ArticleChaos, solitons, and fractals2020
An analysis of COVID-19 spread based on fractal interpolation and fractal dimension.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Fractal dimension based geographical clustering of COVID-19 time series data.Scientific reports · 2023Article
- Dimensional study of COVID-19 via fractal functions.The European physical journal. Special topics · 2023Article
- Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium.Frontiers in public health · 2023Article
- On fractal-fractional Covid-19 mathematical model.Chaos, solitons, and fractals · 2022Article
- Omicron: a mysterious variant of concern.European physical journal plus · 2022Article
- Agent-based analysis of contagion events according to sourcing locations.Scientific reports · 2021Article
- The Chaotic Behavior of the Spread of Infection During the COVID-19 Pandemic in the United States and Globally.IEEE access : practical innovations, open solutions · 2021Article
- Modeling and forecasting the spread of COVID-19 with stochastic and deterministic approaches: Africa and Europe.Advances in difference equations · 2021Article
- The second and third waves in India: when will the pandemic be culminated?European physical journal plus · 2021Article
- An exploration of fractal-based prognostic model and comparative analysis for second wave of COVID-19 diffusion.Nonlinear dynamics · 2021Article
- On the use of growth models to understand epidemic outbreaks with application to COVID-19 data.PloS one · 2020Article
- TL-med: A Two-stage transfer learning recognition model for medical images of COVID-19.Biocybernetics and biomedical engineeringArticle
- WOANet: Whale optimized deep neural network for the classification of COVID-19 from radiography images.Biocybernetics and biomedical engineeringArticle
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2 authors.
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Abstract
The present paper proposes a reconstruction of the epidemic curves from the fractal interpolation point of view. Looking at the epidemic curves as fractal structures might be an efficient way to retrieve missing pieces of information due to insufficient testing and predict the evolution of the disease. A fractal approach of the epidemic curve can contribute to the assessment and modeling of other epidemics. On the other hand, we have considered the spread of the epidemic in countries like Romania, Italy, Spain, and Germany and analyzed the spread of the disease in those countries based on their fractal dimension.
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