Increasing test specificity without impairing sensitivity: lessons learned from SARS-CoV-2 serology.

Thomas PerkmannThomas KollerNicole Perkmann-NageleMaria Ozsvar-KozmaDavid EyrePhilippa MatthewsAbbie BownNicole E StoesserMarie-Kathrin BreyerRobab Breyer-KohansalOtto C BurghuberSlyvia HartlDaniel AletahaDaniela SieghartPeter QuehenbergerRodrig MarculescuPatrick MucherAstrid RadakovicsMiriam KlausbergerMark DuerkopBarba HolzerBoris HartmannRobert StrasslGerda LeitnerFlorian GrebienWilhelm GernerReingard GrabherrOswald F WagnerChristoph J BinderHelmuth Haslacher

Published in: Journal of clinical pathology (2022)

For SARS-CoV-2 serology, SIT² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.

Keyphrases

sars cov
infectious diseases
respiratory syndrome coronavirus
climate change
machine learning
deep learning
coronavirus disease
structural basis