The Cyclicity of coronavirus cases: ?Waves? and the ?weekend effect? : научное издание


Тип публикации: статья из журнала

Год издания: 2021

Идентификатор DOI: 10.1016/j.chaos.2021.110718

Ключевые слова: coronavirus, dynamics, time series, waves, week end effect, spectral analysis, autoregression

Аннотация: Introduction: Medical statistics is one of the "milestones" of current medical systems. It is the foundation for many protocols, including medical care systems, government recommendations, epidemic planning, etc. At this time of global COVID-19, credible data on epidemic spread can help governments make better decisions. This studyПоказать полностью& rsquo;s aim is to evaluate the cyclicity in the number of daily diagnosed coronavirus patients, thus allowing governments to plan how to allocate their resources more effectively. Methods: To assess this cycle, we consider the time series of the first and second differences in the number of registered patients in different countries. The spectral densities of the time series are calculated, and the frequencies and amplitudes of the maximum spectral peaks are estimated. Results: It is shown that two types of cycles can be distinguished in the time series of the case numbers. Cyclical fluctuations of the first type are characterized by periods from 100 to 300 days. Cyclical fluctuations of the second type are characterized by a period of about seven days. For different countries, the phases of the seven-day fluctuations coincide. It is assumed that cyclical fluctuations of the second type are associated with the weekly cycle of population activity. Conclusions: These characteristics of cyclical fluctuations in cases can be used to predict the incidence rate. (c) 2021 Elsevier Ltd. All rights reserved.

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Выпуск журнала: Vol. 144

Номера страниц: 110718

ISSN журнала: 09600779

Место издания: OXFORD



  • Soukhovolsky Vladislav (Russian Acad Sci, Fed Res Ctr, Siberian Branch, Krasnoyarsk, Russia)
  • Kovalev Anton (Russian Acad Sci, Fed Res Ctr, Siberian Branch, Krasnoyarsk, Russia)
  • Pitt Anne (Russian Acad Sci, Fed Res Ctr, Siberian Branch, Krasnoyarsk, Russia)
  • Shulman Katerina (Technion, Rappaport Med Sch, Carmel Med Ctr, Haifa, Israel)
  • Tarasova Olga (Siberian Fed Univ, Krasnoyarsk, Russia)
  • Kessel Boris (Technion, Rappaport Med Sch, Hillel Yaffe Med Ctr, Haifa, Israel)

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