Rapid Decision Algorithm for Patient Triage during Ebola Outbreaks.

Ardiet DL Nsio J Komanda G Coulborn RM Grellety E Grandesso F Kitenge R Ngwanga DL Matady B Manangama G Mossoko M Ngwama JK Mbala P Luquero F Porten K Ahuka-Mundeke S
Emerging infectious diseases 2024 Nov ; 30(11); . doi: 10.3201/eid3011.231650. Epub 2024 10 24
Algorithm Democratic Republic of the Congo Ebola clinical signs contact epidemics exposure outbreaks predictors symptomatology symptoms triage

Abstract

The low specificity of Ebola virus disease clinical signs increases the risk for nosocomial transmission to patients and healthcare workers during outbreaks. Reducing this risk requires identifying patients with a high likelihood of Ebola virus infection. Analyses of retrospective data from patients suspected of having Ebola virus infection identified 13 strong predictors and time from disease onset as constituents of a prediction score for Ebola virus disease. We also noted 4 highly predictive variables that could distinguish patients at high risk for infection, independent of their scores. External validation of this algorithm on retrospective data revealed the probability of infection continuously increased with the score.