title: Predicting Ebola infection: A malaria-sensitive triage score for Ebola virus disease.
abstract: The non-specific symptoms of Ebola Virus Disease (EVD) pose a major problem to triage and isolation efforts at Ebola Treatment Centres (ETCs). Under the current triage protocol, half the patients allocated to high-risk "probable" wards were EVD(-): a misclassification speculated to predispose nosocomial EVD infection. A better understanding of the statistical relevance of individual triage symptoms is essential in resource-poor settings where rapid, laboratory-confirmed diagnostics are often unavailable.
  
  
  
  This retrospective cohort study analyses the clinical characteristics of 566 patients admitted to the GOAL-Mathaska ETC in Sierra Leone. The diagnostic potential of each characteristic was assessed by multivariate analysis and incorporated into a statistically weighted predictive score, designed to detect EVD as well as discriminate malaria. Of the 566 patients, 28% were EVD(+) and 35% were malaria(+). Malaria was 2-fold more common in EVD(-) patients (p<0.05), and thus an important differential diagnosis. Univariate analyses comparing EVD(+) vs. EVD(-) and EVD(+)/malaria(-) vs. EVD(-)/malaria(+) cohorts revealed 7 characteristics with the highest odds for EVD infection, namely: reported sick-contact, conjunctivitis, diarrhoea, referral-time of 4-9 days, pyrexia, dysphagia and haemorrhage. Oppositely, myalgia was more predictive of EVD(-) or EVD(-)/malaria(+). Including these 8 characteristics in a triage score, we obtained an 89% ability to discriminate EVD(+) from either EVD(-) or EVD(-)/malaria(+).
  
  
  
  This study proposes a highly predictive and easy-to-use triage tool, which stratifies the risk of EVD infection with 89% discriminative power for both EVD(-) and EVD(-)/malaria(+) differential diagnoses. Improved triage could preserve resources by identifying those in need of more specific differential diagnostics as well as bolster infection prevention/control measures by better compartmentalizing the risk of nosocomial infection.
authors.affiliation: GOAL Global, Dublin, Ireland.|Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
authors.forename: Mary-Anne
authors.identifier: 0000-0002-8826-3870
authors.initials: MA
authors.lastname: Hartley
authors.affiliation: GOAL Global, Dublin, Ireland.
authors.forename: Alyssa
authors.initials: A
authors.lastname: Young
authors.affiliation: GOAL Global, Dublin, Ireland.
authors.forename: Anh-Minh
authors.initials: AM
authors.lastname: Tran
authors.affiliation: GOAL Global, Dublin, Ireland.
authors.forename: Harry Henry
authors.initials: HH
authors.lastname: Okoni-Williams
authors.affiliation: GOAL Global, Dublin, Ireland.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Suma
authors.affiliation: GOAL Global, Dublin, Ireland.
authors.forename: Brooke
authors.initials: B
authors.lastname: Mancuso
authors.affiliation: GOAL Global, Dublin, Ireland.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Al-Dikhari
authors.affiliation: Centre for Clinical Epidemiology, Institute of Social and Preventive Medicine, Lausanne, Switzerland.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Faouzi
mesh_terms: D029043:Ebolavirus / Q000235:genetics / Q000302:isolation & purification* / Q000502:physiology; D019142:Hemorrhagic Fever, Ebola / Q000175:diagnosis* / Q000821:virology; D006801:Humans; D008288:Malaria / Q000175:diagnosis* / Q000821:virology; D012189:Retrospective Studies; D012807:Sierra Leone; D014218:Triage / Q000379:methods*