Open AccessAnticipating trajectories of exponential growth
Author(s) -
Florian Hutzler,
Fabio Richlan,
Michael Christian Leitner,
Sarah Schuster,
Mario Braun,
Stefan Hawelka
Publication year - 2021
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.201574
Subject(s) - exponential growth , logarithm , exponential function , scaling , judgement , logarithmic growth , linear growth , econometrics , context (archaeology) , mathematics , statistical physics , statistics , physics , mathematical analysis , geography , geometry , archaeology , political science , law
Humans grossly underestimate exponential growth, but are at the same time overconfident in their (poor) judgement. The so-called ‘exponential growth bias' is of new relevance in the context of COVID-19, because it explains why humans have fundamental difficulties to grasp the magnitude of a spreading epidemic. Here, we addressed the question, whether logarithmic scaling and contextual framing of epidemiological data affect the anticipation of exponential growth. Our findings show that underestimations were most pronounced when growth curves were linearly scaled and framed in the context of a more advanced epidemic progression. For logarithmic scaling, estimates were much more accurate, on target for growth rates around 31%, and not affected by contextual framing. We conclude that the logarithmic depiction is conducive for detecting exponential growth during an early phase as well as resurgences of exponential growth.