PSI Vaccines SIG Webinar: Challenges in Estimating Vaccine Effectiveness Against Progression to Severe Disease
Date: Thursday 3rd July 2025
Time: 15:00 - 16:00 GMT +1:00
Location: Online via Zoom
Who is this event intended for?: Statisticians, Mathematicians, Modelers, working in vaccine development
What is the benefit of attending?: the benefit of attending the webinar is gaining an understanding of the challenges in estimating vaccine effectiveness against progression to severe disease, crucial for risk communication and vaccine impact modeling.
Overview
This is a free webinar on Challenges in Estimating Vaccine Effectiveness Against Progression to Severe Disease.
Vaccines can reduce an individual's risk of infection and their risk of progression to disease given infection. The latter effect is less commonly estimated but is relevant for risk communication and vaccine impact modeling. Using a motivating example from the COVID-19 literature, we note how vaccine effectiveness against progression can appear to increase over time in settings where true biological strengthening is unlikely. We use mathematical modeling to demonstrate how this phenomenon can occur when there is an underlying vulnerable subpopulation with poor vaccine response against infection and progression. As a result, the earliest infections are among those with the weakest protection against disease. We describe a modeling framework to link underlying immunology and post-vaccination outcomes that we use to further examine this problem. This work highlights methodological challenges in isolating a vaccine's effect on progression to severe disease after infection.
Registration
This event is free to attend for both PSI members and Non-members.
To register, please
click here.
Speaker details
Speaker
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Biography
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Abstract
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Natalie E. Dean, PhD
Emory University, Department of Biostatistics & Bioinformatics, Rollins School of Public Health. USA
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Natalie Dean is an Associate Professor in the Department of Biostatistics and Bioinformatics at Emory’s Rollins School of Public Health. Her primary research area is in methods for infectious disease epidemiology and vaccine study design, with a focus on emerging pathogens. She co-directs the Emory Alliance for Vaccine Epidemiology and the Summer Institute in Statistics and Modeling of Infectious Diseases. During the COVID-19 pandemic, Dr. Dean was active in science communication, with op-eds in the New York Times, Washington Post, and Stat News. She was honored as a member of the Committee of Presidents of Statistical Societies’ Leadership Academy and as recipient of the 2024 Communications Award from the Joint Policy Board of Mathematics
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Vaccines can reduce an individual’s risk of infection and their risk of progression to disease given infection. The latter effect is less commonly estimated but is relevant for risk communication and vaccine impact modeling. Using a motivating example from the COVID-19 literature, we note how vaccine effectiveness against progression can appear to increase over time in settings where true biological strengthening is unlikely. We use mathematical modeling to demonstrate how this phenomenon can occur when there is an underlying vulnerable subpopulation with poor vaccine response against infection and progression. As a result, the earliest infections are among those with the weakest protection against disease. We describe a modeling framework to link underlying immunology and post-vaccination outcomes that we use to further examine this problem. This work highlights methodological challenges in isolating a vaccine’s effect on progression to severe disease after infection.
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