Fig 3. Linear mixed effect model comparing spike exposure groups in a nursing home cohort—Georgia, December 2020–July 2022, n = 37.

A: Linear Mixed Effect Modeling for anti-SARS-CoV-2 Spike (S) IgG. Footnote: We explored modeling the kinetics of log-transformed antibody titers through a linear mixed-effect model starting at the peak level for each participant from the time of their last spike exposure. Each mixed effect model included the fixed effect comprising the time from the last spike exposure and exposure group and random effects for participants and time. Bonferroni-adjustment of alpha value was made for multiple comparisons in linear mixed effect models to avoid inflation of the type I error; adjusted p-value of <0.006 were considered statistically significant. Light-colored lines indicate individual participant responses; Dark-colored lines indicate mean estimates for the spike exposure groups. B: Linear mixed effect model for percent spike inhibition (virus neutralizing capacity). Footnotes: We explored modeling the kinetics of log-transformed neutralizing antibody titers through a linear mixed effect model starting at the peak level for each participant from the time of their last spike exposure. Each mixed effect model included the fixed effect comprising the time from the last spike exposure and exposure group and random effects for participants and time. Interaction effects were tested using likelihood ratio testing that compared models with and without the interaction. Bonferroni-adjustment of alpha value was made for multiple comparisons in linear mixed effect models to avoid inflation of the type I error; adjusted p-value of <0.006 were considered statistically significant. Light-colored lines indicate individual participant responses; Dark-colored lines indicate mean estimates for the spike exposure groups.