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Updated: Nov 5, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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Predictability of COVID-19 worldwide lethality using permutation-information theory quantifiers.

Leonardo H S Fernandes1, Fernando H A Araujo2, Maria A R Silva3

  • 1Department of Economics and Informatics, Federal Rural University of Pernambuco, Serra Talhada, PE 56909-535, Brazil.

Results in Physics
|May 18, 2021
PubMed
Summary

Proactive COVID-19 prevention measures, like masks and testing, led to lower lethality (higher predictability). Reactive measures resulted in higher lethality (lower predictability), showing prevention

Keywords:
COVID-19Complexity hierarchyFisher information measureLethalityPermutation entropySliding window technique

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Area of Science:

  • Complex systems analysis
  • Epidemiological modeling
  • Information theory in public health

Background:

  • COVID-19 pandemic presented significant global health challenges.
  • Understanding disease lethality predictability is crucial for public health interventions.
  • Quantifying randomness in daily death cases can offer insights into pandemic dynamics.

Purpose of the Study:

  • To examine the predictability of COVID-19 lethality across 43 countries.
  • To quantify disorder and randomness in daily COVID-19 death case time series.
  • To rank countries based on COVID-19 lethality complexity using information-theoretic measures.

Main Methods:

  • Application of the Shannon-Fisher causality plane (SFCP) using Permutation Entropy (Hs) and Fisher Information Measure (Fs).
  • Analysis of time series data for daily COVID-19 death cases.
  • Ranking countries based on complexity hierarchy derived from Hs and Fs values.

Main Results:

  • Proactive countries implementing measures like masks and testing showed lower entropy (higher predictability) in COVID-19 lethality.
  • Reactive countries exhibited higher entropy (lower predictability) in COVID-19 lethality.
  • A complexity hierarchy was established for COVID-19 lethality across the studied nations.

Conclusions:

  • Preventive public health measures are effective in reducing COVID-19 lethality.
  • Proactive strategies correlate with increased predictability of disease outcomes.
  • Information-theoretic measures provide valuable insights into pandemic control effectiveness.