# Emerging methods and applications for test-negative studies of of infectious disease interventions

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA BERKELEY · 2021 · $437,670

## Abstract

PROJECT SUMMARY/ABSTRACT
 The need for longitudinal follow-up of individuals exposed to interventions against rare
 infectious disease endpoints poses a barrier to prospective efficacy and effectiveness studies.
 Studies using the test-negative design (TND) have become a popular alternative. TNDs
 represent a variant on traditional case-control designs: studies enroll subjects who seek care for
 a clinical syndrome, defining those who test positive and negative for a pathogen of interest as
 “cases” and “controls”, respectively. To facilitate rigorous and reproducible assessments of
 vaccine performance, the project will re-assess emerging applications of the TND, and
 contribute methods to measure intervention effects from data collected by TND studies.
 The first two aims revisit estimation strategies for vaccine-conferred protection against infection
 and against the progression of infection to disease—the two components of the vaccine “direct
 effect” that TND studies aim to measure. We propose novel frameworks to estimate each effect
 through extensions of the TND: one through comparisons of symptomatic and asymptomatic
 persons, and another leveraging the age distribution of cases. We will apply these methods to
 estimate pneumococcal conjugate vaccine effectiveness against vaccine-serotype pneumococcal
 pneumonia and carriage, and to re-assess reported differences in rotavirus vaccine effectiveness
 across high, middle, and low-income countries.
 In Aim 3, we will continue development of statistical procedures for cluster randomized test-
 negative designs. A major field trial of this nature for a vector intervention utilizing the
 bacterium Wolbachia to reduce dengue fever transmission is nearing completion. Permutation-
 based inference is planned because of small numbers of clusters. We will extend such methods
 (i) to allow for individual measures of intervention exposure (based on human and mosquito
 mobility), and (ii) to include design variants such as the stepped wedge design and interrupted
 time series where data collection has either recently ended or is in process. We will also consider
 a novel application to assess a new vaccine against Ebola Virus Disease (EVD) in the
 Democratic Republic of the Congo. This project will thus contribute methods and computational
 routines to allow valid inferences from TND study data, permitting novel assessments of
 interventions against rotavirus, pneumococcal disease, EVD, and dengue etc.

## Key facts

- **NIH application ID:** 10219130
- **Project number:** 5R01AI148127-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** NICHOLAS P JEWELL
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $437,670
- **Award type:** 5
- **Project period:** 2020-07-17 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10219130

## Citation

> US National Institutes of Health, RePORTER application 10219130, Emerging methods and applications for test-negative studies of of infectious disease interventions (5R01AI148127-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10219130. Licensed CC0.

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