Relevance.Despite the decrease in the absolute indicators of emergencies, accidents and catastrophes, and the reduction of related injuries in Russia, there is still a high level of mortality and injuries associated with the impact of external causes, surpassing similar indicators in the leading countries of the world. Therefore, research to optimize the provision of first aid and emergency medical care to the injured is needed.Intention.To conduct a content analysis of domestic articles within the branch of knowledge “Disaster Medicine. Service of Disaster Medicine” and to reveal their scientometric indicators.Methodology.The object of research was an electronic database of domestic publications (scientific articles, reviews and brief reports) indexed in the Russian Scientific Citation Index in 2005–2017.Results and Discussion.During the electronic search, 2431 publications on the disaster medicine were found. The polynomial trend with a high coefficient of determination (R2 = 0.90) showed an increase in indicators. Over the research period, the average annual number of publications was (186 ± 23) articles. The general provisions of the disaster medicine were covered in 10.1 % , tasks and organization of the service of disaster medicine – in 5.8 %. forecasting and modeling of health consequences in emergencies – in 16.6 %, organization of health care – in 25.3 %, medical care and treatment of injured – in 13.5 %, medical control, examination and rehabilitation of rescuers – in 4.1 % , training of specialists in disaster medicine – in 9.4 %, biological problems – in 5.3%, psychiatric and psychological aspects – in 9.9 % of articles. The average weighted impact-factor of the journals in which the articles were published is 0.302, the average number of articles per 1 co-author was 0.40, the average number of citations per article is 1.54, for 1 co-author 0.55, the number articles quoted at least once, 43.8 %, the number of self-citations, 19.2 %, the Hirsch index was 19. The median of the chronology of citations was 4.5 years. Scientometric analysis of articles on leading authors, journals and organizations was conducted.Conclusion. The performed analysis helps to optimize scientific research on disaster medicine. The electronic database of the Scientific Electronic Library provides great information opportunities, for example, on May 12, 2018, 70.5 % of articles within the created collection of publications had the full text, including 60.2% of articles that were provided free charge to registered readers of the library.
Relevance. Heavy rainfall in June July 2019 and a rise of water levels in rivers caused flooding in the Irkutsk region. About 11 thousand houses, 49 road sections were flooded, 22 bridges were destroyed and damaged. Over 45 thousand people were affected by the flood, 25 people died, 6 went missing. In the areas of disaster, emergency regime was declared. 10 meter dam on the Iya River was broken, the most dangerous flood was in the Tulun town, Irkutsk Region. The powerful pressure of the river, sweeping and destroying everything in its path, surged into the town. Residential houses and farm buildings floated along the river, breaking against a bridge. On June 29 at 2 p.m. there was a maximum water level of 13 m 87 cm, which was almost 2 times higher than the critical level, after which the water began to decline. The flood divided the city into 2 parts.Intention is to present the results of emergency recovery work and analyze the medical support during the flood elimination in the Irkutsk region.Methodology. The airmobile group (AMG) of the Tula Rescue Center of the EMERCOM of Russia was formed in the amount of 100 persons to participate in the emergency response. From July 6 to August 15, 2019 military personnel of AMG performed emergency recovery work during a flood in the Tulun town, Irkutsk Region.Results and analysis. Due to the unfavorable sanitary and epidemiological situation in the area of emergency response, military personnel of the AMG were vaccinated against hepatitis A. During emergency recovery operations, 4941 dump trucks (123,525 m3) of solid waste were removed, 122 houses and adjoining territories were cleared from household rubbish as a result of a bypass and targeted assistance to the population, 210 destroyed residential buildings and 345 outbuildings were dismantled, 390 m of drainage trenches were dug, 23,396 m3 of water was pumped out from courtyards and streets, 10 tons of humanitarian aid were loaded, transported and unloaded, and other works. On August 13, 2019, AMG employees were involved in a rescue operation with the subsequent air medical evacuation of the victim. 47 cases of treatment of the affected people within primary health care were registered. The general morbidity (help seeking) of AMG military personnel was 1190 ‰, i.e. each soldier turned for medical help 1.2 times. In the structure of the general morbidity, the 1st rank was taken by diseases of the skin and subcutaneous tissue (XII chapter according to ICD 10), the 2nd – diseases of the respiratory system (X chapter), the 3rd – diseases of the digestive system (XI chapter). The prevaling cases of treatment were infected foot and leg scuffs, acute respiratory infections, acute toothache, enterocolitis.Conclusion. An algorithm for cooperation with local authorities of the State system for the prevention and liquidation of emergency situations in the territory of the Angara region has been developed. The experience gained in organizing medical support for military personnel of the Tula Rescue Center of the EMERCOM of Russia will allow detailed planning of the forces and means of the medical service in the formation of an airmobile group.
Relevance. The study of the global pool of theses and dissertations in disaster medicine can reflect the general structure of innovative research and will assist in reviewing current scientific literature in this field of knowledge. Intention is to analyze the structure and dynamics of the number of foreign dissertations in disaster medicine and compare them with similar indicators of Russian dissertations. Methodology. The object of study is the global pool of dissertations presented in the ProQuest Dissertations & Theses Global electronic database, Health & Medicine section, for the period 1992-2020 and an array of domestic dissertations in the scientific specialty 05.26.02 “Safety in emergency situations” (medical, biological and psychological sciences) for 1992-2020. The quantitative indicators of foreign and Russian dissertations in emergency medicine were compared. Results and Discussion. The electronic search made it possible to find 28,423 foreign doctoral (PhD) dissertations in the problems of disaster medicine. The polynomial trend with a very high coefficient of determination (R2 = 0.97) shows an increase in the annual number of dissertations for the period 1992-2020. The average annual number of dissertations in the period under review was 980 ± 386. Dissertations described general provisions (4.7 %), tasks and organization of the disaster medicine service (8.3 %), forecasting and modeling of the health consequences of emergencies (4.8 %), organization of medical-sanitary support (18.5 %), provision of medical care and treatment of victims (14.9 %), medical control, examination and rehabilitation of rescuers (2.3 %), training of disaster medicine specialists (12.8 %), biological issues (6.2 %), psychiatric and psychological security problems (28.1 %). The general array of dissertations was analyzed by leading countries and universities. Quantity and scope of foreign dissertations on the problems of disaster medicine were compared with those of Russian dissertations over time. Conclusion. More than 95 % of the analyzed pool of disaster medicine dissertations in the ProQuest Dissertations & Theses Global database are published in full text. Our study makes it possible to optimize scientific research in the field of disaster medicine and also shows possible approaches to dissertation analysis when preparing own manuscripts.
Relevance. Artificial intelligence is one of the fastest growing areas in the field of computer technology. Intention is to provide an overview of modern artificial intelligence technologies applied in various branches of Safety in Emergency Situations and summarize modern emergency management systems. Methodology. The object of the study was research on safety in emergency situations, presented in the global stream of scientific articles published in 2005–2020 and indexed in the abstract-bibliographic databases Scopus and the Russian Science Citation Index. Results and discussion. A review of modern artificial intelligence technologies made it possible to create a generalized classification of its systems used in various branches of security in emergency situations, including for preventing the development of crisis situations, and to show the main examples of use in this branch of knowledge. Conclusion. A promising direction in the use of AI systems is the classification of texts, in particular, scientific articles and other specialized texts on a specific research topic, which can be carried out using machine learning methods. An important role is given to text pre-processing technologies, or tokenization.
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