Rapid Decision Algorithm for Patient Triage during Ebola Outbreaks
Denis-Luc Ardiet
1 , Justus Nsio
1, Gaston Komanda, Rebecca M. Coulborn, Emmanuel Grellety, Francesco Grandesso, Richard Kitenge, Dolla L. Ngwanga, Bibiche Matady, Guyguy Manangama, Mathias Mossoko, John K. Ngwama, Placide Mbala, Francisco Luquero, Klaudia Porten, and Steve Ahuka-Mundeke
Author affiliation: Epicentre, Paris, France (D.-L. Ardiet, G. Komanda, R.M. Coulborn, E. Grellety, F. Grandesso, F. Luquero, K. Porten); Ministry of Health, Kinshasa, Democratic Republic of the Congo (J. Nsio, R. Kitenge, D.L. Ngwanga, B. Matady, M. Mossoko, J.K. Ngwama); Médecins Sans Frontières France, Paris (G. Manangama); Institut National de la Recherche Biomédicale, Kinshasa (P. Mbala, S. Ahuka-Mundeke); University of Kinshasa, Kinshasa (S. Ahuka-Mundeke)
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Figure 1
Figure 1. Performance of a rapid decision algorithm for patient triage during Ebola outbreaks (version 4.2, Ebola virus disease [EVD] prediction score only) for different decision thresholds to predict Ebola infection in a population of EVD-suspected patients in Democratic Republic of the Congo during epidemics in 2018–2019, with and without stratification by time-to-presentation (days). A) Sensitivity; B) specificity; C) positive predictive value; D) negative predictive value; E) positive likelihood ratio; F) negative likelihood ratio.
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