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Prevalence estimation methods for time-dependent antibody kinetics of infected and vaccinated individuals: a graph-theoretic approach
Immune events such as infection, vaccination, and a combination of the two result in distinct time-dependent antibody responses in affected individuals.
Minimal Assumptions for Optimal Serology Classification: Theory and Implications for Multidimensional Settings and Impure Training Data
This leads us to formulate an optimization problem that: (i) embeds the data in a parameterized, curved space; (ii) classifies samples based on their position relative to a coordinate axis; and (iii) subsequently optimizes the space by minimizing the empirical classification error of pure training data, for which the classes are known.
Optimal classification and generalized prevalence estimates for diagnostic settings with more than two classes
The classification process is challenging when the relative fraction of the population in each class, or generalized prevalence, is unknown.
Prevalence Estimation and Optimal Classification Methods to Account for Time Dependence in Antibody Levels
Serology testing can identify past infection by quantifying the immune response of an infected individual providing important public health guidance.
Modeling in higher dimensions to improve diagnostic testing accuracy: theory and examples for multiplex saliva-based SARS-CoV-2 antibody assays
We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics.
