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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">sredob</journal-id><journal-title-group><journal-title xml:lang="ru">Здоровье населения и среда обитания – ЗНиСО</journal-title><trans-title-group xml:lang="en"><trans-title>Public Health and Life Environment – PH&amp;LE</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2219-5238</issn><issn pub-type="epub">2619-0788</issn><publisher><publisher-name>ФБУЗ ФЦГиЭ Роспотребнадзора</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.35627/2219-5238/2024-32-3-54-62</article-id><article-id custom-type="elpub" pub-id-type="custom">sredob-1704</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>ЭПИДЕМИОЛОГИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>EPIDEMIOLOGY</subject></subj-group></article-categories><title-group><article-title>Алгоритмический подход к установлению эпидемических порогов в системе эпидемиологического надзора за инфекционными заболеваниями</article-title><trans-title-group xml:lang="en"><trans-title>Algorithmic Approach to Determination of Epidemic Thresholds in Infectious Disease Surveillance Systems</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0756-2271</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Блох</surname><given-names>А. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Blokh</surname><given-names>A. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Блох Алексей Игоревич – канд. мед. наук, руководитель Сибирского федерального окружного центра по профилактике и борьбе со СПИД, врач-эпидемиолог ФБУН «Омский НИИ природно-очаговых инфекций» Роспотребнадзора.</p><p>пр-т Мира, д. 7, Омск, 644080; ул. Ленина, д. 12, Омск, 644099</p></bio><bio xml:lang="en"><p>Alexey I. Blokh - Cand. Sci. (Med.), Head of the Siberian Federal District Center for AIDS Prevention and Control; epidemiologist, Omsk Research Institute of Natural Focal Infections.</p><p>7 Mira Avenue, Omsk, 644080; 12 Lenin Street, Omsk, 644099</p></bio><email xlink:type="simple">blokh_ai@oniipi.org</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4185-9829</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Летюшев</surname><given-names>А. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Letushev</surname><given-names>A. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Летюшев Александр Николаевич – к.м.н., доцент кафедры организации санитарно-эпидемиологической службы.</p><p>ул. Баррикадная, д. 2/1, Москва, 125993</p></bio><bio xml:lang="en"><p>Aleksandr N. Letushev - Cand. Sci. (Med.), Associate Professor, Department of Organization of the Sanitary and Epidemiological Service; Russian Medical Academy of Continuous Professional Education.</p><p>2/1 Barrikadnaya Street, Moscow, 125993</p></bio><email xlink:type="simple">kaf.orgses.rmapo@yandex.ru</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7220-4366</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Пеньевская</surname><given-names>Н. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Penevskaya</surname><given-names>N. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Пеньевская Наталья Александровна – д-р мед. наук, доцент, заместитель директора по научной работе ФБУН «Омский НИИ природно-очаговых инфекций» Роспотребнадзора.</p><p>пр-т Мира, д. 7, Омск, 644080; ул. Ленина, д. 12, Омск, 644099</p></bio><bio xml:lang="en"><p>Natalia A. Penyevskaya - Dr. Sci. (Med.), docent; Deputy Director for Research, Omsk Research Institute of Natural Focal Infections.</p><p>7 Mira Avenue, Omsk, 644080; 12 Lenin Street, Omsk, 644099</p></bio><email xlink:type="simple">nap20052005@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9566-9214</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Рудаков</surname><given-names>Н. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Rudacov</surname><given-names>N. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Рудаков Николай Викторович – д-р мед. наук, профессор, директор ФБУН «Омский НИИ природно-очаговых инфекций» Роспотребнадзора.</p><p>пр-т Мира, д. 7, Омск, 644080; ул. Ленина, д. 12, Омск, 644099</p></bio><bio xml:lang="en"><p>Nikolay V. Rudakov - Dr. Sci. (Med.), Prof.; Director, Omsk Research Institute of Natural Focal Infections.</p><p>7 Mira Avenue, Omsk, 644080; 12 Lenin Street, Omsk, 644099</p></bio><email xlink:type="simple">mail@oniipi.org</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФБУН «Омский НИИ природно-очаговых инфекций» Роспотребнадзора; ФГУО ВО Омский государственный медицинский университет Минздрава</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Omsk Research Institute of Natural Focal Infections; Omsk State Medical University</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования» Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian Medical Academy of Continuous Professional Education</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>29</day><month>03</month><year>2024</year></pub-date><volume>32</volume><issue>3</issue><fpage>54</fpage><lpage>62</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Блох А.И., Летюшев А.Н., Пеньевская Н.А., Рудаков Н.В., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Блох А.И., Летюшев А.Н., Пеньевская Н.А., Рудаков Н.В.</copyright-holder><copyright-holder xml:lang="en">Blokh A.I., Letushev A.N., Penevskaya N.A., Rudacov N.V.</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://zniso.fcgie.ru/jour/article/view/1704">https://zniso.fcgie.ru/jour/article/view/1704</self-uri><abstract><sec><title>Введение</title><p>Введение. Обзор посвящен алгоритмическому подходу к установлению эпидемических порогов для широкого круга заболеваний, в том числе гриппа и острых респираторных инфекций.</p></sec><sec><title>Цель исследования</title><p>Цель исследования: сравнительная характеристика отечественных и зарубежных подходов к установлению эпидемических порогов для применения в системе эпидемиологического надзора.</p></sec><sec><title>Материалы и методы</title><p>Материалы и методы. Для раскрытия алгоритмического подхода к установлению эпидемических порогов в системе эпидемиологического надзора проведено обобщение результатов 14 зарубежных научных работ и двух отечественных методических документов, опубликованных до 31.12.2023. Поиск научной литературы проведен в базах данных eLibrary, CyberLeninka, PubMed, а также с применением Google Scholar по ключевым словам «эпидемический порог» / “epidemic threshold” и «эпидемия» / “epidemic”. Проведено сопоставление отечественных и зарубежных алгоритмов установления эпидемических порогов по различными характеристикам, включая применяемый статистический метод, определение эпидемического порога в числовом значении, сложность алгоритма и возможность автоматизации расчетов.</p></sec><sec><title>Результаты</title><p>Результаты. Представлены классификация и сравнительные характеристики базовых алгоритмов определения эпидемических порогов, используемых в различных странах мира при осуществлении эпидемиологического надзора (в том числе синдромного). Описаны существующие способы установления и формы представления эпидемических порогов, а также последовательность шагов для выполнения алгоритмов Фаррингтона, Системы раннего выявления отклонений C1-C3, Метода движущихся эпидемий, Метода движущихся перцентилей, Многоуровневого выделения повышающейся активности по показателям с учетом смешанных эффектов, а также алгоритмов МР 3.1.2.0118–17 и МР 3.1.2.0303–22. Анализируются проблемы разработки, оценки точности и перспективы внедрения существующих и разрабатываемых алгоритмов.</p></sec><sec><title>Заключение</title><p>Заключение. Современные алгоритмы установления эпидемических порогов в системах эпидемиологического надзора по всему миру разнообразны, опираются на различные статистические методы, различаются по сложности. На сегодняшний день отсутствуют убедительные доказательства более высокой эффективности какого-либо алгоритма.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Introduction</title><p>Introduction: This review is devoted to the algorithmic approach to establishing epidemic thresholds for a wide range of diseases, including influenza and acute respiratory infections.</p></sec><sec><title>Objective</title><p>Objective: To compare Russian and foreign approaches to the determination of epidemic thresholds within public health surveillance systems.</p></sec><sec><title>Materials and methods</title><p>Materials and methods: To reveal the algorithmic approach to establishing epidemic thresholds in the epidemiological surveillance system, we summarized the results of 14 foreign scientific works and two domestic method guidelines published before December 31, 2023. The literature search was conducted in the eLibrary, CyberLeninka, PubMed, and Google Scholar databases using the keywords “epidemic threshold” and “epidemic”. We compared domestic and foreign algorithms for establishing epidemic thresholds by various characteristics, including the statistical method used, determination of a numerical value of the epidemic threshold, complexity of the algorithm, and the possibility of automating calculations.</p></sec><sec><title>Results</title><p>Results: Here we discuss the classification and comparative characteristics of the basic algorithms for determining epidemic thresholds used in various countries of the world when carrying out epidemiological surveillance, including the syndromic one. We describe the existing methods for establishing and presenting epidemic thresholds, as well as the sequence of steps for performing the Farrington algorithms, the Early Aberration Detection System C1–C3, the Method of Moving Epidemics, the Method of Moving Percentiles, Multi-level identification of increasing activity by indicators taking into account mixed effects, as well as algorithms provided in Russian Method Guidelines MR 3.1.2.0118–17 and MR 3.1.2.0303–22. We also dwell on the problems of development, accuracy assessment and prospects for the implementation of existing and developed algorithms.</p></sec><sec><title>Conclusions</title><p>Conclusions: Current algorithms for establishing epidemic thresholds in epidemiological surveillance systems around the world are diverse; they rely on different statistical methods and vary in complexity. To date, there is no convincing evidence of higher efficiency of any algorithm.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>эпидемиология</kwd><kwd>эпидемии</kwd><kwd>общественное здоровье</kwd><kwd>наблюдение и контроль</kwd><kwd>эпидемиологические методы</kwd><kwd>заболеваний эпидемические вспышки</kwd></kwd-group><kwd-group xml:lang="en"><kwd>epidemiology</kwd><kwd>epidemics</kwd><kwd>public health surveillance</kwd><kwd>epidemiologic methods</kwd><kwd>disease outbreaks</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Langmuir AD. The surveillance of communicable diseases of national importance. N Engl J Med. 1963;268:182-192. doi: 10.1056/NEJM196301242680405</mixed-citation><mixed-citation xml:lang="en">Langmuir AD. The surveillance of communicable diseases of national importance. 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