Due to changes in the collection and availability of data on COVID-19, this website will no longer be updated. The webpage will no longer be available as of 11 May 2023. On-going, reliable sources of data for COVID-19 are available via the COVID-19 dashboard and the UKHSA

GLA Covid-19 Mobility Report

Since March 2020, London has seen many different levels of restrictions - including three separate lockdowns and many other tiers/levels of restrictions, as well as easing of restrictions and even measures to actively encourage people to go to work, their high streets and local restaurants. This reports gathers data from a number of sources, including google, apple, citymapper, purple wifi and opentable to assess the extent to which these levels of restrictions have translated to a reductions in Londoners' movements.

The data behind the charts below come from different sources. None of these data represent a direct measure of how well people are adhering to the lockdown rules - nor do they provide an exhaustive data set. Rather, they are measures of different aspects of mobility, which together, offer an overall impression of how people Londoners are moving around the capital. The information is broken down by use of public transport, pedestrian activity, retail and leisure, and homeworking.

Public Transport

For the transport measures, we have included data from google, Apple, CityMapper and Transport for London. They measure different aspects of public transport usage - depending on the data source. Each of the lines in the chart below represents a percentage of a pre-pandemic baseline.

https://cdn.datapress.cloud/london/img/dataset/60e5834b-68aa-48d7-a8c5-7ee4781bde05/2025-06-09T20%3A54%3A15/6b096426c4c582dc9568ed4830b4226d.webp" alt="Embedded Image" />

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Citymapper Citymapper mobility index 2021-09-05 Compares trips planned and trips taken within its app to a baseline of the four weeks from 6 Jan 2020 7.9% 28% 19% Google Google Mobility Report 2022-10-15 Location data shared by users of Android smartphones, compared time and duration of visits to locations to the median values on the same day of the week in the five weeks from 3 Jan 2020 20.4% 40% 27% TfL Bus Transport for London 2022-10-30 Bus journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 34% 24% TfL Tube Transport for London 2022-10-30 Tube journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 30% 21% Pedestrian activity

With the data we currently have it's harder to estimate pedestrian activity and high street busyness. A few indicators can give us information on how people are making trips out of the house:

https://cdn.datapress.cloud/london/img/dataset/60e5834b-68aa-48d7-a8c5-7ee4781bde05/2025-06-09T20%3A54%3A15/bcf082c07e4d7ff5202012f0a97abc3a.webp" alt="Embedded Image" />

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Walking Apple Mobility Index 2021-11-09 estimates the frequency of trips made on foot compared to baselie of 13 Jan '20 22% 47% 36% Parks Google Mobility Report 2022-10-15 Frequency of trips to parks. Changes in the weather mean this varies a lot. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail & Rec Google Mobility Report 2022-10-15 Estimates frequency of trips to shops/leisure locations. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail and recreation

In this section, we focus on estimated footfall to shops, restaurants, cafes, shopping centres and so on.

https://cdn.datapress.cloud/london/img/dataset/60e5834b-68aa-48d7-a8c5-7ee4781bde05/2025-06-09T20%3A54%3A16/b62d60f723eaafe64a989e4afec4c62b.webp" alt="Embedded Image" />

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Grocery/pharmacy Google Mobility Report 2022-10-15 Estimates frequency of trips to grovery shops and pharmacies. Compared to baseline of 5 weeks from 3 Jan '20 32% 55.00% 45.000% Retail/rec <a href="https://ww

Due to changes in the collection and availability of data on COVID-19, this website will no longer be updated. The webpage will no longer be available as of 11 May 2023. On-going, reliable sources of data for COVID-19 are available via the COVID-19 dashboard and the UKHSA

GLA Covid-19 Mobility Report

Since March 2020, London has seen many different levels of restrictions - including three separate lockdowns and many other tiers/levels of restrictions, as well as easing of restrictions and even measures to actively encourage people to go to work, their high streets and local restaurants. This reports gathers data from a number of sources, including google, apple, citymapper, purple wifi and opentable to assess the extent to which these levels of restrictions have translated to a reductions in Londoners' movements.

The data behind the charts below come from different sources. None of these data represent a direct measure of how well people are adhering to the lockdown rules - nor do they provide an exhaustive data set. Rather, they are measures of different aspects of mobility, which together, offer an overall impression of how people Londoners are moving around the capital. The information is broken down by use of public transport, pedestrian activity, retail and leisure, and homeworking.

Public Transport

For the transport measures, we have included data from google, Apple, CityMapper and Transport for London. They measure different aspects of public transport usage - depending on the data source. Each of the lines in the chart below represents a percentage of a pre-pandemic baseline.

https://cdn.datapress.cloud/london/img/dataset/60e5834b-68aa-48d7-a8c5-7ee4781bde05/2025-06-09T20%3A54%3A15/6b096426c4c582dc9568ed4830b4226d.webp" alt="Embedded Image" />

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Citymapper Citymapper mobility index 2021-09-05 Compares trips planned and trips taken within its app to a baseline of the four weeks from 6 Jan 2020 7.9% 28% 19% Google Google Mobility Report 2022-10-15 Location data shared by users of Android smartphones, compared time and duration of visits to locations to the median values on the same day of the week in the five weeks from 3 Jan 2020 20.4% 40% 27% TfL Bus Transport for London 2022-10-30 Bus journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 34% 24% TfL Tube Transport for London 2022-10-30 Tube journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 30% 21% Pedestrian activity

With the data we currently have it's harder to estimate pedestrian activity and high street busyness. A few indicators can give us information on how people are making trips out of the house:

https://cdn.datapress.cloud/london/img/dataset/60e5834b-68aa-48d7-a8c5-7ee4781bde05/2025-06-09T20%3A54%3A15/bcf082c07e4d7ff5202012f0a97abc3a.webp" alt="Embedded Image" />

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Walking Apple Mobility Index 2021-11-09 estimates the frequency of trips made on foot compared to baselie of 13 Jan '20 22% 47% 36% Parks Google Mobility Report 2022-10-15 Frequency of trips to parks. Changes in the weather mean this varies a lot. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail & Rec Google Mobility Report 2022-10-15 Estimates frequency of trips to shops/leisure locations. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail and recreation

In this section, we focus on estimated footfall to shops, restaurants, cafes, shopping centres and so on.

https://cdn.datapress.cloud/london/img/dataset/60e5834b-68aa-48d7-a8c5-7ee4781bde05/2025-06-09T20%3A54%3A16/b62d60f723eaafe64a989e4afec4c62b.webp" alt="Embedded Image" />

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Grocery/pharmacy Google Mobility Report 2022-10-15 Estimates frequency of trips to grovery shops and pharmacies. Compared to baseline of 5 weeks from 3 Jan '20 32% 55.00% 45.000% Retail/rec <a href="https://ww

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

Public transport in England experienced a substantial decline during the COVID-19 pandemic, however the number of trips per person per year began growing again in 2021. The average number of trips by buses outside London rose to ** per person per. Buses outside London had already been declining before the COVID-19 pandemic.

Context:

The fate of the world changed in 2020.

Daily activities were impacted, impeded, and wouldn't be the same forever.

In partnership with Microsoft and the University of Oxford, A Tale of Two Cities is a Data AI hackathon that aims to address trends during and after the pandemic.

I will present my work at this hackathon through my association with the University of Oxford as an AI Tutor for the Artificial Intelligence: Cloud and Edge Implementations course.

Acknowledgments:

I'd like to thank the original authors of these data sources!

Relevant data was extracted from these sources and split into two phases: - COVID era (before 1st February, 2022), and - Post COVID era (after 1st February, 2022)

This helped me to compare trends in New York and London over time. https://i.imgur.com/KFRaB51.png" alt="">

Ipsos UK conducted a series of six waves of UK-wide online surveys through the duration of the COVID-19 pandemic on behalf of the Department for Transport as part of the All Change? research programme. The research programme was designed in response to the COVID-19 pandemic to measure and explore the reasons for current and intended changes in travel behaviour amongst the British public.

Fieldwork for the first wave took place in May/June 2020 while the sixth and final wave took place in November 2021. All survey interviews were conducted online withadults aged 16-75 years old across England, Wales, Scotland and Northern Ireland. The data are longitudinal; however, they include additional fresh samples at each wave. The data are provided here in a single dataset file covering all six waves.

Respondents at waves 2-6 were drawn from those that had taken part in previous waves and agreed to be recontacted. While wave 2 involved 'top-up' sampling to boost the overall sample to approximately 4,000, this was not the case at wave 3 when the sample was drawn exclusively from the longitudinal cohort and contained no 'fresh' samples. At wave 4, a targeted 'top-up' exercise was undertaken to bolster the numbers among a selection of groups and geographies available for recontact at wave 5 (this reached 564 respondents). Waves 5 and 6 also involved a full 'top-up' exercise to secure samples of over 4,000.

At each wave, the survey questionnaire was translated into the Welsh language with respondents in Wales given the choice of whether to complete the survey in Welsh or in English.

Further information and reports are available on the GOV.UK web site.

Introduction

This page comprises the additional datasets used for the COVID-19 Global Forecasting Challenge (currently in week 3). Only datasets that have not been hosted on Kaggle will be uploaded here: * Oxford COVID-19 Government Response Tracker * Assessment Capacities Project COVID-19 Government Measures

UPDATE: Please see my notebook on the COVID-19 Global Forecasting Challenge (Week 3) competition here for merging the data.

Oxford COVID-19 Government Response Tracker

The Oxford COVID-19 Government Response Tracker (OxCGRT) provides a systematic cross-national, cross-temporal measure to understand how government responses have evolved over the full period of the disease’s spread. The project tracks governments’ policies and interventions across a standardized series of indicators and creates a composite index to measure the stringency of these responses. Data is collected and updated in real time by a team of dozens of students and staff at Oxford University. Read the white paper here. Access the OxCGRT website here.

Indicators

The OxCGRT tracks 11 indicators of government response:

1. School closing (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend closing
     • 2 = Require closing
2. Workplace closing (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend closing
     • 2 = Require closing
3. Cancel public events (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend cancelling
     • 2 = Require cancelling
4. Close public transport (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend closing
     • 2 = Require closing
5. Public info campaigns(with geographic scope)
   • Ordinal scale:
     • 0 = No COVID-10 public information campaign
     • 1 = COVID-10 public information campaign
6. Restrictions on internal movement (with geographic scope)
   • Ordinal scale:
     • 0 = No measures
     • 1 = Recommend movement restriction
     • 2 = Restricted movement
7. International travel controls
   • Ordinal scale:
     • 0 = No measures
     • 1 = Screening
     • 2 = Quarantine on high-risk regions
     • 3 = Ban on high-risk regions
8. Fiscal measures
   • Value of fiscal stimuli in USD
9. Monetary measures
   • Value of interest rate in %
10. Emergency investment in health care
    • Value of new short-term spending on health in USD
11. Investment in vaccines
    • Value of investment in USD

Indicators with geographic scope are coded in the following way: - 0 = Targeted - 1 = General

The Assessment Capacities Project (ACAPS) COVID-19 Government Measures Dataset

This dataset comprises government measures and descriptions of these measures by country and date. The measures include:

1. Social distancing
2. Movement restrictions
3. Public health measures
4. Social and economic measures
5. Lockdowns

Descriptors of these measures include: - Date of implementation - Specific measure - Penalties for non-compliance - Source (e.g. government, media)

As of October 2020, 92 percent of survey respondents in Great Britain supported the measure that anyone who tests positive for the coronavirus (COVID-19) has to self-isolate for fourteen days. Furthermore, almost 90 percent of Brits support the compulsory wearing of masks on public transport and in shops. On the other hand, less than 40 percent of respondents would support the closing of schools and nurseries.

The latest number of confirmed coronavirus cases in the UK can be found here.

Dataset containing results of the Bus User Satisfaction Survey that is carried out annually. The data shows how Leicester compares with other authorities in the overall satisfaction of bus users.Please note due to coronavirus restrictions, the survey was not carried out in 2020 or 2021.This dataset is also part of a dashboard that has been created showing a range of transport related data. The dashboard can be viewed here.

Explore the interactive maps showing the average delay and average speed on the Strategic Road Network and Local ‘A’ Roads in England, in 2020.

Additional http://bit.ly/COVID_Congestion_Analysis" class="govuk-link">Analysis on the impact of the Coronavirus (COVID-19) pandemic on the road journeys is also available. This story map contains charts and interactive maps for road journeys in England.

On the Strategic Road Network (SRN) for 2020, the average delay is estimated to be 6.7 seconds per vehicle per mile compared to speed limits travel times, a 29.5% decrease compared to 2019.

The average speed is estimated to be 61.8mph, 5.1% up on 2019.

In 2020, on average 42.1% of additional time was needed compared to speed limits travel times, on individual road sections of the SRN to ensure on time arrival. This is down 25.2 percentage points compared to 2019, so on average a lower proportion of additional time is required.

On local ‘A’ roads for 2020, the average delay is estimated to be 33.9 seconds per vehicle per mile compared to free flow travel times. This is a decrease of 22.8% on 2019.

The average speed is estimated to be 27.3 mph. This is an increase of 8.2% on 2019.

The outbreak of coronavirus (COVID-19) has had a marked impact on everyday life, including on congestion on the road network. As these data are affected by the coronavirus pandemic in the UK, caution should be taken when interpreting these statistics and comparing them with previous time periods. While values had previously been moving towards their pre-lockdown levels, this trend appears to have reversed in the months following September 2020.

Contact us

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Objectives: To study the prevalence of COVID-19 health protective behaviours before and after rules eased in England on the 19th July 2021.Design: Observational study pre (12th-18th July) and post (26th July-1st August) 19th July, and a cross-sectional online survey (26th to 27th July).Setting: Observations occurred in supermarkets (n = 10), train stations (n = 10), bus stops (n = 10), a coach station (n = 1) and a London Underground station (n = 1). The survey recruited a nationally representative sample.Participants: All adults entering the observed locations during a one-hour period (n = 3819 pre- and n = 2948 post-19th July). In the online survey, 1472 respondents reported having been shopping for groceries/visited a pharmacy and 566 reported having used public transport or having been in a taxi/minicab in the last week.Main outcome measures: We observed whether people wore a face covering, maintained distance from others and cleaned their hands. We investigated self-reports of wearing a face covering while in shops or using public transport.Results: In most locations observed, the proportion of people wearing face coverings, cleaning the hands and maintaining physical distance declined post 19th July. Pre 19th July, 70.2% (95% CI 68.7 to 71.7%) of people were observed to be wearing a face covering versus 55.8% (54.2 to 57.9%) post 19th July. Equivalent rates for physical distancing were 40.9% (39.0 to 42.8%) versus 29.5% (27.4 to 31.7%), and for hand hygiene were 4.4% (3.8 to 5.1%) versus 3.9% (3.2 to 4.6%). Self-reports of “always” wearing face coverings were broadly similar to observed rates.Conclusions: Adherence to protective behaviours was sub-optimal and declined during the relaxation of restrictions, despite appeals to exercise caution. Self-reports of “always” wearing a face covering in specific locations appear valid.