> US National Institutes of Health, RePORTER application 10142680, Competitive revision to - Methods to estimate the effect of intervention on the incidence and transmission of Tuberculosis (3R01GM122876-04S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10142680. Licensed CC0.

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