With the rollout of the Covid-19 vaccine underway, the Financial Times (FT), one of the world’s leading news organisations, was looking for an accurate way to analyse how easily accessible Covid vaccination centres are across England.
Analysing the accessibility of Covid vaccination centres across England
With 1,220 vaccination sites in England, the FT specifically wanted to analyse how accessible each Covid vaccination site is by travel time using different modes of transport.
Often, location accessibility is analysed using straight-line distance rather than time. The downside of this approach is that it assumes people can travel directly and doesn’t take into account the available transport options and local geography of a location. As a result, it can be an inaccurate way to understand accessibility.
As John Burn-Murdoch, Senior Data-Visualisation Journalist at the FT, explains:
“Most analyses of geographical service coverage focus only on the distance from point A to point B, but in reality, travel time is a much better metric — especially in a country like the UK where public transport service varies greatly from place to place.”
In order to conduct the travel time analysis at the scale required by the FT, the team needed a tool that would allow them to automate the process of calculating travel time polygons, also known as isochrones, for tens of thousands of points.
Generating thousands of travel time isochrones with the TravelTime API
Having identified the need to analyse travel time catchment areas, the FT team chose to use the TravelTime API to conduct the analysis.
The first step was to use the API to calculate multiple travel time isochrones for each of the 1,220 vaccination centres in England.
These isochrones would show how far away someone could be from each vaccination centre and still reach it within a given travel time and using a given mode of transport.
The team then overlaid the travel time isochrones over the 35,000 neighbourhoods in England and used the intersections of the two datasets to determine how many people lived within reach of a vaccination site and how many fell outside of the catchment area, depending on the transport mode.
The team was also able to layer on additional data, such as car ownership, to analyse access to vaccination centres by driving and other transport modes.
Highlighting differences in access to Covid vaccination centres
Using the TravelTime API, the FT analysis revealed that roughly 5.5 million people in England live more than one hour by public transport from their nearest vaccination centre.
The analysis also highlighted the uneven distribution of vaccine centres across the country, particularly in rural areas.
Achieving a more accurate analysis with travel time data
For the FT, one of the biggest benefits of using the TravelTime API was the ability to run large datasets with no interruption in performance.
“We were very impressed with the reliability and stability of the API,” says John. “We could confidently leave scripts running overnight, working their way through thousands of datapoints, with no fear of waking up to find an error message.”
Additionally, the API was able to provide more accurate results than would have been achievable had the team used a distance-based approach.
“Without the API, we would have had to revert back to the cruder metric of distance from home to vaccination site,” John explains. “However, this would have been so much of a simplification as to render the results unreliable, given the number of people who live within, say, 10 miles of a vaccination site, but have no viable means of getting there by public transport.”
You can read the full analysis from the FT here.
Create travel time polygons and matrices with the TravelTime API