Fig 1.
Some of the first images of SARS-CoV-2.
A, B, C, D: Early real images with false colour of the coronavirus published on February 13th, 2020 by the NIAID. E: First public-domain 3D model of the coronavirus from the CDC published on January 30th, 2020. Credits: A, B, C, D, NIAID. E, Public Health Image Library (PHIL), by Alissa Eckert and Dan Higgins.
Fig 2.
Attributes and format of SARS-CoV-2 coronavirus images.
These images (N = 71) were available online at the start of the COVID-19 pandemic [5]: 29.6% of the images were photographs and 70.4% were illustrations; 9.9% were in black and white and 90.1% were in colour; and 29.6% were in two dimensions, while 70.4% were in three dimensions.
Fig 3.
Chord diagram of the attributes of the images presented.
Each number corresponds to one of the images. Each string indicates the connection between the image and its attributes, and the colours are used for ready visualization. The percentages and squares in the outer ring show the number of images needed to get a specific percentage for each attribute. Note there were fewer black and white images.
Table 1.
Characteristics of participants.
Fig 4.
Box plot with the mean scores that each image obtained.
Mean scores are distributed by category (beauty, scientific content, realism, infectivity, fear and didactic quality) and attribute (photograph, illustration, black and white, colour, two dimensions and three dimensions).
Table 2.
Correlations among categories.
Fig 5.
Chromaticity of the coronavirus images.
Presentation of the colour parameters for each coronavirus image analysed in the different charts. In all cases, the colours shown are only a pedagogic reference approximation: A, CIE 1931 Chromaticity chart, the numbers in blue are in nanometres; B, Hue 360° Chromaticity chart with the numbers in degrees; C, Kelvin chart with the numbers are in Kelvin.