Quantifying the breadth of vaccine response with antigenic distance
What does it even mean when we talk about vaccine breadth? If we have a universal vaccine candidate, how can we calculate its breadth? We propose a framework utilizing antigenic distance and summary antibody landscapes based on data from cohort studies with panels of immunogenicity data to multiple strains.
Intro to Open Science, v2
Open science is a pretty broad term that broadly includes data sharing, open access publication, inclusive research, preregistration, and more! In this talk, I gave an intro to the concept of open science at a seminar for the Center for the Ecology of Infectious Disease (CEID) at UGA.
Longitudinal trajectories of influenza immune response after repeat vaccination
Repeat vaccination is sort of a hot topic in flu immunity right now, but most analyses are still done in a cross-sectional format. Using data from an ongoing influenza vaccination cohort study, we break trajectories up into component segments to analyze patterns of boosting and waning. This allows us to quantify trends across strata and allow for measurement error in responses of a specific magnitude.
How do pre-existing immunity and host factors interact to impact influenza vaccine response?
Some prior mechanistic modeling studies show that dose should modulate the effect of an influenza vaccine, but do not make strong predictions about the roles of covariates. Using data from an ongoing cohort study, we examine these predictions and also examine whether other covariates should be included in future models.
Exploring the effect of host factors on the relationship between pre-existing immunity and influenza vaccine response
Mechanistic models suggest that fold change in flu immunity after vaccination should be linearly decreasing with pre-vaccination immunity. However, these models do not account for host factors, such as age. We found that mechanistic model predictions were sometimes supported by the data, and we are working to explore when they are and are not.
How does pre-existing immunity interact with other factors to impact influenza vaccine responses?
Previous mechanistic models predict that fold change in influenza antibody level should have a negative linear relationship with pre-vaccination titer on a log-log scale. Models also predict that higher vaccine doses should have a higher intercept, but parallel slopes. Using vaccine cohort data, we found that the first conclusion was true, but the latter was not always true. Now we are working to understand in which cases the model deviates from expected predictions.