Publication date: Sep 19, 2025
Antibody dynamics models are analytical frameworks that probabilistically link changes in antibody titer timeseries to exposures. To date, antibody dynamics models have not been applied to SARS-CoV-2 datasets and have not incorporated observed exposures (i. e., from vaccination and positive PCR results) directly in their inference. We developed a bespoke framework that incorporates these features and applied it to data from the “Prospective Assessment of COVID-19 in a Community” (PACC) cohort. We used ELISA to measure serum antibody levels against Wuhan-1 spike (S) and nucleocapsid (N) proteins and inferred the level of protection from SARS-CoV-2 infection each antigen provided at different titers (protection curves). The S protection curve shifted when the Omicron lineage evolved, indicating that higher Wuhan-1 titers were required for protection. Age and exposure history did not shift the protection curves. This work highlights the utility of antibody dynamics frameworks to inform SARS-CoV-2 vaccination strategies.
Open Access PDF
| Concepts | Keywords |
|---|---|
| Antibodies | Health sciences |
| Date | Immunology |
| Nucleocapsid | Medical specialty |
| Pcr | Medicine |
| Wuhan | Public health |
Semantics
| Type | Source | Name |
|---|---|---|
| disease | MESH | COVID-19 |
| pathway | REACTOME | SARS-CoV-2 Infection |
| disease | IDO | history |