A paper written by Joydeep Bhattacharya, professor, Priyama Majumda, and former MS (Econ) Iowa State student Ritwik Banerjee, is the subject of an August 12 BBC article, "Exponential growth bias: The numerical error behind Covid-19."
The researchers speculate that some of the graphical representations found in the media may have been counter-productive. It’s common for the number of infections to be presented on a “logarithmic scale”, in which the figures on the y-axis increase by a power of 10 (so the gap between 1 and 10 is the same as the gap between 10 and 100, or 100 and 1000).
While this makes it easier to plot different regions with low and high growth rates, it means that exponential growth looks more linear than it really is, which could reinforce the exponential growth bias. “To expect people to use the logarithmic scale to extrapolate the growth path of a disease is to demand a very high level of cognitive ability,” the authors told me in an email. In their view, simple numerical tables may actually be more powerful.