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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">proanaris</journal-id><journal-title-group><journal-title xml:lang="ru">Проблемы анализа риска</journal-title><trans-title-group xml:lang="en"><trans-title>Issues of Risk Analysis</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1812-5220</issn><issn pub-type="epub">2658-7882</issn><publisher><publisher-name>ФГБУ ВНИИ ГОЧС (ФЦ)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.32686/1812-5220-2020-17-4-10-21</article-id><article-id custom-type="elpub" pub-id-type="custom">proanaris-421</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>РИСК САНИТАРНО-ЭПИДЕМИОЛОГИЧЕСКИЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>SANITARY AND EPIDEMIOLOGICAL RISK</subject></subj-group></article-categories><title-group><article-title>Иерархическое моделирование эпидемической опасности распространения нового коронавируса COVID-19</article-title><trans-title-group xml:lang="en"><trans-title>Hierarchical Epidemic Risk Modeling of Spreading New COVID-19 Coronavirus</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7596-7780</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Черкашин</surname><given-names>А. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Cherkashin</surname><given-names>A. K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Черкашин Александр Константинович: доктор географических наук, профессор, главный научный сотрудник, заведующий лабораторией теоретической географии</p><p>Researcher ID Web of Science: K-2418-2017</p><p>Количество публикаций: 140</p><p>Область научных интересов: теория и практика географических исследований и моделирования</p><p>Контактная информация: Адрес: 664033, г. Иркутск, ул. Улан-Баторская, д. 1</p></bio><bio xml:lang="en"><p>Alexander K. Cherkashin</p></bio><email xlink:type="simple">akcherk@irnok.net</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Институт географии им. В. Б. Сочавы СО РАН</institution><country>Россия</country></aff><aff xml:lang="en"><institution>V. B. Sochava Institute of geography SB RAS</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>29</day><month>08</month><year>2020</year></pub-date><volume>17</volume><issue>4</issue><fpage>10</fpage><lpage>21</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Черкашин А.К., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Черкашин А.К.</copyright-holder><copyright-holder xml:lang="en">Cherkashin A.K.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.risk-journal.com/jour/article/view/421">https://www.risk-journal.com/jour/article/view/421</self-uri><abstract><p>Предмет исследования — многоуровневое изучение территориальных особенностей опасности чрезвычайных ситуаций, анализ оперативной информации и управление рисками различного происхождения. Разрабатывается тематическая модель текущего эпидемического процесса коронавируса COVID-19 в терминах теории надежности. Модель базируется на методах параметрического вариационного и иерархического моделирования, где учитывается подобие экспоненциальных функций связи характеристик опасной ситуации на разных организационных уровнях.</p><p>Цель работы — выявление особенностей реакции населения разных стран на противоэпидемические меры органов государственного управления рисками.</p><p>Методы исследования основаны на информационной технологии проектирования и аппроксимации кривых и поверхностей функциями различной сложности, что реализуется средствами фрактального параметрического моделирования пространственных объектов и позволяет путем варьирования параметров и функций их связей создавать новые графические конфигурации. Расчеты проводятся в  смещенных относительно средовых значений переменных, что дает возможность принять во внимание территориальную специфику управления параметрами интенсивности отказов (риска заболевания). В сравнительно-статистическом анализе преимущество моделирования определено относительностью показателей надежности, что позволяет нивелировать страновые особенности сбора эпидемиологических данных. Сложность иерархических моделей выражается в кратности вложения (суперпозиции) экспоненциальных функций. В модели эпидемии в данном случае не регулируется интенсивность заражения (риски заболевания), а снижается приемлемый риск инфицирования путем организационного давления на величину этого риска. Эффективность воздействия оценивается по значениям устойчивых показателей управляемости, индивидуальным для каждой территории. Высокую управляемость поведением населения в условиях начавшейся эпидемии продемонстрировали власти Китая, средний уровень свойственен западным странам со сходными тенденциями развития пандемии. Российское общество показало низкую управляемость при высокой степени государственной готовности к борьбе с пандемией.</p></abstract><trans-abstract xml:lang="en"><p>The subject of the research are a multi-level study of the territorial characteristics of emergency situations, analysis of operational information, and risk management of various origins. A topic model of the current COVID-19 coronavirus epidemic process have been developed in terms of reliability theory. The model is based on the methods of parametric hierarchical and variational modeling, which takes into account the similarity of exponential functions of the relationship between the parameters of the situation at different organizational levels.</p><p>The objective of the work is to identify the characteristics of the reaction of the population of different countries to anti-epidemic measures of public risk management.</p><p>The research methods are based on information technology for designing and approximating curves and surfaces with functions of various complexity, which is implemented by means of fractal parametric modeling of spatial objects and allows you to create new graphical confi gurations by varying the parameters and functions of their connections. Calculations are performed in variables that are biased relative to the environmental values, which makes it possible to take into account the territorial specifi cs of managing the parameters of the failure rate (risk of disease). In comparative statistical analysis, the advantage of this modeling is related to the relativity of reliability indicators, which makes it possible to eliminate country-specific features of epidemiological data collection. The complexity of hierarchical models is expressed in the multiplicity of embedding (superposition) of exponential functions. The model of the epidemic does not regulate the intensity of infection (disease risk), but reduces the acceptable risk of infection by organizational pressure on the magnitude of this risk. The effectiveness of the impact is assessed by the values of stable manageability indicators, which is individual for each territory. The Chinese authorities demonstrated high manageability of the population's behavior in the conditions of the beginning of the epidemic. The average manageability level is typical for Western countries with similar trends in the development of the pandemic. Russian society has shown low manageability with a high degree of state readiness to fight the pandemic.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>демографическая реакция</kwd><kwd>управление риском заражения коронавирусом</kwd><kwd>параметрическая аппроксимация</kwd><kwd>иерархическое моделирование</kwd><kwd>теория надежности</kwd><kwd>приемлемый риск</kwd></kwd-group><kwd-group xml:lang="en"><kwd>demographic response</kwd><kwd>risk management of coronavirus infection</kwd><kwd>parametric approximation</kwd><kwd>hierarchical modeling</kwd><kwd>reliability theory</kwd><kwd>acceptable risk</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено за счет средств государственного задания АААА-А17-117041910167-0.</funding-statement><funding-statement xml:lang="en">The research is executed at the expense of means of the state AAAA-A17-117041910167-0 task.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang G., Pang H., Xue Y., Zhou Y., Wang R. 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