# Serocalculator: Estimating Incidence Rates from Serological Data

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2024 · $191,594

## Abstract

PROJECT ABSTRACT
Public health scientists lack reliable data on the burden of many infectious diseases, which is a
barrier to effective control measures. Seroepidemiology provides an efficient means to generate
unbiased estimates of disease burden such as seroincidence, the rate at which new infections
occur in a population. This project supports the development of an open-source R software
package, called serocalculator, to generate seroincidence estimates from cross-sectional
population surveys of serologic antibody response data. Our package will implement an
innovative statistical approach for estimating seroincidence that leverages information about
antibody waning from confirmed cases and overcomes many methodological challenges that
have stymied other approaches. Our specific aims are: Aim 1) Build an open-source, free-to-use
R software package for estimating incidence from cross-sectional serosurveys that is efficient,
reliable, and user-friendly and Aim 2) Enable widespread adoption and sustainable use of our
serocalculator R package through open-source access, a graphical user interface for non-R-
users, and a training curriculum. Our software will fill a gap between theory and practice by
equipping a new community of users with a tool to efficiently estimate incidence from cross-
sectional serosurveys. We expect this tool will be used to generate incidence estimates for a
range of infectious diseases, providing critical information needed to inform disease control
interventions and ultimately reduce the burden of disease.

## Key facts

- **NIH application ID:** 10798302
- **Project number:** 5R21AI176416-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Kristen Aiemjoy
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $191,594
- **Award type:** 5
- **Project period:** 2023-03-01 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10798302

## Citation

> US National Institutes of Health, RePORTER application 10798302, Serocalculator: Estimating Incidence Rates from Serological Data (5R21AI176416-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10798302. Licensed CC0.

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