Abstract: Objective To identify the biomarkers as early warning signals for severe COVID-19. Methods We retrospectively analyzed the clinical data of 63 patients with COVID-19 from Hubei Provincial Hospital of Integrated Chinese and Western Medicine, including 32 moderate cases and 31 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory test results were compared between the two groups. Logistic regression analysis was performed to identify the factors that predicted the severity of COVID-19. The receiver-operating characteristic curve (ROC) of neutrophil/lymphocyte ratio (NLR) was calculated, and the area under the curve (AUC) was determined to estimate the optimal threshold of NLR for predicting severe cases of COVID-19. Results The patients with moderate and server COVID-19 showed significant differences in the rate of diabetes, NLR, serum amyloid A (SSA), C-reactive protein (CRP) and serum albumin (ALB) levels (P<0.05). The co- morbidity of diabetes, NLR, SSA and CRP were found to positively correlate and ALB to inversely correlate with the severity of COVID-19 (P<0.05). Multivariate logistic regression analysis showed that NLR was an independent risk factor for severe COVID-19 (OR=1.264, 95%CI: 1.046-1.526, P=0.015) with an AUC of 0.831 (95%CI: 0.730-0.932), an optimal diagnostic threshold of 4.795, a sensitivity of 0.839, and a specificity of 0.750. Conclusion An increased NLR can serve as an early warning signal of severe COVID-19.