Global Healthcare Infrastructure & Expenditure by Country (1970–2023)
About this data
A comprehensive panel dataset covering 221 countries and territories from 1970 to 2023 with 27 indicators spanning healthcare infrastructure, expenditure, health outcomes, disease burden, and socioeconomic context. ## Sources - **World Bank World Development Indicators (WDI)** — primary source for all 22 health and socioeconomic indicators - **WHO Global Health Observatory** — regional classification (WHO regions: AFRO, AMRO, EMRO, EURO, SEARO, WPRO) - **World Bank Income Classifications** — derived income group (Low, Lower-middle, Upper-middle, High) based on GNI per capita thresholds ## Key Indicators - **Health Expenditure:** % of GDP, per capita (USD) - **Infrastructure:** Hospital beds, physicians, nurses & midwives per 1,000 population - **Health Outcomes:** Life expectancy (total, male, female), infant and under-5 mortality, maternal mortality - **Disease Burden:** TB incidence, HIV incidence, immunization rates (measles, DPT) - **Nutrition:** Child stunting and overweight prevalence - **WASH:** Basic water and sanitation access - **Context:** Population, urbanization rate, GDP per capita, WHO region, income group ## Coverage - **11,929 rows** × 27 columns - 221 countries/territories, 54 years (1970–2023) - Core indicators (life expectancy, mortality, population) have near-complete coverage; specialized indicators (health expenditure, infrastructure) concentrated in 2000–2022 ## Use Cases - Cross-country health system comparisons - Longitudinal analysis of health outcomes vs. spending - SDG progress tracking (Goal 3: Good Health & Well-Being) - Income-group or regional health disparity analysis - Predictive modeling of health outcomes from infrastructure investments
Schema
| Name | Type | Description |
|---|---|---|
| country_code | string | |
| country_name | string | |
| who_region | string | |
| income_group | string | |
| year | string | |
| population | string | |
| urban_population_pct | string | |
| gdp_per_capita_usd | string | |
| health_expenditure_pct_gdp | string | |
| health_expenditure_per_capita_usd | string | |
| hospital_beds_per_1000 | string | |
| physicians_per_1000 | string | |
| nurses_midwives_per_1000 | string | |
| life_expectancy_total | string | |
| life_expectancy_male | string | |
| life_expectancy_female | string | |
| infant_mortality_per_1000 | string | |
| under5_mortality_per_1000 | string | |
| maternal_mortality_per_100k | string | |
| immunization_measles_pct | string | |
| immunization_dpt_pct | string | |
| tuberculosis_incidence_per_100k | string | |
| hiv_incidence_per_1000 | string | |
| overweight_pct_children_under5 | string | |
| stunting_pct_children_under5 | string | |
| basic_water_access_pct | string | |
| basic_sanitation_access_pct | string |
Sample Data
Preview a sample of the data before downloading.
For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Global Healthcare Infrastructu" })
// Found: eb922319-f9ca-432e-a031-1177dd193216
get_download_url({ dataset_id: "eb922319-f9ca-432e-a031-1177dd193216" }) // free — no API key needed# Free dataset — no API key required: curl https://api.databazaar.io/datasets/eb922319-f9ca-432e-a031-1177dd193216/download-url