There are two methods for showing the development of Covid-19 case counts: the linear method and the logarithmic method. The linear method is simply placing the numbers of cases side by side in a graph, day by day, as bars or a curve. During an exponential growth the graph shows a curve that goes up an becomes steeper and steeper. With a logarithmic representation the difference between higher numbers becomes smaller and smaller, as you can see in the axis on the left side. In this case an exponential growth looks like a straight line.
According to researchers, the general public does not fully understand how to interpret logarithmic graphs. This is an issue because the media often use logarithmic graphs to display data related to Covid-19. In fact, only about 40 percent of participants were able to answer questions based on logarithmic graphs correctly, compared to 84 percent with linear graphs. Therefore, the researchers are calling for the media to switch to using the more widely understood linear graphs. They have found that people who routinely read logarithmic graphs and those who use linear scale graphs have vastly different opinions on Covid-19 related policy making.
More specifically, in terms of Covid-19 death rates, logarithmic graphs do better represent the nature of deaths due to Covid-19 and actually predict greater death rates. However, people who read these graphs reported feeling less worried about Covid-19 because they interpreted the graph incorrectly. They see the curve of the logarithmic graphs as a sign that death rates are lowering. In this case understanding needs to be prioritized over greater statistical accuracy.
Actually, all you need to understand is that a logarithmic graph does not show the case numbers but the exponential growth rate so that a straight line actually means exponential growth.
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