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Introduction: Hospital-acquired bacterial superinfections in COVID-19 patients are one of the main reasons of a severer course of the disease, a higher risk of adverse outcomes, and, consequently, a longer hospital stay. Much attention is, therefore, paid to the study of genetic markers enabling identification of clonal relationships between different isolates of the causative agents of bacterial co-infections, which, in their turn, help distinguish between hospital- and community-acquired cases of infectious diseases. Objective: To study the genetic diversity and clonal relationships of A. baumannii and P. aeruginosa isolated from patients with a novel coronavirus disease (COVID-19) in Rostov-on-Don. Materials and methods: We tested biological specimens from 217 in- and outpatients with community-acquired pneumonia in the city of Rostov-on-Don. Whole-genome sequencing of A. baumannii and P. aeruginosa strains was performed using a MiSeq sequencer (Illumina, USA). SNP markers were selected using proprietary software written in Java and Python. Cluster analysis and dendrogram construction were performed using the author's software using the UPGMA method. The MEGA 5 software was used to build the dendrogram. Results: We established the spectrum of bacteria causing the development of secondary infection associated with COVID-19. Results of the whole-genome sequencing of 10 pneumonia pathogens isolated from patients with the novel coronavirus disease revealed clonality of individual strains. The nosocomial origin of two isolates of P. aeruginosa and two of A. baumannii was demonstrated and confirmed by the analysis of their plasmid composition. Secondary bacterial infection in COVID-19 patients may be attributed to the pathological development of the dominant microflora of the upper respiratory tract mucosa, which provides normal biocenosis in healthy people, or non-compliance with basic principles of hospital hygiene and infection control precautions. Conclusion: The research helped determine the etiological structure of pneumonia in patients with COVID-19. Whole-genome sequencing and the following bioinformatic analysis revealed the nosocomial origin of a number of strains of P. aeruginosa and A. baumanii.

In 2020, the COVID-19 pandemic contributed to the epidemiology of respiratory tract infections. The importance of timely differential diagnosis of COVID-19 and seasonal acute respiratory diseases is hard to overestimate. Patients with the novel coronavirus disease are at risk of developing hospital-acquired pneumonia. The analysis of specific features of circulation of various strains of pathogens of nosocomial infections resistant to antibacterial chemotherapeutic agents is relevant. Our objective was to study the etiological structure of community-acquired pneumonia during the epidemic spread of COVID-19 and to assess risks of developing healthcare-associated pneumonia. Materials and methods. Biological specimens from 446 inpatients and outpatients diagnosed with community-acquired pneumonia in the city of Rostov-on-Don were tested. Verification of respiratory viruses, including RNA of SARS-CoV-2, M. pneumoniae, C. pneumoniae, and L. pneumophila, was performed by polymerase chain reaction in nasopharyngeal swab specimens. Bacteriological analysis of sputum was carried out using differential diagnostic media, and isolated pathogens were then identified by time-of-flight mass spectrometry on an Autoflex instrument (Bruker Daltonics GmbH, Germany) using the MALDI BioTyper R 3.0 software. Results and discussion. In December 2020, the proportion of SARS-CoV-2 positive test results among patients diagnosed with community-acquired pneumonia was 35.6 %. The frequency of mixed viral infections in patients with a confirmed diagnosis of COVID-19 was not significantly different from that in patients tested negative (25.9 % and 26.2 %, respectively). The microbiota in pneumonia unrelated to SARS-CoV-2 was dominated by Candida fungi and plasma-coagulating staphylococci while cultures of non-fermenting gram-negative bacteria were significantly more often isolated from COVID-19 cases. Secondary infection presumably induced by environmental contamination or disease transmission from healthcare personnel was registered in 51.6 % of inpatients. Transmission of nosocomial infections between patients was not observed.

Summary. Introduction: As of today, acute viral upper respiratory tract infections (URTIs) remain the most common diseases in the world and the Russian Federation and one of the most important problems of national health care. The objective of our work was to study the dynamics and intensity of the epidemic process of influenza and other URTIs in the Russian Federation and Rostov Region over a thirty-year period and to establish the main features of the disease incidence in the Rostov Region. Materials and methods: We analyzed data of annual State Reports on Sanitary and Epidemiological Wellbeing of the Population in the Russian Federation and Statistical Form No. 2 on information about infectious and parasitic diseases for the period 1990–2019 and data on the size of population using StatSoft STATISTICA 6.1.478 Russian, Microsoft Excel, and NextGIS QGIS software. Results: We found that in 1990–1999, 2000–2009, and 2010–2019, regional URTI rates tended to decrease in each subsequent decade compared to the previous one. The long-term incidence rate of URTIs in the Rostov Region was 16,099.2 ± (2.045 × 384.2) ‰оо, lower than the Russian average rate of 19,710.3 ± (2.045 × 326.4) (p = 0.05). The amplitude of fluctuations in the incidence was 8,015.4 ‰оо and 7,619.6 ‰оо in the Rostov Region and the Russian Federation, respectively. Until 1997, regional incidence rates were comparable to the national averages but demonstrated an upward trend since the year 2000. We revealed unevenness of the course of the epidemic process related to cyclicity, with an increase in the duration of cycles since 1998. It was determined that the regional incidence of influenza was significantly lower than the national average and had a tendency to decrease. The long-term influenza rate in the Rostov Region was 412.4 ± (2.045 × 131.3) (p = 0.05) or almost three times lower than that in the country 1,553.0 ± (2.045 × 301.2) (p = 0.05). The dynamics of influenza incidence in the Rostov Region also had a cyclical course with a smaller amplitude of fluctuations (3,215.1 ‰оо) than in the Russian Federation (5,164.8 ‰оо). The duration of epidemic cycles in 1990–1998 and 2002–2012 was two years but we noted a three-year cycle in 1999–2001. We established a correlation between influenza and URTI rates and population density in regional cities and various age groups: the highest URTI rates (74.9 %) were registered in children between two to 17 years of age while 52.5 % of influenza cases were adults (aged 18+). Conclusion: The established characteristics of the development of the epidemic process of influenza and URTIs in the Rostov Region prove the necessity of a differentiated approach to organizing and implementing comprehensive preventive measures within optimization of epidemiological surveillance of these diseases, and can also serve as basic criteria for disease prediction.

The complex of actions is presented carried out by the Local Administration of Russian Federal Consumer Rights Protection and Human Welfare Supervision Service in the Rostov Region together with the Ministry of Health of the Rostov Region and Center of Hygiene and Epidemiology in the Rostov Region, aimed at the prevention of influenza and acute respiratory viral infections and including: organizational work, results of epidemiological surveillance during interepidemic and epidemic periods with the epidemiological situation assessment, managerial decision-making on the basis of the results obtained, as well as working with reference-centers. The epidemic rise of incidence in the season of 2015 - 2016 was more intensive judging by the majority of characteristics in comparison with the previous period. The main etiological agent of infection was influenza virus A(H1N1)pdm09 characterized by the early onset of epidemic rise from mid-January 2016, the lesser engagement of children from 3 to 6 years of age into epidemic process but maximal engagement of schoolchildren aged 7 - 14, by the higher rate of disease development, higher per cent of hospitalized with influenza diagnosis, and maximal number of deceased at the peak of epidemic.