1. Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection
- Author
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Lin Yuan, Dean Bottino, Madison Stoddard, Greg Hather, Laura F. White, and Arijit Chakravarty
- Subjects
AcademicSubjects/SCI01030 ,0301 basic medicine ,mixed-effects modeling ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,Longitudinal data ,population PK/PD ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Immunology ,Cellular biomarkers ,COVID-19 ,durability of immune response ,Computational biology ,biochemical phenomena, metabolism, and nutrition ,Biology ,03 medical and health sciences ,030104 developmental biology ,0302 clinical medicine ,Immunity ,Econometrics ,Methods ,Mixed effects ,Immunology and Allergy ,AcademicSubjects/SCI00100 ,030217 neurology & neurosurgery - Abstract
The duration of natural immunity in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a matter of some debate in the literature at present. For example, in a recent publication characterizing SARS-CoV-2 immunity over time, the authors fit pooled longitudinal data, using fitted slopes to infer the duration of SARS-CoV-2 immunity. In fact, such approaches can lead to misleading conclusions as a result of statistical model-fitting artifacts. To exemplify this phenomenon, we reanalyzed one of the markers (pseudovirus neutralizing titer) in the publication, using mixed-effects modeling, a methodology better suited to longitudinal datasets like these. Our findings showed that the half-life was both longer and more variable than reported by the authors. The example selected by us here illustrates the utility of mixed-effects modeling in provide more accurate estimates of the duration and heterogeneity of half-lives of molecular and cellular biomarkers of SARS-CoV-2 immunity.
- Published
- 2021
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