Making sense of COVID-19 immunity in a data-rich era

Date: Thursday 17 November 2022

Abstract

Throughout the COVID-19 pandemic the infectious disease and immunity research communities encountered an unprecedented explosion of data. Unlike ever before, there was a rapid development and approval of effective vaccines and other therapeutics for preventing and treating COVID-19 – with which came large amounts of immunological and clinical data. However, this richness of data was also a major challenge to the research community and public health decision making. For example, when there were multiple and seemingly conflicting reports on the success or failure of vaccines or therapeutics, there was often difficulty reconciling contradictory information.

In this talk, I will present our team's unique approach to synthesizing immunological and clinical data, and the application of modelling and data analysis to assist in a cohesive understanding of vaccine and drug efficacy in this data-rich era. I will discuss how we analyzed the efficacy and determined dose-response relationships for different SARS-CoV-2 interventions. The synthesis of data from multiple different sources allowed us to provide clear assessment of the determinates of the success of different vaccines and therapeutics. Using quantitative relationships, we could predict (with confidence quantification) whether new treatments or vaccines were expected to work, even against new variants. Overall, our experience shows the high need for rigorous quantitative analysis of data for both the research community and policy makers.