Background: Some learned societies of radiology emitted guidelines to limit or rule out chest X-ray in patients management and recommend chest CT-scanner (CCS) as the reference to assess pulmonary injury in suspected or diagnosed Covid19 (SDC) patients with signs of clinical severity. We intend to explore the place of lung ultrasound (LU) imagery to assess lung status in those latter patients, with afterthoughts on the interest of it for quick triage of patients. Methods: eChoVid is a multicentric observational study based on routinely collected data, conducted in 3 emergency units of Assistance Publique des Hopitaux de Paris. 107 SDC patients included between 19.03.2020 and 01.04.2020 had both a LU examination (LU) and a chest CT-scanner (CCS). LU consisted in scoring lesions of 8 chest zones, each scored from 0 to 3, defining a severity Global Score (GS) ranging from 0 to 24. CCS severity score was graded from 0 to 3, according to interstitial pneumonia signs extension. 14 patients had a LU by both an expert and a newly trained physician (NTP). Findings: GS shows good performances to predict CCS severity assessment of Covid19 disease categorized as Normal vs Pathologic, AUC-ROC=0.93, maximal Youden index for GS=1, with 95% sensitivity, 83% specificity. Similar performances were found for CCS categorization Normal or Minimal vs Moderate or Severe, N=90, AUC-ROC= 0.89, maximal Youden index for GS=7, with 86% sensitivity, 78% specificity. Multi-logistic regression model provided a weighted score, relating ultrasound scoring of each chest zone and CT-scanner severity score, with no significant improvement of GS. Good agreement was found between GS assessed by NTP and experts, measured by Bland & Altman method. Interpretation : GS score brings a simple tool to assess lung damages severity in SDC patients. Compared performance results between NTP and expert physician are very preliminary but opens a path towards adoption beyond the scope of ultrasound experts. LU is a good candidate for triage of SDC patients, especially useful when CT-scanners suffer from availability issues related either to overwhelmed requests or poor health infrastructure.