Periodic recurrent waves of Covid-19 epidemics and vaccination campaign

Campi, Gaetano; Bianconi, A.

doi:10.1016/j.chaos.2022.112216

Cited by 8 publications

(4 citation statements)

References 45 publications

(74 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The WT has also been useful in the study of the epidemic evolution of COVID-19. For example, Campi et al [48] analyzed the daily deaths per million caused by the COVID-19 epidemic and SARS-CoV-2 contagiousness measure through the RIC-index (i.e., the ratio of the time reproductive number and the doubling time). The Morse wavelet was used to generate the scalogram of the daily days data and RIC-index; however, the authors did not report the values of γ and β.…”

Section: Applications Of the Generalized Morse Wavelets A Medical And...mentioning

confidence: 99%

Applications of the Generalized Morse Wavelets: A Review

et al. 2023

View full text Add to dashboard Cite

The study of signals, processes, and systems has motivated the development of different representations that can be used to analyze and understand them. Classical ways of studying the behavior of signals are the time domain and frequency domain representations. For the analysis of non-stationary signals, time-frequency representations have become an essential tool to understand how the frequency content of signals changes with time. A common time-frequency technique employed in the literature is the wavelet transform. Nevertheless, selecting an adequate mother wavelet to perform the wavelet transform has become challenging due to the diverse available wavelet families. This paper reviews the applications and uses of a particular class of wavelet basis known as the Generalized Morse Wavelets. This class of wavelet family provides a systematic framework to choose and generate a wavelet for general-purpose use. This study reviews the application of Generalized Morse Wavelets in biomedical engineering, dynamical systems analysis, electrical engineering, geophysics, and communication systems. Moreover, the parameters of the Generalized Morse Wavelets used in each study are presented. The results of this study reveal that Generalized Morse Wavelets have proven helpful in studying signals, systems, and processes in areas ranging from biomedical engineering to geophysics. Nonetheless, the parameters of the Generalized Morse Wavelets are yet to be chosen through a rigorous methodology and argumentation. Therefore, there is an opportunity to generate methods for selecting the parameters of the Generalized Morse Wavelets based on the characteristics of the signals, systems, or processes under research.INDEX TERMS Generalized Morse wavelets, mother wavelet selection, continuous wavelet transform, applications, time-frequency analysis.

show abstract

Section: Applications Of the Generalized Morse Wavelets A Medical And...mentioning

confidence: 99%

Applications of the Generalized Morse Wavelets: A Review

et al. 2023

View full text Add to dashboard Cite

show abstract

“…3. Machine learning and statistical techniques includes analyzing large datasets of information about the pandemic, such as new cases and deaths, applying regressions, identifying classes, trends and clusters [6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Assessment of COVID-19 Numbers by Using Fisher Transform Indicator

Nutku¹

2023

Preprint

View full text Add to dashboard Cite

New cases, new deaths, new deaths per new cases numbers belonging to COVID-19 pandemic investigated via open, high, low, close candlesticks and Fisher transform indicator. Candlestick plots, accompanied by crossovers in the Fisher transform indicator, facilitate the determination of the beginning of upward and downward trends in numbers, clearly and in a timely manner. It has been shown that an increase in the total number of peaks over time, in both smoothed candlestick data and in the Fisher transform indicator, can indicate the temporary or persistent diminishing of a pandemic.

show abstract

“…3. Machine learning and statistical techniques includes analyzing large datasets of information about the pandemic, such as new cases and new deaths, applying regressions, identifying classes, trends and clusters [6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%