ArticleChaos, solitons, and fractals2021
The Cyclicity of coronavirus cases: "Waves" and the "weekend effect".
Article in Chaos, solitons, and fractals, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Combinatorial (bio-geo-temporal) and non-combinatorial analysis of the COVID-19 dissemination that affected Georgia (the country) in 2021.Frontiers in public health · 2026Article
- Back-projection improves inference from sparsely sampled genomic surveillance data.bioRxiv : the preprint server for biology · 2025Article
- Understanding Citizens' Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI.Journal of medical Internet research · 2025Article
- Nonlinear time series analysis of state-wise COVID-19 in Malaysia using wavelet and persistent homology.Scientific reports · 2024Article
- 20-Month monitoring of SARS-CoV-2 in wastewater of Curitiba, in Southern Brazil.Environmental science and pollution research international · 2023Article
- Key epidemiological indicators and spatial autocorrelation patterns across five waves of COVID-19 in Catalonia.Scientific reports · 2023Article
- The effect of self-esteem on the spread of a pandemic. A cross-country analysis of the role played by self-esteem in the spread of the COVID-19 pandemic.Social science & medicine (1982) · 2023Article
- In COVID We Trust: The Impact of The Pandemic on Religiousness-Evidence from Italian Regions.Journal of religion and health · 2023Article
- Death takes no bribes: Impact of perceived corruption on the effectiveness of non-pharmaceutical interventions at combating COVID-19.Social science & medicine (1982) · 2022Article
- The impact of the government response on pandemic control in the long run-A dynamic empirical analysis based on COVID-19.PloS one · 2022Article
- Development of an Early Alert System for an Additional Wave of COVID-19 Cases Using a Recurrent Neural Network with Long Short-Term Memory.International journal of environmental research and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMedical 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 study'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.
methodsTo 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.
resultsIt 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.
conclusionsThese characteristics of cyclical fluctuations in cases can be used to predict the incidence rate.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.