# DIVINCI Enrollment Supplement

> **NIH NIH U01** · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · 2024 · $896,275

## Abstract

Research Summary
The objectives of DIVINCI are to study influenza infection from birth to examine the effect of first
influenza exposure and subsequent exposures on the immune response. In this U01, we address
fundamental questions about how initial and repeated influenza exposures through natural
infections and/or vaccination shape infant and childhood immunity to influenza. The COVID-19
pandemic has created two main issues affecting DIVINCI: 1) reducing circulation of other
respiratory viruses across the world creating uncommon exposure histories for babies born during
DIVINCI enrollment and 2) increasing infection rates due to Omicron and likely other variants and
therefore increasing rates of influenza-like illness in these communities and the need for clinical
testing of respiratory specimens. To address the above problems, we propose to continue to
enroll participants into the New Zealand and the Los Angeles cohorts for the next two years. In
total, we propose to enroll 150 additional infants in the New Zealand cohort and
continue enrollment efforts in Southern California. Additionally, the Supplement will cover
the unanticipated costs of operating during a pandemic including the increase in the
number of participants meeting our testing criteria and the need for higher level PPE.

## Key facts

- **NIH application ID:** 10905806
- **Project number:** 3U01AI144616-05S1
- **Recipient organization:** ST. JUDE CHILDREN'S RESEARCH HOSPITAL
- **Principal Investigator:** AUBREE L GORDON
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $896,275
- **Award type:** 3
- **Project period:** 2019-05-02 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10905806

## Citation

> US National Institutes of Health, RePORTER application 10905806, DIVINCI Enrollment Supplement (3U01AI144616-05S1). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10905806. Licensed CC0.

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