# CoVimmune COVID-19 Immunity Calculator: Web Application Development and Validation Study

**Authors:** Rebecca Slotkin, Tassos C Kyriakides, Vinni Yu, Xien Chen, Anupam Kundu, Shaili Gupta

PMC · DOI: 10.2196/59467 · JMIR Formative Research · 2025-04-22

## TL;DR

A web app was developed to estimate SARS-CoV-2 neutralizing antibody levels based on IgG test results, helping assess vaccine-induced immunity.

## Contribution

A novel web-based calculator was developed to translate IgG test results into estimated neutralizing antibody titers for vaccinated individuals.

## Key findings

- The web application uses datasets to correlate IgG and neutralizing antibody titers in vaccinated adults.
- The tool incorporates statistically significant clinical factors to improve nAb titer prediction accuracy.
- The calculator provides a patient-centered estimate of vaccine-mediated antibody protection.

## Abstract

This study illustrates the development of a simple web-based application, which demonstrates the relationship between serum anti-SARS-CoV-2 S1/receptor-binding domain immunoglobulin G (IgG) and anti-SARS-CoV-2 neutralizing antibody (nAb) half-maximal inhibitory concentration (IC50) titers in a vaccinated US adult population and compares them to prior data on nAb titers at different time points after vaccination.

The objective of this study is to create an easily accessible calculator that uses the results of commercially available anti-SARS-CoV-2 serum IgG to approximate the underlying ability to neutralize SARS-CoV-2.

Our web-based application leveraged two previously published datasets. One dataset demonstrated a robust correlation between nAb and serum IgG. The other dataset measured nAb titers at specific time periods over a year-long interval following a messenger RNA vaccination primary series and booster vaccine dose. Clinical factors that were statistically significant on a forward linear regression model examining the prediction of nAb from serum IgG were incorporated in the application tool.

By combining the datasets described above, we developed a publicly available web-based application that allows users to enter a serum IgG value and determine their estimated nAb titer. The application contextualizes the estimated nAb titer with the theoretical distance from the corresponding vaccine-mediated antibody protection. Using the clinical variables that had a significant impact on how well IgG values predict nAb titers, this application allows for a patient-centered, nAb titer prediction.

This application offers an example of how we might bring the advances made in scientific research on protective antibodies post-SARS-CoV-2 vaccination into the clinical sphere with practical tools.

## Linked entities

- **Proteins:** PSMD1 (proteasome 26S subunit, non-ATPase 1)
- **Diseases:** SARS-CoV-2 (MONDO:0100096), COVID-19 (MONDO:0100096)

## Full-text entities

- **Diseases:** CoVimmune COVID-19 (MESH:D000086382)
- **Species:** Homo sapiens (human, species) [taxon 9606], Severe acute respiratory syndrome coronavirus 2 (no rank) [taxon 2697049]

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12040297/full.md

## References

9 references — full list in the complete paper: https://tomesphere.com/paper/PMC12040297/full.md

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Source: https://tomesphere.com/paper/PMC12040297