Müller, Sebastian and Paltra, Sydney and Rehmann, Jakob and Nagel, Kai and Conrad, T. O. F. (2023) Explicit Modelling of Antibody Levels for Infectious Disease Simulations in the Context of SARS-CoV-2. iScience, 26 (9). ISSN 2589-0042
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Official URL: https://www.cell.com/iscience/fulltext/S2589-0042(...
Abstract
Measurable levels of immunoglobulin G antibodies develop after infections with and vaccinations against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These antibody levels are dynamic: due to waning, antibody levels will drop over time. During the COVID-19 pandemic, multiple models predicting infection dynamics were used by policymakers to support the planning of public health policies. Explicitly integrating antibody and waning effects into the models is crucial for reliable calculations of individual infection risk. However, only few approaches have been suggested that explicitly treat these effects. This paper presents a methodology that explicitly models antibody levels and the resulting protection against infection for individuals within an agent-based model. The model was developed in response to the complexity of different immunization sequences and types and is based on neutralization titer studies. This approach allows complex population studies with explicit antibody and waning effects. We demonstrate the usefulness of our model in two use cases.
Item Type: | Article |
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Subjects: | Mathematical and Computer Sciences > Mathematics > Mathematical Modelling Mathematical and Computer Sciences > Statistics > Applied Statistics > Medical Statistics |
Divisions: | Department of Mathematics and Computer Science > Institute of Mathematics Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Proteomics Group |
ID Code: | 2901 |
Deposited By: | Admin Administrator |
Deposited On: | 15 Feb 2023 08:56 |
Last Modified: | 23 Aug 2023 09:31 |
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