# Prospective annual estimates of influenza vaccine effectiveness and burden of disease

> **NIH ALLCDC U01** · KAISER FOUNDATION RESEARCH INSTITUTE · 2020 · $1,800,000

## Abstract

Summary/Abstract
Although influenza vaccination is the best available tool for reducing illnesses and deaths due to influenza,
influenza vaccine effectiveness (VE) can vary substantially from year to year, depending on the antigenic
match between circulating viruses and vaccine strains. To guide the ongoing development of influenza
vaccination recommendations, we propose to conduct annual estimates of influenza VE, influenza burden of
illness, and cases prevented by vaccination. We will conduct active surveillance for medically attended,
laboratory-confirmed influenza in a predefined cohort. We will identify patients seeking ambulatory care for
acute respiratory illness; eligible and consenting patients will be enrolled in the study. We will collect
specimens for respiratory virus testing from all participants, which will be tested for influenza (including type,
subtype, and lineage) via nucleic acid amplification. We will determine risk factors for influenza, and illness
outcomes, through a combination of questionnaires and administrative healthcare databases. We will
determine subjects' influenza vaccination history through self-report, validated using an immunization registry.
Data will be shared with CDC and other participating sites to provide mid-season and end-of-season VE
estimates. We will estimate VE using a test-negative design, comparing the odds of vaccination among
subjects who test positive for influenza with the odds among subjects testing negative. We will provide annual
estimates stratified by virus type/subtype/lineage and by age group. Because we are identifying patients with
influenza from a defined cohort, we will also estimate the incidence of medically attended influenza in our study
population, and estimate the number of influenza cases averted by vaccination.
 This project will also serve as a resource for studying VE and epidemiology of a novel influenza virus,
should an influenza pandemic occur during the study period. We will work with CDC and other sites to prepare
and pilot-test protocols for pandemic studies. In addition, this project provides a platform for respiratory
syncytial virus (RSV) surveillance, which can provide important data on the epidemiology of RSV prior to
licensure of RSV vaccines. We will test specimens for RSV and estimate the incidence of medically attended
RSV in our study population. Finally, we will use data collected from this study to further explore potential
biases and limitations of the test-negative design and to anticipate possible effects of RSV vaccine licensure
on influenza VE estimates from test-negative studies.
 The proposed research will 1) generate data to guide influenza prevention actions and
recommendations; 2) provide baseline data on RSV incidence prior to vaccine licensure; and 3) enhance our
understanding of the test-negative study design.

## Key facts

- **NIH application ID:** 9966830
- **Project number:** 5U01IP001037-05
- **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE
- **Principal Investigator:** Michael L Jackson
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2020
- **Award amount:** $1,800,000
- **Award type:** 5
- **Project period:** 2017-08-01 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9966830

## Citation

> US National Institutes of Health, RePORTER application 9966830, Prospective annual estimates of influenza vaccine effectiveness and burden of disease (5U01IP001037-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9966830. Licensed CC0.

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