Comparisons

The 2024 #30DayChartChallenge wrapped up at the end of April. I was able to share a number of charts, but wanted to keep the fun going and tackle each of the prompts. Here are my visualizations for the first group, “Comparisons.”

Prompts for 30DayChartChallenge
Prompts for 30DayChartChallenge

Day 1: Part-to-a-whole

This stacked bar chart shows the percentage of total cases of selected communicable diseases by WHO region in 2016. The bars are ordered from most global cases (mumps) to least (polio). A stacked bar chart like this can do a good job of showing if a region is disproportionally burdened by a disease, such as yellow fever in Africa. However, it can also obscure some interesting insights. For example, you cannot see the range of cases by country. The Western Pacific region has a significant number of mumps cases (~429,000) and includes countries from Australia to Mongolia. What the chart doesn’t show you is that more than 75% of these cases occurred in China or Japan.

Data source: World Health Organization, https://www.who.int/data/gho/data/themes/immunization.

Day 2: neo

The prompt neo and the WHO disease data set made me think of “newly independent states”, specifically the post-Soviet states that emerged from the dissolution of the Soviet Union in 1990-1991. I was curious what changes occurred in disease rates and decided to look at the period from 1999 to 2019. The only disease in the data set with complete data for all of these countries was Pertussis, so I chose to focus on that. The Russian Federation was a notable outlier so I excluded it from the final product.

Most countries reported an increase in cases. Some notable exceptions were the Baltic States of Estonia and Lithuania.

Data source: World Health Organization, https://www.who.int/data/gho/data/themes/immunization.

Day 3: makeover

Pertussis Cases in Post-Soviet Countries, 1999 to 2019.
Country Cases, 1999 Cases, 2019 Difference
Ukraine 1179 2314 1135
Latvia 55 720 665
Belarus 272 776 504
Kyrgyzstan 107 436 329
Republic of Moldova 38 174 136
Kazakhstan 56 147 91
Georgia 233 290 57
Uzbekistan 54 106 52
Tajikistan 80 112 32
Armenia 13 39 26
Turkmenistan 7 8 1
Azerbaijan 22 0 -22
Lithuania 80 26 -54
Estonia 235 135 -100
Russian Federation 22222 14407 -7815
Note:
Source: World Health Organization

For this prompt I decided to “make over” day 2 as a table. I created a static table using the kableextra package. I included all of the post-Soviet countries this time and showed how the case numbers of pertussis changed in this 20 year period. For countries with increased cases the difference value is colored in brown.

Data Source: World Health Organization

Day 4: waffle

This waffle chart shows the breakdown of the diseases reported in the WHO data set in the South East Asian Region. There were no reported cases of yellow fever, and the most common disease among the remaining six is measles.

Data source: World Health Organization, https://www.who.int/data/gho/data/themes/immunization.

Day 5: diverging

For day 5, I used data from the Healthy Places Index (HPI). The HPI maps “data on social conditions that drive health — like education, job opportunities, clean air and water, and other indicators that are positively associated with life expectancy at birth” (HPI website). Census tracts are given a score, where a positive score indicate a healthier place and a negative one a less healthy place. Hover over a bar to see the county’s average HPI value and total population.

Data source: Healthy Places Index, https://www.healthyplacesindex.org/.

Day 6: OECD

Day 6 is OECD day. I selected data from the OECD Social Expenditure Database and examined countries’ total public spending on family benefits as a percentage of GDP. Comparing spending between 2010 and 2019, I created visualizations for the two countries that represented the largest change in spending, Ireland (-1.84) and Poland (1.60).

Data source: OECD Social Expenditure Database, http://www.oecd.org/social/expenditure.htm