Modeling the correlation between COVID-19 infection and mortality using a sigmoidal approach

Aferni A.E.; Guettari M.; Vilca-Huayta O.-A. · European Physical Journal Plus (2026) · DOI: 10.1140/epjp/s13360-026-07306-3

Resumen

This study examines correlations between COVID-19 infections and deaths in six countries across six continents (Afghanistan, Costa Rica, Colombia, Australia, Algeria, and Germany). Using a sigmoid dose–response model, we relate cumulative infections, (t), to cumulative deaths, D(t), treating deaths as a time-delayed response to the spread of infection through transmission networks. Both I(t) and D(t) follow modified sigmoidal equations, which we apply to N consecutive epidemic waves. Pearson (r) and Spearman (rs) correlation coefficients highlight strong correlations between the parameters of I(t) and D(t). We identify empirical laws linking infection parameters to death parameters, leading to a mortality equation D(t) expressed as a function of infection-related parameters. We also establish a novel expression for the epidemic fatality rate βf. Cross-correlation analysis of infection and death spread rates (VI(t) and VD(t)) reveals an average time lag Δt of 7–24 days across the six countries. The average fatality rate β(t) ranges from 0.16 to 3.92%. © The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2026.

Instituciones: Universidad Nacional del Altiplano