WHO Global Health Indicators for Prediction

By shrijeetverma13 · May 4, 2026

This dataset contains REAL, authoritative health data from the World Bank Open Data platform, which hosts World Health Organization (WHO) and United…

The analysis examined which countries showed the largest changes in total population between their earliest and latest recorded years. Data tables were generated highlighting the top 10 countries with the greatest absolute population shifts, giving a clear picture of where demographic growth or decline has been most dramatic.

The analysis examined which countries consistently rank highest across multiple indicators in 2024. A bar chart was generated showing the top 15 countries by how often they appear in the top 10 across all available indicators, giving a clear picture of which nations perform best overall.

The analysis identified the top 10 indicators with the widest value ranges across countries, highlighting the biggest opportunity gaps. A horizontal bar chart was generated showing these indicators ranked by their range (max minus min value), and data tables provide the detailed min, max, mean, and country count for each indicator.

The analysis compares key development indicators across global regions, revealing clear leaders and laggards. Two visualizations were generated: a grouped bar chart showing average indicator values by region, and a normalized heatmap (0=lowest, 1=highest) for easy cross-indicator comparison. Overall, North America ranks as the top-performing region (score: 0.781), while Sub-Saharan Africa ranks lowest (score: 0.228).

From 2000 to 2024, the global average across 31 tracked indicators showed a slight overall decline. Using normalized values (0–1 scale per indicator) to fairly compare indicators with very different units, the average dipped from 0.569 in 2000 to 0.526 in 2024 — a decrease of about 0.043. Two charts were generated: one showing the overall normalized global trend, and another showing raw average values for the 5 most-reported indicators on a log scale.

The analysis reveals significant disparities in indicator values across income level groups. Three visualizations were generated: a bar chart showing mean values by income group, a box plot illustrating the distribution spread across groups, and a horizontal bar chart highlighting the top 10 indicators with the largest High vs. Low income disparity ratios. Multiple data tables further break down these differences across indicators and income categories.

The analysis successfully produced a stacked bar chart and supporting data tables showing how countries are distributed across the four income levels — Low income, Lower middle income, Upper middle income, and High income. The visualization clearly illustrates which world regions contribute most to each income category, with each colored segment representing a different region's share within that income group.

The IQR outlier detection analysis successfully identified countries that appear as statistical outliers most frequently across multiple indicators. Two bar charts were generated: one showing the top 20 countries by outlier frequency (colored by income level), and another showing the distribution of outlier counts by income level. Data tables were also produced summarizing each country's outlier count alongside their income level and region.

The analysis examined the distribution of indicator values across the top 6 most common indicators for the most recent year available (2024). A side-by-side box plot was generated showing the spread, median, and outliers for each indicator on a logarithmic scale, making it easy to compare metrics that span very different value ranges. The visualization reveals how each indicator's values are distributed across countries, including the central tendency and any extreme outliers.

The analysis produced three comparative tables showing the top 5 and bottom 5 countries for each indicator, along with region and income level clustering patterns. The tables highlight which countries lead and lag across different development indicators, and how performance groups by geography and economic status.