Abstract
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 that there is a strong benefit to updating the current SARS-CoV-2 vaccines to match the currently circulating variants. We propose a general 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.
Keywords: COVID-19; SARS-CoV-2; Vaccine; modeling; omicron; simulations; variants.
【저자키워드】 COVID-19, SARS-CoV-2, Vaccine, omicron, modeling, Simulations, variants., 【초록키워드】 Immunity, Vaccines, Influenza, variants, SARS-CoV-2 vaccine, response, recall, Analysis, complex, H5N1, circulating variants, Affect, approach, benefit, influenza virus, induce, individuals, dissect, influence, circulating variant, 【제목키워드】 Influenza, pathogen, predict, pre-existing immunity,