Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling.

ABSTRACT:

Introduction

Identifying optimal COVID-19 vaccine dose is essential for maximizing their impact. However, COVID-19 vaccine dose-finding has been an empirical process, limited by short development timeframes, and therefore potentially not thoroughly investigated. Mathematical IS/ID modelling is a novel method for predicting optimal vaccine dose which could inform future COVID-19 vaccine dose decision making.

Methods

Published clinical data on COVID-19 vaccine dose-response was identified and extracted. Mathematical models were calibrated to the dose-response data stratified by subpopulation, where possible to predict optimal dose. Predicted optimal doses were summarised across vaccine type and compared to chosen dose for the primary series of COVID-19 vaccines to identify vac

SUBMITTER: Rhodes S 

PROVIDER: S-EPMC9574467 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature