When displaying the confirmed cases of the day, a logarithmic y-axis was used instead of a regular axis. 

Can lead to an impression of fewer confirmed cases. 


New York University

Visualization of Covid 19 misinformation can occur commonly when:

data is represented partially 

Scale of the graph is manipulated

When the data is taken out of context 


Types of Covid 19 Misinformation Visualization


Obasanjo, D. (2020, April 4). You can teach an entire semester of how to lie with statistics with the y-axis of this chart [Tweet]. Twitter. https://twitter.com/Carnage4Life/status/1246579721585868800

You can teach an entire semester of how to lie with statistics with the y-axis of this chart.

Doan, S. (2021). Misrepresenting COVID-19: Lying With Charts During the Second Golden Age of Data Design. Journal of Business and Technical Communication, 35(1), 73–79. https://doi.org/10.1177/1050651920958392

Misrepresenting COVID-19: Lying With Charts During the Second Golden Age of Data Design

Covid 19 Misinformation Visualization: Case of Manipulated Axis


Data is visualized without telling the viewer about how the data is collected or what constitutes the numbers. 

Can be used to favor personal opinions, such as wishing to extend social distancing. 


Covid 19 Misinformation Visualization: Case of No Context


Charts comparing the recovery rate of COVID-19 with that of SARS and MERS can represent data partially by omitting crucial information, such as the spread and incubation time of the different viruses. This partial data visualization can cause people to underestimate the seriousness of the COVID-19 virus.

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