Currently, the epidemic situation regarding the incidence of coronavirus infection COVID−19 in Ukraine continues to be tense. In order to in−depth study of the problem of clinical features, treatment and prevention of this disease, as well as the development of a mathematical model for predicting the severity of its course, 30 patients aged 18 to 85 years were examined. Among the patients there were young and middle−aged people as well as elderly patients with chronic diseases, namely obesity, hypertension, diabetes. The diagnosis of coronavirus infection was confirmed in all the patients by molecular genetic method, i.e. SARS−CoV−2 RNA was isolated, and in 10 patients − IgM + IgG to SARS was determined by immunochromatographic analysis. With COVID−19, young and middle−aged patients have a fairly mild course with a decrease in platelet count by 7 %, erythrocyte sedimentation rate by 48 %, prothrombin by 14 % and D−dimer by 31 %. The construction of regression equations based on trend lines revealed that in elderly patients after treatment there was a further decrease in the level of D−dimer (20 %), an increase in platelet count (30 %), a decrease in white blood cell count (26 %), neutrophils (38 %), increase in lymphocyte levels by 3 times, decrease in erythrocyte sedimentation rate (by 10 %) and prothrombin parameters (by 15 %). Based on cluster and regression analysis, coefficients were calculated for each prognostic function. It was found that the linear dependence and statistically significant effect on the course of COVID−19 in all patients have leukocytes, erythrocyte sedimentation rate and D−dimer. In order to prevent the spread of coronavirus infection in Ukraine COVID−19 in this March, quarantine was introduced throughout the country, which is being extended to this day. There is no doubt about the importance of recommendations for improving anti−epidemic measures to prevent coronavirus infection throughout Ukraine. Key words: coronavirus infection, COVID−19, clinical blood counts, disease prognosis, anti−epidemic measures in Ukraine.