data viz 2021.2: Gender Inequality and HIV

Author by Leah Shea

3 minutes
Tags: datadata visualization
data viz 2021.2: Gender Inequality and HIV

#MakeoverMonday is a weekly data visualization exercise led by Eva Murray and Andy Kriebel. They post a data set and original viz - and we improve upon it! To participate or for more information, visit the Makeover Monday website

2021 week 2: Gender Inequality (#Viz5)

Below is the original visualization. It depicts the gender disparities in adolescent HIV in Sub-Saharan Africa.

original viz

First, two questions: 

1) What works?

  • Strong statement of need based on data written out in text as well as graphical formats.
  • Shows many different metrics, with comparisons between male and female on the right.
  • Inclusion of logos in header.

2) What doesn't?

  • There are more efficient and visual ways to show the discrepancy between male and female.
  • Some of the colors are muted and makes the visualization difficult to read.
  • Different colors used across different metrics makes the viz a little difficult to interpret.

Updated Visualization

updated viz

Click here for the full interactive viz on Tableau Public.


  • Focused on creating a custom color data set based on the two logos provided. From there, established consistency in coloration across metrics.
  • Added logos as images to the dashboard.
  • Simplified the relationships between metrics, i.e. put the HIV new infection total as a bar chart with the HIV new infection rates as a line within the same chart. AIDS death total and rates share a similarly formatted graph positioned below. You can see the trend lines for the rates is declining, with the total population still disproportionately affecting the female population.
  • Instead of a formal legend for the graphs on the right, the header showing female and male correlates to the colors used in the graphs below.
  • The geographic heat map also acts as a filter in the live viz, which helps in exploring the HIV new infections and AIDS deaths for each country included in the analysis.
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