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The κ-statistics approach to epidemiology
Giorgio Kaniadakis1, Mauro M Baldi2, Thomas S Deisboeck3
1Dipartimento di Scienza Applicata e Tecnologia, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy. giorgio.kaniadakis@polito.it.
Scientific Reports
|November 18, 2020
Summary
The new [Formula: see text]-statistics framework effectively models complex systems, including historical plague and COVID-19 pandemics. This statistical approach demonstrates universal applicability across diverse epidemiological events.
Area of Science:
- Statistical modeling
- Epidemiology
- Complex systems analysis
Background:
- Many natural and artificial systems exhibit statistical distributions with exponential bulk and Pareto power-law tails.
- The [Formula: see text]-statistics framework has emerged as a powerful tool for describing such distributions.
- This framework's relevance is increasingly recognized across various scientific fields for fitting empirical data.
Purpose of the Study:
- To apply the [Formula: see text]-statistics framework to develop a novel statistical approach for epidemiological analysis.
- To introduce and validate the derived [Formula: see text]-Weibull distributions using historical and contemporary pandemic data.
- To assess the universal applicability of the [Formula: see text]-Weibull model in describing epidemiological patterns.
Main Methods:
- Utilized the [Formula: see text]-statistics framework to derive [Formula: see text]-Weibull distributions.
- Fitted the [Formula: see text]-Weibull distributions to epidemiological data from the 1417 Florence plague.
- Analyzed COVID-19 pandemic data from China, Germany, Italy, Spain, and the United Kingdom, covering their first cycles.
Main Results:
- The [Formula: see text]-Weibull distributions showed excellent agreement with empirical data from both the plague and COVID-19 pandemics.
- The model successfully described the entire first cycle of the COVID-19 pandemic in multiple European countries.
- The analysis confirmed the robustness and accuracy of the [Formula: see text]-Weibull model in epidemiological forecasting.
Conclusions:
- The [Formula: see text]-Weibull model, based on [Formula: see text]-statistics, provides a universal framework for analyzing epidemiological data.
- The model's success in fitting data from vastly different pandemics (plague and COVID-19) highlights its broad applicability.
- This statistical approach offers a promising tool for understanding and predicting the dynamics of infectious disease outbreaks.
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