Prevalence Estimation Methods for Time-Dependent Antibody Kinetics of Infected and Vaccinated Individuals: A Markov Chain Approach

by Prajakta Bedekar, Rayanne A. Luke, and Anthony J. Kearsley

Modeling the change in antibody levels post infection or vaccination improves understanding of the time-dependent immune response. Disease or vaccination prevalence in populations and time-dependence simultaneously affect antibody levels, interact non-trivially, and pose considerable modeling challenges. We model transitions from the naïve state to either the infected or vaccinated state using a time-varying stochastic process. This is coupled with a probabilistic framework to describe post-event antibody dynamics. An important result of this work is the design of an unbiased prevalence estimation method. This is a critical step towards analyzing protection from infection or vaccination and improving booster timing recommendations.

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