tetano
Editor, Senior Moderator
Sci Rep
. 2025 Oct 6;15(1):34800.
doi: 10.1038/s41598-025-18673-9. Comparing neutralizing antibody activity over time between naïve and convalesced COVID-19 vaccinated individuals
Lisette de Pillis[SUP] 1 [/SUP], Rebecca Caffrey[SUP] 2 [/SUP], Ge Chen[SUP] 2 [/SUP], Mark Dela[SUP] 3 [/SUP], Leif Eldevik[SUP] 2 [/SUP], Hong Liu[SUP] 2 [/SUP], Joseph P McConnell[SUP] 2 [/SUP], Shahrokh Shabahang[SUP] 2 [/SUP], Stephen A Varvel[SUP] 4 [/SUP]
Affiliations
Longitudinal data comprised of neutralizing antibody (NAb) activity measurements from subjects who received COVID-19 vaccinations were collected between November 2020 and April 2022. To detect differences between convalesced and naïve groups with respect to the evolution of NAb activity since the subject's first COVID-19 vaccine, we initially fit a linear mixed effects model to only the decay section of NAb evolution. We conclude that NAb activity, when restricted to this region, behaves differently between these two groups, with the convalesced group generally having higher neutralizing antibody levels than the naïve group. We then fit a nonlinear mixed effects model over the entire NAb progression using a system of ordinary differential equations described by De Pillis et al. as our structural component to the model. This analysis not only supports the claim that over the entire progression, NAb activity behaves differently for convalesced and naïve groups, but aligns with the linear analysis in confirming that NAb decay is slower in the convalesced group than the naïve group. Finally, we use the estimated parameters from the nonlinear mixed effects model to predict NAb progression for each subject from their last observed measurement to 100 days past this measurement.
Keywords: AditxtScoreTM; COVID-19; Linear mixed effects models; MATLAB; Mathematical models; Monolix; Neutralizing antibody; Nonlinear mixed effects models; ODEs; Prediction; R; SARS-Cov-2.
. 2025 Oct 6;15(1):34800.
doi: 10.1038/s41598-025-18673-9. Comparing neutralizing antibody activity over time between naïve and convalesced COVID-19 vaccinated individuals
Lisette de Pillis[SUP] 1 [/SUP], Rebecca Caffrey[SUP] 2 [/SUP], Ge Chen[SUP] 2 [/SUP], Mark Dela[SUP] 3 [/SUP], Leif Eldevik[SUP] 2 [/SUP], Hong Liu[SUP] 2 [/SUP], Joseph P McConnell[SUP] 2 [/SUP], Shahrokh Shabahang[SUP] 2 [/SUP], Stephen A Varvel[SUP] 4 [/SUP]
Affiliations
- PMID: 41053351
- DOI: 10.1038/s41598-025-18673-9
Longitudinal data comprised of neutralizing antibody (NAb) activity measurements from subjects who received COVID-19 vaccinations were collected between November 2020 and April 2022. To detect differences between convalesced and naïve groups with respect to the evolution of NAb activity since the subject's first COVID-19 vaccine, we initially fit a linear mixed effects model to only the decay section of NAb evolution. We conclude that NAb activity, when restricted to this region, behaves differently between these two groups, with the convalesced group generally having higher neutralizing antibody levels than the naïve group. We then fit a nonlinear mixed effects model over the entire NAb progression using a system of ordinary differential equations described by De Pillis et al. as our structural component to the model. This analysis not only supports the claim that over the entire progression, NAb activity behaves differently for convalesced and naïve groups, but aligns with the linear analysis in confirming that NAb decay is slower in the convalesced group than the naïve group. Finally, we use the estimated parameters from the nonlinear mixed effects model to predict NAb progression for each subject from their last observed measurement to 100 days past this measurement.
Keywords: AditxtScoreTM; COVID-19; Linear mixed effects models; MATLAB; Mathematical models; Monolix; Neutralizing antibody; Nonlinear mixed effects models; ODEs; Prediction; R; SARS-Cov-2.