ArticleScientific reports2020
The κ-statistics approach to epidemiology.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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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Who cites it
22 citing papers in PubMed.
- Twenty Years of Kaniadakis Entropy: Current Trends and Future Perspectives.Entropy (Basel, Switzerland) · 2025Article
- Emergence to dominance: Estimating time to dominance of SARS-CoV-2 variants using nonlinear statistical models.PloS one · 2025Article
- Biothermodynamics of Hemoglobin and Red Blood Cells: Analysis of Structure and Evolution of Hemoglobin and Red Blood Cells, Based on Molecular and Empirical Formulas, Biosynthesis Reactions, and Thermodynamic Properties of Formation and Biosynthesis.Journal of molecular evolution · 2024Article
- A deep learning system for predicting time to progression of diabetic retinopathy.Nature medicine · 2024Article
- SARS-CoV-2 strain wars continues: Chemical and thermodynamic characterization of live matter and biosynthesis of Omicron BN.1, CH.1.1 and XBC variants.Microbial risk analysis · 2023Article
- Article
- XBB.1.5 Kraken cracked: Gibbs energies of binding and biosynthesis of the XBB.1.5 variant of SARS-CoV-2.Microbiological research · 2023Article
- The SARS-CoV-2 Hydra, a tiny monster from the 21st century: Thermodynamics of the BA.5.2 and BF.7 variants.Microbial risk analysis · 2023Article
- Never ending story? Evolution of SARS-CoV-2 monitored through Gibbs energies of biosynthesis and antigen-receptor binding of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants.Microbial risk analysis · 2023Article
- The Scientific Contribution of the Kaniadakis Entropy to Nuclear Reactor Physics: A Brief Review.Entropy (Basel, Switzerland) · 2023Review
- On the Kaniadakis Distributions Applied in Statistical Physics and Natural Sciences.Entropy (Basel, Switzerland) · 2023Article
- Generalized statistics: Applications to data inverse problems with outlier-resistance.PloS one · 2023Article
- Strain wars 5: Gibbs energies of binding of BA.1 through BA.4 variants of SARS-CoV-2.Microbial risk analysis · 2022Article
- Beyond COVID-19: Do biothermodynamic properties allow predicting the future evolution of SARS-CoV-2 variants?Microbial risk analysis · 2022Article
- Why doesn't Ebola virus cause pandemics like SARS-CoV-2?Microbial risk analysis · 2022Article
- TheEntropy (Basel, Switzerland) · 2022Article
- Omicron BA.2.75 Subvariant of SARS-CoV-2 Is Expected to Have the Greatest Infectivity Compared with the Competing BA.2 and BA.5, Due to Most Negative Gibbs Energy of Binding.Biotech (Basel (Switzerland)) · 2022Article
- Kaniadakis Functions beyond Statistical Mechanics: Weakest-Link Scaling, Power-Law Tails, and Modified Lognormal Distribution.Entropy (Basel, Switzerland) · 2022Article
- A Bayesian Analysis of Plant DNA Length Distribution viaEntropy (Basel, Switzerland) · 2022Article
- The Longitudinal Plasma Modes ofEntropy (Basel, Switzerland) · 2022Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A great variety of complex physical, natural and artificial systems are governed by statistical distributions, which often follow a standard exponential function in the bulk, while their tail obeys the Pareto power law. The recently introduced [Formula: see text]-statistics framework predicts distribution functions with this feature. A growing number of applications in different fields of investigation are beginning to prove the relevance and effectiveness of [Formula: see text]-statistics in fitting empirical data. In this paper, we use [Formula: see text]-statistics to formulate a statistical approach for epidemiological analysis. We validate the theoretical results by fitting the derived [Formula: see text]-Weibull distributions with data from the plague pandemic of 1417 in Florence as well as data from the COVID-19 pandemic in China over the entire cycle that concludes in April 16, 2020. As further validation of the proposed approach we present a more systematic analysis of COVID-19 data from countries such as Germany, Italy, Spain and United Kingdom, obtaining very good agreement between theoretical predictions and empirical observations. For these countries we also study the entire first cycle of the pandemic which extends until the end of July 2020. The fact that both the data of the Florence plague and those of the Covid-19 pandemic are successfully described by the same theoretical model, even though the two events are caused by different diseases and they are separated by more than 600 years, is evidence that the [Formula: see text]-Weibull model has universal features.
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