MATERIALS AND METHODS: Additional analytical blocks on comparative and dynamic analysis of morbidity by the groups of nosologies were developed using the software meeting the general concept of the software complex (JavaScript, PHP, and others) and integrated into a new version of the Web application "Epidemiological Atlas of Russia. Territory of the Federal District". The initial data including information by the groups of diseases were converted into a set of interrelated tables with their further integration into the database of a new version of the Atlas under the control of a free relational MySQL database management system.

RESULTS: The existing classifications of nosologic forms and the search for additional characteristics, potentially forming the groups of nosologies, have been analyzed and the current database of the Epidemiological Atlas has been optimized. The algorithms for obtaining and evaluating epidemiological indicators in the new analytical blocks for estimating cumulative morbidity by the nosologic groups were designed. There were created original analytical modules "Comparative analysis of morbidity by the groups of nosologies" and "Dynamic analysis of morbidity by the groups of nosologies" for the Web application "Epidemiological Atlas of Russia. Territory of Federal District" for the comparative and dynamic morbidity analysis based on the groups of nosologies in the administrative-territorial subject units, in the district subjects, and in the district as a whole, with the possibility of information detailing. The materials based on the database queries contain temporal (calendar month) and spatial detailing (administrative-territory unit of the Russian Federation subject). All materials may be exported as tables, graphs, or maps in various formats (.xls, .pdf, .csv, .png, .jpeg, .svg). Since the databases of the current epidemiological atlases of the Volga Federal District and Russia are universal, the mechanisms of processing tables and queries are identical providing the possibility of using the developed approaches employed in the Epidemiological Atlas of Russia or atlases of other federal districts in case of replicating a new Web application version. New analytical blocks may extend notions on the incidence of current infectious diseases and reveal characteristic regional features, facilitate more exact scientifically grounded proposals for decision-making by the executive authorities and timely taking preventive and anti-epidemic measures.

MATERIALS AND METHODS: We studied the samples of the pharyngeal mucosa smears taken from children aged 1-15 years with X-ray confirmed pneumonia. The selection of DNA probes for specific detection of community-acquired pneumonia pathogens (S. pneumoniae, H. influenzae, M. pneumoniae, C. pneumonia, and L. pneumophila) and development of the microarray design were carried out using the disprose program. The nucleotide sequences of pathogens were obtained from NCBI Nucleotide database. In the research we used CustomArray microarrays (USA). For a pooled sample containing S. pneumoniae and H. influenzae DNA, we performed a sequential selection of the best combinations of hybridization parameters: DNA fragment size, DNA amount, hybridization temperature. The selection criteria were: the percentage of effective probes with a standardized hybridization signal (SHS) ≥3 Z, and the excess of SHS levels of effective specific probes compared to SHS of effective nonspecific probes. We selected the probes to detect of S. pneumoniae and H. influenzae characterized by an effective hybridization signal under optimal conditions. The developed microarray was tested under the selected conditions on clinical samples containing S. pneumoniae or H. influenzae DNA. Using ROC analysis there were established threshold values for the signals of specific probes at optimal sensitivity points and the test specificity, the excess of which was interpreted as the evidence of pathogen presence in a sample.

RESULTS: A microarray design included 142 DNA probes to detect S. pneumoniae, H. influenzae, M. pneumoniae, C. pneumoniae, and L. pneumophila, the probes being synthesized onto slides. Using the example of clinical samples containing S. pneumoniae and/or H. influenza DNA, we selected optimal parameters for DNA hybridization on microarrays, which enabled to identify bacterial pathogens of community-acquired pneumonia with sufficient efficiency, specificity and reproducibility: the amount of hybridized DNA was 2 μg, the DNA fragment size: 300 nt, hybridization temperature: 47°C. There was selected a list of probes for specific detection of S. pneumoniae and H. influenzae characterized by an effective hybridization signal under the identified conditions. We determined the threshold values of standardized probe signals for specific detection of S. pneumoniae (4.5 Z) and H. influenzae (4.9 Z) in clinical samples.

MATERIALS AND METHODS: The GIS software package "Epidemiological Atlas of Russia" was designed for data monitoring, epidemiological analysis, and cartographic visualization and was implemented as a web resource consisting of a web application, a package administration module, and a database management system. The following development tools were used to create the package: JavaScript, PHP, additional mapping libraries (Leaflet, OpenStreetMap), MySQL database management systems, Visual Basic .NET. The primary information for the database was taken from official federal statistical observation forms No.1 and No.2 "Information on infectious and parasitic diseases".

RESULTS: Analytical methods and GIS technologies used in epidemiological practice were evaluated, optimal technical solutions based on the experience of developing the "Epidemiological Atlas of the Volga Federal District" were selected. A versatile database structure was designed and developed to create an array of input and output statistical values of an epidemiological nature. Original algorithms were created to obtain and evaluate epidemiological indicators. Web application "Epidemiological Atlas of Russia" was developed to present, analyze, and visualize information on infectious and parasitic diseases in the subjects of a district, federal districts, and the Russian Federation as a whole. It allows to work with report forms of the Ministry of Health to organize federal statistical monitoring in the field of health protection and with laboratory studies results to create thematic modules providing detailed information on individual nosologies. Initial data were temporally broken down by months, and spatially, by Russian Federation subjects. All visualization results were dynamically updated and generated based on user's interactive request.