80 research outputs found
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.
Individual immune responses are time-dependent, which is reflected in antibody
measurements. Moreover, the probability of obtaining a particular measurement
changes due to prevalence as the disease progresses. Taking into account these
personal and population-level effects, we develop a mathematical model that
suggests a natural adaptive scheme for estimating prevalence as a function of
time. We then combine the estimated prevalence with optimal decision theory to
develop a time-dependent probabilistic classification scheme that minimizes
error. We validate this analysis by using a combination of real-world and
synthetic SARS-CoV-2 data and discuss the type of longitudinal studies needed
to execute this scheme in real-world settings.Comment: 29 pages, 11 figure
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