Vaccine models predict rules for updating vaccines against evolving pathogens such as SARS-CoV-2 and influenza in the context of pre-existing immunity - Desikan, Rajat; Linderman, Susanne L.; Davis, Carl; Zarnitsyna, Veronika I.; Ahmed, Hasan; Antia, Rustom (Frontiers in Immunology, 2022)
Currently, vaccines for SARS-CoV-2 and influenza viruses are updated if the new vaccine induces higher antibody-titers to circulating variants than current vaccines. This approach does not account for complex dynamics of how prior immunity skews recall responses to the updated vaccine. We: (i) use computational models to mechanistically dissect how prior immunity influences recall responses; (ii) explore how this affects the rules for evaluating and deploying updated vaccines; and (iii) apply this to SARS-CoV-2. Our analysis of existing data suggests the conclusions of current studies for Omicron-vaccines need to be revised, and that there is a strong benefit to updating the current vaccines. We propose a two-dose strategy for determining if vaccines need updating as well as for vaccinating high-risk individuals. Finally, we directly validate our model by reanalysis of earlier human H5N1 influenza vaccine studies.