Differentiating COVID-19 and dengue from other febrile illnesses in co-epidemics: Development and internal validation of COVIDENGUE scores. Issue 45 (January 2022)

• Record Type: Journal Article
• Authors: Gérardin, Patrick; Maillard, Olivier; Bruneau, Léa; Accot, Frédéric; Legrand, Florian; Poubeau, Patrice; Manaquin, Rodolphe; Andry, Fanny; Bertolotti, Antoine; Levin, Cécile
• Is Part Of: Travel medicine and infectious disease. Issue 45(2022)
• Publication Date: 2022-01
• Subjects: COVID-19 -- SARS-CoV-2 -- Dengue -- Arbovirus -- Cohort study -- Prediction model; Travel -- Health aspects -- Periodicals; Communicable diseases -- Periodicals; Tropical medicine -- Periodicals; 610.5
• DOI: 10.1016/j.tmaid.2021.102232
• Languages: English
• ISSNs: 1477-8939

Abstract

Abstract: Objectives: The purpose of this cohort study was to develop two scores able to differentiate coronavirus 2019 (COVID-19) from dengue and other febrile illnesses (OFIs). Methods: All subjects suspected of COVID-19 who attended the SARS-CoV-2 testing center of Saint-Pierre hospital, Reunion, between March 23 and May 10, 2020, were assessed for identifying predictors of both infectious diseases from a multinomial logistic regression model. Two scores were developed after weighting the odd ratios then validated by bootstrapping. Results: Over 49 days, 80 COVID-19, 60 non-severe dengue and 872 OFIs were diagnosed. The translation of the best fit model yielded two scores composed of 11 criteria: contact with a COVID-19 positive case (+3 points for COVID-19; 0 point for dengue), return from travel abroad within 15 days (+3/-1), previous individual episode of dengue (+1/+3), active smoking (−3/0), body ache (0/+5), cough (0/-2), upper respiratory tract infection symptoms (−1/-1), anosmia (+7/-1), headache (0/+5), retro-orbital pain (−1/+5), and delayed presentation (>3 days) to hospital (+1/0). The area under the receiver operating characteristic curve was 0.79 (95%CI 0.76–0.82) for COVID-19 score and 0.88 (95%CI 0.85–0.90) for dengue score. Calibration was satisfactory for COVID-19 score and excellent for dengue score. For predicting COVID-19, sensitivity was 97% at the 0-point cut-off and specificity 99% at the 10-point cut-off. For predicting dengue, sensitivity was 97% at the 3-point cut-off and specificity 98% at the 11-point cut-off. Conclusions: COVIDENGUE scores proved discriminant to differentiate COVID-19 and dengue from OFIs in the context of SARS-CoV-2 testing center during a co-epidemic. Highlights: Dengue was more symptomatic at presentation than COVID-19 during a co-epidemic. Anosmia is a strong predictor of COVID-19, body ache a strong predictor of dengue. COVIDENGUE scores can differentiate COVID-19 from dengue and other febrile illnesses. A good calibration of both scores is essential for individual prediction purposes. Classification plots should be used to guide decision making in validation studies.