Finite-size scaling versus dual random variables and shadow moments in the size distribution of epidemics

2020/11/09 by Álvaro Corral, Corral, Alvaro
Biochemistry, Genetics and Molecular Biology · Economics, Econometrics and Finance · Environmental Science · Mathematics · Physics and Astronomy · #Adaptation and Self-Organizing Systems (nlin.AO) #COVID-19 epidemiological studies #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Evolution and Genetic Dynamics #FOS: Physical sciences #Hydrology and Drought Analysis #Physics and Society (physics.soc-ph)

paper · pdf · doi:10.48550/arxiv.2011.04316

openalex publication_date 2020/11/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

I discuss and criticize the use of "dual transformations" to calculate "shadow moments" in the distribution of epidemic fatalities. I show how this transformation is arbitrary and not only yields an unjustified functional form for the distribution of fatalities but turns out to be highly unphysical (see Fig. 1 in the manuscript). Therefore, the expected number of fatalities calculated from the "shadow moments" approach lacks any theoretical support. This is of fundamental importance to assess risk from pandemics. I argue that the natural way to address this sort of problems in statistical physics is by means of finite-size scaling.

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