Hospitals1 km radius
10.2%of the urban-centre population is estimated within one kilometre of a recorded hospital.
One Kilometre From Care
See how close city residents live to recorded hospitals and pharmacies.
Try the project ↓How to use this project
Help
How to explore
This global database estimates how many people in each urban centre live within a straight-line kilometre of a hospital or pharmacy recorded in its source map.
Choose a city
Start with Indianapolis or pick another urban centre from the list.
Read the two shares
Compare the estimated population near a recorded hospital with the population near a recorded pharmacy.
Compare similar places
See where the selected centre sits among places with populations within 25% of its size.
Check the gaps
Finish with source coverage before treating the estimates as a city ranking.
- Urban centre
- A dense, connected group of population-grid cells; it can differ from a city or metro boundary.
- One-kilometre share
- The estimated percentage of the urban-centre population inside a straight-line one-kilometre buffer around a recorded facility.
- Recorded facility
- A hospital or pharmacy present in the open map data used by the JRC, which may be incomplete.
- Peer
- Another included urban centre with a modelled population within 25% of the selected centre.
Global urban centres · 2025 estimateOne kilometre
One kilometre
from care
See how many people a global city database places within one kilometre of a recorded hospital or pharmacy.
A nearby facility can matter when someone needs care. This project compares the same straight-line radius across cities, then shows where the underlying facility map is incomplete.
Start here
Choose an urban centre
One choice updates every view. The list includes 1,567 centres with at least 100,000 people and both facility measures.
How much of Indianapolis is inside the radius?
Each grid stands for 100 people in the modelled urban-centre population. A filled mark represents one percentage point within a straight-line one-kilometre buffer.
Modelled population418.1K
Urban-centre area254 km²
Income groupHigh income
UN regionNorthern America
Pharmacies1 km radius
2.9%of the urban-centre population is estimated within one kilometre of a recorded pharmacy.
How to read this: these are estimates around facilities present in the source map. A low value can reflect true distance, missing map records, or both.
Where does Indianapolis sit among its peers?
The field includes 232 centres with populations within 25% of Indianapolis. Move the city control to redraw the comparison.
Pharmacy share rises ↑
Hospital share rises →
How to read this: right means a larger hospital share; up means a larger pharmacy share. The crosshair marks Indianapolis. This is a comparison of source estimates, not a ranking of health systems.
More recorded facilities do not place everyone nearby
Switch facility type to compare the number recorded per 100,000 people with the share inside one kilometre. The two measures describe different things.
How to read this: right means more recorded facilities per person; up means a larger nearby share. City area and where facilities sit both affect the result.
The map has large gaps
The database contains 11,422 urban centres, but both facility measures are available for only 2,248. Coverage also differs by income group.
Hospital measure present Pharmacy measure present
Low income
1,050 centres37.8%4.5%
Lower Middle
4,591 centres40.7%9.9%
Upper Middle
4,179 centres64.6%21.5%
High income
1,593 centres91.8%66.8%
How to read this: longer bars mean the measure exists for more urban centres in that income group. The outlined row contains Indianapolis. Uneven coverage makes cross-city rankings especially risky.
What this one-kilometre measure can and cannot show
It is a straight-line buffer. It does not follow streets, entrances, travel time, opening hours, cost, capacity, quality, or eligibility.
The facilities come from open map data. The JRC warns that OpenStreetMap completeness and accuracy limits carry into these indicators. Missing records can lower a city's estimate.
An urban centre is not a legal city boundary. The JRC groups dense, connected population-grid cells, so its population and area can differ from familiar municipal or metro figures.
Why this exists
The question
How much of an urban centre's population does this global dataset estimate within one kilometre of a recorded hospital or pharmacy, how does that compare with similarly sized places, and how should incomplete facility coverage limit the comparison?
What to try
Choose an urban centre to update its paired proximity fields, similar-population comparison, facility-count view, and source-coverage context.
Method and limits
About the data
I found the health theme from the Global Human Settlement Urban Centre Database through TidyTuesday's September 29, 2026 release. I checked the underlying European Commission Joint Research Centre dataset, technical report, citation requirements, and CC BY 4.0 reuse terms. The JRC defines urban centres from population density, size, and connected grid cells rather than legal city limits. Its hospital and pharmacy indicators use 2024 facility locations and a 2025 population grid. The proximity share counts modelled population inside a straight-line one-kilometre buffer, not a walking route or travel time.
The checked source CSV has 11,422 urban-centre rows and is pinned to TidyTuesday commit 4888498fd80a2d732e93a7c002a4272a313996da. The 1,471,778-byte file has SHA-256 905832bc244278863f2688f1e763ab415811da4d2a2e8969077ab8f17542d355. A reproducible Python reducer verifies both the hash and row count, then retains the 1,567 named centres with at least 100,000 modelled residents, an income group, facility counts, and both one-kilometre shares. It writes a deterministic 150,508-byte browser snapshot with SHA-256 0aa8e1a0904c4630c3f8741bca8756a764796155355688be83fc064c2e4168c6. The page reads only that checked-in file and makes no runtime request.
The peer field uses centres whose populations fall from 75% to 125% of the selected centre's population. Percentiles count the share of peers at or below the selected value. Facility rates divide the source's recorded facility count by modelled population and multiply by 100,000. The chart caps its horizontal display at the peer group's 95th percentile so extreme counts do not compress the rest; the selected exact rate remains in text. Group coverage uses all source rows with a stated World Bank income group.
The JRC documentation says the facility data inherit OpenStreetMap limitations in completeness and accuracy. A low estimate can reflect distance, missing facility records, or both. The measure does not include routes, entrances, opening hours, cost, capacity, quality, or eligibility. The data cannot establish actual access to care, compare health-system performance, explain why two cities differ, or support a causal claim.
Skills used
- Data analysis
- Data engineering
- Statistical reasoning
- Systems design
- Visualization
- Information design
- Interaction design
- Visual design
- Creative coding
- Product thinking
- Editorial storytelling
- Accessibility
- Performance
What the data shows
- The source provides a hospital proximity share for 6,434 of 11,422 urban centres and a pharmacy share for 2,470. Both measures and both facility counts are present for 2,248 centres.
- Among the 1,567 included centres with at least 100,000 modelled residents, the median estimated share within one kilometre is 32.1% for a recorded hospital and 16.3% for a recorded pharmacy.
- Indianapolis is estimated at 10.1% near a recorded hospital and 2.9% near a recorded pharmacy. Its 232 similarly sized peers have medians of 32.7% and 15.5%, but incomplete map records prevent treating that gap as a direct measure of real access.