# Improving influenza vaccines through wastewater-based macro-scale strain surveillance

> **NIH NIH R43** · GT MOLECULAR, LLC · 2022 · $256,575

## Abstract

ABSTRACT
Influenza infects 9 to 45 million people in the United States each year and results in 300,000 to 500,000 deaths
worldwide. Vaccination is the foundation of the global response to control and reduce the spread of Influenza;
however, seasonal influenza vaccine efficacy ranged from non-statistically significant to 60% between 2011
and 2019.Vaccine efficacy is largely contingent upon properly matching strains in circulation to the stains
selected for inclusion in the seasonal vaccine. History provides examples of mismatches that rendered vaccine
ineffective, thus highlighting the need to revisit the strain selection paradigm. In depth viral surveillance and
genomic characterization of circulating strains and the monitoring of viral spread dynamics across geographic
areas throughout the year are paramount to select strains with the highest probability of circulation. However,
with the current influenza surveillance network, < 0.2% of all influenza cases in the United States undergo
genomic characterization, making it highly possible that a circulating strain would not be characterized.
Additionally, there are several inherent challenges within the current swab-based surveillance approach that
could bias the data coming out of this program and thus result in the incorrect selection of viruses for inclusion
in the yearly vaccine. To improve vaccine-strain selection, we propose a macro-scale influenza and SARS-
CoV-2 surveillance approach through monitoring community wastewater. Nearly all community members
unintentionally provide their wastewater treatment facilities with regular fecal samples, and both SARS-CoV-2
and influenza have been shown to be shed in human feces. GT Molecular already developed and deployed a
state-of-the-art viral quantification methodology for SARS-CoV-2 in wastewater monitoring used by over 100
communities around the country. In the proposed work, we will expand our wastewater monitoring capabilities
to include (i) monitoring influenza prevalence, in addition to SARS-CoV-2, for observation of viral spread
dynamics across geographic regions (Aim 1) and (ii) providing macroscale strain surveillance and genomic
characterization of influenza and SARS-CoV-2 circulating strains found in wastewater (Aim 2). We will achieve
Specific Aim 1 through optimization of our current SARS-CoV-2 workflow for simultaneous concentration,
extraction, and quantification of SARS-CoV-2 and influenza. We will achieve Specific Aim 2 through
optimization of our previously described tiled amplicon sequencing approach for genomic characterization of
viral genomes in wastewater. Many vaccine experts expect SARS-CoV-2 to become endemic and potentially
require a seasonal vaccine, like influenza. Therefore, this work could serve as a foundation for the surveillance
of both viruses, providing a robust dataset for international surveillance programs to use in their yearly strain
inclusion discussion and decision making.

## Key facts

- **NIH application ID:** 10385514
- **Project number:** 1R43AI167462-01
- **Recipient organization:** GT MOLECULAR, LLC
- **Principal Investigator:** Sarah Jo Kane
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $256,575
- **Award type:** 1
- **Project period:** 2022-02-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10385514

## Citation

> US National Institutes of Health, RePORTER application 10385514, Improving influenza vaccines through wastewater-based macro-scale strain surveillance (1R43AI167462-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10385514. Licensed CC0.

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