## [1] "Updated on 2020-09-04 10:18:02"
Reading Guide
Data
This report is based on mobility data produced for the Disease Prevention Maps tools by the Facebook Data for Good Program (https://dataforgood.fb.com/tools/disease-prevention-maps/), with access facilitated by the COVID-19 Mobility Data Network (https://www.covid19mobility.org/).
These data represent people who use Facebook in this region and have location services enabled. Data are aggregated at a 600m x 600m sized tiles and vectors (lines) are drawn connecting all areas to each other. These lines provide data in both directions (going from area A to B and from area B to A). These data include:
- The starting point of each line
- The ending point of each line
- The number of people who traveled along this line in both directions for the 45 days preceeding the collection of the data (noted on the bottom of every set of figures)
- The number of people who traveled along this line in both directions for a given time period.
- The length of the line in euclidean distance (as the crow flies, not through the existing travel network).
- Data are aggregated in 8 hour blocks, one of these blocks for UK is from 2100 to 0500. We treat this as belonging to the date that 2100 is in.
Pointers on evaluating the data
- It is best to look at percent change in trips and total distance traveled as two views of a “mobility” metric. For example, if the number of trips goes up but the total distance traveled goes down, it likely means that people are moving a bit more but mainly going shorter distances, perhaps just exercising or walking around the neighborhood.
- When looking at the travel network remember that some people will live at boundaries of the area of interest, therefore, it may just be short distance movements that are resulting in people traveling from one location to another. Long distance travel connections are more difficult to rationalize and warrant further investigation.
- You’ll often see an uptick in movement and total distance traveled on the weekends. This is generally normal behavior, though deviation from this during lock down measures should be evaluated.
- Keep an eye on the Y axis, it may be log scaled to better show the data. The labels are correct but rates of change are more extreme than they appear.
Key Takeaways
- The uptick in movement has generally leveled off. There are some new travel patterns for the regions with most travel that should be evaluated to ensure that the networks make sense and are expected.
UK Summary
City Specific Analysis
Most Travel
Manchester
Glasgow City
Birmingham
Camden and City of London
Wandsworth
Tower Hamlets
Lewisham and Southwark
Merton, Kingston upon Thames and Sutton
Ealing
Harrow and Hillingdon
Hounslow and Richmond upon Thames
Staffordshire CC
Hackney and Newham
Redbridge and Waltham Forest
Greater Manchester North East
Greater Manchester South East
Greater Manchester South West
Warwickshire
Leeds
Tyneside
Brent
Barking & Dagenham and Havering
Liverpool
South Nottinghamshire
Hertfordshire
Leicestershire CC and Rutland
Kensington & Chelsea and Hammersmith & Fulham
South and West Derbyshire
Wolverhampton
Nottingham
Lambeth
East Merseyside
Bath and North East Somerset, North Somerset and South Gloucestershire
Dudley
Greater Manchester North West
Bexley and Greenwich
Berkshire
Mid Lancashire
South Hampshire
West Surrey
Bristol, City of
Solihull
Sunderland
North Lanarkshire
Haringey and Islington
Sheffield
Barnsley, Doncaster and Rotherham
Walsall
Calderdale and Kirklees
Bradford
Barnet
Enfield
Durham CC
Leicester
Sandwell
Stoke-on-Trent
Wakefield
Devon CC
Central Hampshire
Medium Travel
Coventry
South Lanarkshire
East Riding of Yorkshire
Cheshire East
South Teesside
Hartlepool and Stockton-on-Tees
East Surrey
Chorley and West Lancashire
Kent Thames Gateway
Bromley
Inverclyde, East Renfrewshire and Renfrewshire
Kingston upon Hull, City of
Edinburgh, City of
Buckinghamshire CC
Essex Thames Gateway
North Nottinghamshire
Worcestershire
Derby
Medway
Plymouth
Cheshire West and Chester
East Derbyshire
Cardiff and Vale of Glamorgan
Belfast
Southampton
Central Bedfordshire
Gwent Valleys
Portsmouth
Croydon
Wirral
North Hampshire
West Essex
Oxfordshire
East Lancashire
Mid Kent
Blackpool
Norwich and East Norfolk
West Northamptonshire
Thurrock
West Kent
Northumberland
Warrington
Sefton
Cambridgeshire CC
Heart of Essex