In early-February, 2020, the first cases of the coronavirus (COVID-19) were reported in the United Kingdom (UK). The number of cases in the UK has since risen to 24,243,393, with 1,062 new cases reported on January 13, 2023. The highest daily figure since the beginning of the pandemic was on January 6, 2022 at 275,646 cases.

COVID deaths in the UK COVID-19 has so far been responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK has one of the highest death toll from COVID-19 in Europe. As of January 13, the incidence of deaths in the UK is 298 per 100,000 population.

Regional breakdown The South East has the highest amount of cases in the country with 3,123,050 confirmed cases as of January 11. London and the North West have 2,912,859 and 2,580,090 cases respectively.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In early-February 2020, the first cases of COVID-19 in the United Kingdom (UK) were confirmed. As of December 2023, the South East had the highest number of confirmed first episode cases of the virus in the UK with 3,180,101 registered cases, while London had 2,947,727 confirmed first-time cases. Overall, there has been 24,243,393 confirmed cases of COVID-19 in the UK as of January 13, 2023.

COVID deaths in the UK COVID-19 was responsible for 202,157 deaths in the UK as of January 13, 2023, and the UK had the highest death toll from coronavirus in western Europe. The incidence of deaths in the UK was 297.8 per 100,000 population as January 13, 2023.

Current infection rate in Europe The infection rate in the UK was 43.3 cases per 100,000 population in the last seven days as of March 13, 2023. Austria had the highest rate at 224 cases per 100,000 in the last week.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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 of January 12, 2023, COVID-19 has been responsible for 202,157 deaths in the UK overall. The North West of England has been the most affected area in terms of deaths at 28,116, followed by the South East of England with 26,221 coronavirus deaths. Furthermore, there have been 22,264 mortalities in London as a result of COVID-19.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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

These documents were produced through a collaboration between GLA, PHE London and Association of Directors of Public Health London. The wider impacts slide set pulls together a series of rapid evidence reviews and consultation conversations with key London stakeholders. The evidence reviews and stakeholder consultations were undertaken to explore the wider impacts of the pandemic on Londoners and the considerations for recovery within the context of improving population health outcomes. The information presented in the wider impact slides represents the emerging evidence available at the time of conducting the work (May-August 2020). The resource is not routinely updated and therefore further evidence reviews to identify more recent research and evidence should be considered alongside this resource. It is useful to look at this in conjunction with the ‘People and places in London most vulnerable to COVID-19 and its social and economic consequences’ report commissioned as part of this work programme and produced by the New Policy Institute. Additional work was also undertaken on the housing issues and priorities during COVID. A short report and examples of good practice are provided here. These reports are intended as a resource to support stakeholders in planning during the transition and recovery phase. However, they are also relevant to policy and decision-making as part of the ongoing response. The GLA have also commissioned the University of Manchester to undertake a rapid evidence review on inequalities in relation to COVID-19 and their effects on London.

These reports present assessments of the available evidence concerning population change in London since the beginning of the COVID-19 pandemic. The main document (May 2021) is accompanied by a short summary report and an annex that provides an overview of the data sources considered. In February 2022 a report was released which integrated new evidence that had become available since the original analysis.

• This briefing presents evidence on the socio-economic impact of COVID-19 on London and Londoners​
• Topics included in the briefing focus on recent data releases published in the preceding months that tell us how social policy issues are evolving in London since the start of the COVID-19 pandemic

For more on the health and demographic impacts see the Demographic Impact Briefing and for labour market impacts see Labour Market Analysis. A page linking to all Covid-19 related data and analyses can be found here.

Given the paramount impacts of COVID-19 on people’s lives in the capital of the UK, London, it was foreseeable that the city’s crime patterns would have undergone significant transformations, especially during lockdown periods. This study aims to testify the crime patterns’ changes in London, using data from March 2020 to March 2021 to explore the driving forces for such changes, and hence propose data-driven insights for policy makers and practitioners on London’s crime deduction and prevention potentiality in post-pandemic era. (1) Upon exploratory data analyses on the overall crime change patterns, an innovative BSTS model has been proposed by integrating restriction-level time series into the Bayesian structural time series (BSTS) model. This novel method allows the research to evaluate the varied effects of London’s three lockdown periods on local crimes among the regions of London. (2) Based on the predictive results from the BSTS modelling, three regression models were deployed to identify the driving forces for respective types of crime experiencing significant increases during lockdown periods. (3) The findings solidified research hypotheses on the distinct factors influencing London’s specific types of crime by period and by region. In light of the received evidence, insights on a modified policing allocation model and supporting the unemployed group was proposed in the aim of effectively mitigating the surges of crimes in London.

This mapping tool enables you to see how COVID-19 deaths in your area may relate to factors in the local population, which research has shown are associated with COVID-19 mortality. It maps COVID-19 deaths rates for small areas of London (known as MSOAs) and enables you to compare these to a number of other factors including the Index of Multiple Deprivation, the age and ethnicity of the local population, extent of pre-existing health conditions in the local population, and occupational data. Research has shown that the mortality risk from COVID-19 is higher for people of older age groups, for men, for people with pre-existing health conditions, and for people from BAME backgrounds. London boroughs had some of the highest mortality rates from COVID-19 based on data to April 17th 2020, based on data from the Office for National Statistics (ONS). Analysis from the ONS has also shown how mortality is also related to socio-economic issues such as occupations classified ‘at risk’ and area deprivation. There is much about COVID-19-related mortality that is still not fully understood, including the intersection between the different factors e.g. relationship between BAME groups and occupation. On their own, none of these individual factors correlate strongly with deaths for these small areas. This is most likely because the most relevant factors will vary from area to area. In some cases it may relate to the age of the population, in others it may relate to the prevalence of underlying health conditions, area deprivation or the proportion of the population working in ‘at risk occupations’, and in some cases a combination of these or none of them. Further descriptive analysis of the factors in this tool can be found here: https://data.london.gov.uk/dataset/covid-19--socio-economic-risk-factors-briefing

Introduction

The 2023 mid-year estimate (MYE) is the current official estimate of the population for local authorities in England and Wales. Estimates are produced annually by the Office for National Statistics (ONS) and the 2023 MYE was published on 15 July 2024.

Comparison to previous MYE data

The previous MYE series (for the period 2012-2020) starts with the 2011 census estimate. Each subsequent year’s population is calculated by adding estimates of births, deaths and migration to the previous year’s population. The 2021 MYE represents a break in this series as it uses the 2021 census as its base.

The ONS revised the 2012-2020 MYE series to bring it in line with the 2021 MYE, so that comparisons could be made between between this series and the previous series. The values plotted on the chart are the revised values of the previously published estimates for 2011 to 2022, together with the estimates for 2023.

Key Points

• London’s mid-2023 population was 8.945 million
• London’s population increased by 76,300 persons compared to the previous mid-year value
• Components of change were as follows:
• 105,100 births and 53,500 deaths (natural change of 51,600)
• Net domestic migration was an outflow of 129,200
• Net international migration was an inflow of 154,100

Population Change

London’s 2023 population was 8,945,310. The first chart below shows the 2023 MYE in the context of previous estimates. There is an uptick after a temporary decrease in population which we attribute to the COVID-19 pandemic.

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/666cd938678c5361c953cb608e532416.webp" width="1152" alt="Embedded Image" />

Components of Change

Births, deaths and migration form the components of population change.

The 2023 MYE value for births was 4% lower than that in 2022, and for deaths 3% higher. The consequent value for natural change (births - deaths) was 10% lower than in 2022.

At -129,000, the value for domestic migration (migration within the UK) was nearly 3% higher than the 2022 value, so still significantly lower than the peak net outflow during the COVID-19 pandemic of -186,000. An outflow of domestic migrants from London is normal and this has been the case each year for the last two decades. This flow is partly because many international in-migrants initially settle in London before moving out to other parts of the UK. The second move in this sequence is counted as a domestic migration.

There has been a marked change in immigration since 2021. This can be attributed to the end of free movement for EU nationals, easing of travel restrictions following the COVID 19 pandemic, and the war in Ukraine. At over 150,000, the 2023 MYE value for London’s net international migration was more than 18% higher than 2022, and represents a considerable increase from 78,000 in 2021.

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/cb537d44954e11f7f7b7e2189ae74629.webp" width="1152" alt="Embedded Image" />

Age structure of the population

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/6d4cf55b96888dbc3aacfc1de5c664ec.webp" width="1152" alt="Embedded Image" />

Future Updates

The release of the next mid-year estimates is expected in July 2025.

The full ONS mid-year population estimates release and back series can be found on the ONS website: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates.

For information relating to London’s population see the demography pages of the London Datastore: https://data.london.gov.uk/demography/ or email demography@london.gov.uk.

An in-depth review of the available evidence for population change in London since the start of the coronavirus pandemic has been produced by GLA Demography: https://data.london.gov.uk/dataset/population-change-in-london-during-the-pandemic.

The Opinion Research team set up an online diary to capture the views, behaviours and experiences of a sample of Londoners during the coronavirus outbreak. Commencing in late May, this online diary ran for 8 weeks. Fortnightly summary reports can be found accessed below, and included: Week 1 and 2 – reflected on experiences during lockdown to date and explored views on easing lockdown. Week 3 and 4 – explored priorities for London’s recovery, both short and long-term, and views on the Test and Trace system. Week 5 and 6 – explored growing disengagement with the coronavirus outbreak and reflected on some of the positive impacts of lockdown.​ Week 7 and 8 – explored the idea of a 15-minute city and aspirations for the future of London. 

These files comprise the publicly available data for the COG-UK hospital-onset COVID-19 infection study. The individual CSV files provided are: - HOCI_public_dataset: Anonymized version of main study dataset, with one row per HOCI case included in the final analysis - HOCI_public_varlist: Variable descriptions for main study dataset - epi_data_combined: Weekly data on total SARS-CoV-2 +ve (cov_pos_epi) and -ve (cov_neg_epi) inpatients at each study site -community_incidence_summary: Weekly local community incidence data for each study site, per 100,000 people per week, obtained from UK government testing dashboard and weighted according to outer postcodes of inpatients at each site.

Notes on anonymisation: HOCI_public_dataset is an anonymised version of the main HOCI study database. In order to fully anonymise individuals, and because the focus of the study was on infection control actions rather than patient outcomes, all individual-level patient demographic and clinical characteristics have been removed. Site and ward names have been changed to anonymized codes, and all free text fields have been removed as some of these contained unblinded details of hospitals and wards. All date fields have been removed, with study week of SARS-CoV-2 +ve test result for each HOCI case provided.

Notes on acronyms: In ‘HOCI_public_varlist’, the following acronyms are used: AGP, aerosol-generating procedure CR, contact restrictions CT, contact tracing DIPC, Director of IPC HCAI, healthcare-associated infection HCW, healthcare worker IPC, infection prevention and control SR, sequence report SRO, sequence report output QM, quality management

All data relating to Coronavirus (COVID-19) mortality and long-term outdoor air pollution in London.

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="">

This is a subset of data taken from https://coronavirus.data.gov.uk / https://coronavirus-staging.data.gov.uk. Please follow this link for more information: https://coronavirus-staging.data.gov.uk/about-data