# Optimizing Post-treatment Household Contact Investigation for Tuberculosis

> **NIH NIH F31** · JOHNS HOPKINS UNIVERSITY · 2024 · $47,270

## Abstract

PROJECT SUMMARY / ABSTRACT
Significance: Approximately 10.6 million people fell ill with tuberculosis (TB) in 2021. However, only 6.4 million
of these individuals were diagnosed and linked to care. A quarter of the 4.2 million undiagnosed TB cases were
in India. To help find the missing millions, the World Health Organization recommends investigating household
contacts of individuals with active TB. This intervention is usually implemented after index patient diagnosis.
Considering India’s high TB recurrence rate of approximately 13%, the government has also introduced TB
screening among treatment-completed patients. However, evidence around the effectiveness of screening in the
post-treatment period is scarce and optimal strategies for implementation have not yet been identified.
Specific Aims: Post-treatment household contact investigation is being implemented in Maharashtra, India
under the TB Aftermath non-inferiority trial and includes screening of the index patient (n=1076) and their
household contacts. This proposal assesses the overall effectiveness of post-treatment household contact
investigation and will generate policy-relevant evidence for optimizing the intervention in India and other similar
high TB burden settings. We will (1) determine the effect of the intervention compared to control sites that
represent standard of care, (2) evaluate implementation of the intervention compared to the standard of care,
and (3) develop a model for predicting TB recurrence to help target the intervention among high-risk households.
Approach: We will conduct a segmented regression analysis of TB recurrences detected in the 36 months
before and 36 months after post-treatment household contact investigation was introduced under TB Aftermath.
We will use routine TB data and compare trends in TB Aftermath sites (n=6) to control sites (n=6) selected using
propensity score matching. We will evaluate implementation based on the RE-AIM framework and will use mixed
methods. For the qualitative component, we will leverage existing TB Aftermath data (n=100 in-depth interviews
with patients, contacts, and staff) and will conduct 20 additional interviews with staff at the control sites. We will
use a convergent design to merge qualitative and quantitative findings (descriptive statistics on implementation
outcomes). Lastly, we will build and validate a predictive model for recurrence using TB Aftermath data (n=1076
participants). We will leverage existing RePORT India cohort data for external validation. By combining rigorous
epidemiologic and implementation research methods and engaging with key stakeholders, our team is poised to
thoughtfully translate optimized post-treatment household contact investigation into policy and practice.
Fellowship Information: The proposed study will serve as the dissertation for Ms. Samyra Cox, an Infectious
Disease Epidemiology PhD candidate at the Johns Hopkins Bloomberg School of Public Health. We propose a
dedicated mentor...

## Key facts

- **NIH application ID:** 10898300
- **Project number:** 1F31AI183564-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Samyra Roder Cox
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $47,270
- **Award type:** 1
- **Project period:** 2024-03-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10898300

## Citation

> US National Institutes of Health, RePORTER application 10898300, Optimizing Post-treatment Household Contact Investigation for Tuberculosis (1F31AI183564-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10898300. Licensed CC0.

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