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Introduction: The novel coronavirus infection COVID-19 is a major public health problem worldwide. Several publications show the presence of gastrointestinal (GI) symptoms (nausea, vomiting, and diarrhea) in addition to respiratory disorders.The aim of this study was the monitoring of RNA of COVID-19 pathogen, coronavirus SARS-CoV-2 (Coronaviridae: Coronavirinae: Betacoronavirus; Sarbecovirus) in children hospitalized with acute intestinal infection (AII), with following molecular-genetic characterization of detected strains., Material and Methods: Fecal samples of children with AII hospitalized in infectious hospital of Nizhny Novgorod (Russia) in the period from 01.07.2020 to 31.10.2021 were used as material for the study. Viral RNA detection was performed by real-time polymerase chain reaction (RT-PCR). The nucleotide sequence of S-protein gene fragment was determined by Sanger sequencing., Results and Discussion: SARS-CoV-2 genetic material was detected in 45 out of 2476 fecal samples. The maximum number of samples containing RNA of the virus occurred in November 2020 (detection rate of 12.2%). In 20.0% of cases, SARS-CoV-2 RNA was detected in combination with rota-, noro-, and adenoviruses. 28 nucleotide sequences of S-protein gene fragment complementary DNA (cDNA) were determined. Phylogenetic analysis showed that the studied SARS-CoV-2 strains belonged to two variants. Analysis of the S-protein amino acid sequence of the strains studied showed the absence of the N501Y mutation in the 2020 samples, which is a marker for variants with a high epidemic potential, called variants of concern (VOC) according to the World Health Organization (WHO) definition (lines Alpha B.1.1.7, Beta B.1.351, Gamma P.1). Delta line variant B.1.617.2 was identified in two samples isolated in September 2021., Conclusion: The detection of SARS-CoV-2 RNA in the fecal samples of children with AII, suggesting that the fecal-oral mechanism of pathogen transmission may exist, determines the necessity to optimize its monitoring and to develop an algorithm of actions with patients with signs of AII under the conditions of a novel coronavirus infection pandemic.