TY  - JOUR
AU  - Slotkin, Rebecca
AU  - Kyriakides, Tassos C
AU  - Yu, Vinni
AU  - Chen, Xien
AU  - Kundu, Anupam
AU  - Gupta, Shaili
PY  - 2025
DA  - 2025/4/22
TI  - CoVimmune COVID-19 Immunity Calculator: Web Application Development and Validation Study
JO  - JMIR Form Res
SP  - e59467
VL  - 9
KW  - COVID-19
KW  - immunity
KW  - neutralizing antibody
KW  - immunoglobulin G
KW  - vaccine hesitancy
KW  - vaccine timing
KW  - patient-centered care
KW  - web application
KW  - vaccination
KW  - SARS-CoV-2
AB  - Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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. 
SN  - 2561-326X
UR  - https://formative.jmir.org/2025/1/e59467
UR  - https://doi.org/10.2196/59467
DO  - 10.2196/59467
ID  - info:doi/10.2196/59467
ER  -