# IP24-045, PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement

> **NIH ALLCDC U01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $5,753,431

## Abstract

SUMMARY
Monitoring of the incidence, morbidity, and mortality of respiratory infections has largely been performed by
collecting and analyzing data from hospitals and clinical laboratories. While these data sources provide valuable
information on risk factors, incidence, therapeutic response, and outcomes of severe disease, they do not reflect
the range of potential clinical presentations and courses of disease, factors that increase or decrease the risk of
community transmission, and the impact of disease on education and employment. We therefore propose to
create “PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement,” which
will serve as one of the CDC Pandemic Preparedness Network Cohorts and the Network’s Data Hub. We will
participate in Components A1, A2, B, and C, with a catchment that spans San Diego County in HHS Region 9
adjacent to the U.S./Mexico border. Our relevant experience includes establishment of innovative programs for
large-scale COVID-19 clinical testing, environmental surveillance through monitoring of wastewater and surface
swabs, viral genome sequencing, and monitoring of immunity using co-created community-based sample
collection strategies that are highly accessible and culturally sensitive. Major PREVENT activities will include:
Component A1: We will enroll and retain a diverse longitudinal cohort of 2,000 individuals for: weekly symptom
screening; surveys on knowledge, attitudes, and behaviors related to preventative measures; extraction of
outcome and vaccination data from electronic health records and immunization information systems; and
collection of follow-up data from participants on use of preventative/therapeutic measures and healthcare
resources, missed school/work, symptom type/duration, and long-term sequelae. Symptomatic swabs will be
collected and tested for 20 high-priority respiratory pathogens. Viral genome sequencing will be performed on a
subset of samples using targeted and metatranscriptomic methods. Samples will be banked for >5 years.
Component A2: Serial blood samples will be collected, analyzed, and banked from 20% of participants in
Component A1. Samples will be collected at enrollment, in the months flanking the respiratory infection season,
before/after vaccinations, and after infection. Quantitative immunoassays for antigen-specific antibody (Ab)
levels and neutralizing antibody (nAb) levels against contemporary circulating virus isolates will be performed.
Component B: For >100 index cases from A1 per year, we will collect and test daily nasal swabs from >75% of
household members for >2 weeks. A subset of swabs (including at least 1 per index case) will be analyzed by
viral genome sequencing, and high-priority pathogens/variants will be cultured. For a subset of households, we
will also explore the relationships between viral load (quantified by qPCR) and viral titer (by in vitro cell-based
assay), and between viral culture positivity and transmission.
Compo...

## Key facts

- **NIH application ID:** 11040976
- **Project number:** 1U01IP001238-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** LOUISE CHANG LAURENT
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2024
- **Award amount:** $5,753,431
- **Award type:** 1
- **Project period:** 2024-08-01 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11040976

## Citation

> US National Institutes of Health, RePORTER application 11040976, IP24-045, PREVENT: Preparedness through Respiratory Virus Epidemiology and Community Engagement (1U01IP001238-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11040976. Licensed CC0.

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