Updated 9th April 2022

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9,900 new COVID cases across England daily

Written byZOE Editorial Staff

    By combining COVID swab testing with data from the COVID Symptom Study app, we are able to estimate the number of new daily COVID cases within the community

    Data from the COVID Symptom Study suggests there are currently 9,900 daily new cases of COVID across England. 

    This excludes care homes [*] and asymptomatic cases. These results are based on a group of 980,000 people using our app, of whom 18,000 were invited to do COVID swab tests after showing early signs of coronavirus infection. These tests were provided by the Department of Health and Social Care, either via a self-administered home test kit or regional testing centres.

    Developed by health technology company ZOE, the COVID Symptom Study app now has more than 3.6 million users across the UK, US and Sweden, making it the largest ongoing coronavirus study in the world.

    All areas of England are seeing new cases, but levels in the North are around twice those in the South. These figures give an up to date view of COVID infection rates, unlike deaths which lag by about a month.

    How we are calculating these figures

    The figure of 9,900 was calculated using swab testing and app symptom data collected over the last two weeks (2-15 May), from users of all ages and spread throughout England. This makes it the first time that digital health data from a very large population has been combined with physical COVID swab tests to create an accurate view of what COVID looks like in the population on a day-by-day basis. 

    These results were based on 980,000 people contributing digitally of whom 18,000 received rapid testing for COVID infection in the two weeks from 2-15 May. Those invited for testing include individuals using our app who have reported being healthy for at least nine days before they log new symptoms for the first time. We have aggregated these two weeks in order to get a large enough population to allow us to estimate regional variations, as well as overall levels in England.

    Facilitating a safe exit from lockdown

    The ability to accurately estimate the number of new daily COVID cases within the community via technology can be a critical part of the UK’s fight against COVID, alongside ONS surveys that report weekly or monthly based on random swab testing or changes in antibody testing. 

    With all eyes on “r”, it is critical that the number of daily new cases does not rise as we ease out of lockdown. The COVID Symptom Study enables over 3 million people to contribute, and so provides a more current picture of how the COVID situation is changing. It can also highlight regional differences and show potential increases in the virus before other detection methods. 

    Daily new cases across England

    The map below shows the rates across the different regions of England. The data for each region is presented as a range, because the absolute infection rates are now low. These estimates show a two fold difference between North and South, but should be treated with caution as the number of actual cases is relatively small. 

    We do not yet have sufficient numbers to estimate Northern Ireland, and Wales and Scotland have not yet joined the COVID testing scheme, but we hope to extend testing to those nations shortly.

    The daily new cases estimate does not account for those in the population who are asymptomatic (i.e. show no symptoms but can still spread the virus), as we cannot detect these cases by those reporting their health using the app. These figures also exclude care homes as there is not enough data from the app to estimate this population at this point.

    Daily new cases of COVID-19 in England between 2-15 May

    Jonathan Wolf, CEO of ZOE comments: 

    “These results are only possible because of the millions of people who are generously recording their health daily on the COVID Symptom Study app. By combining physical swab testing with daily digital health reporting we are now able to understand the daily new cases of infection. This was previously a mystery. We will be updating this regularly, which will provide vital information to the NHS and government as we all look to ease our way out of lockdown”

    Professor Tim Spector comments

    “This new incidence rate will be capturing the day-to-day change in the disease which means we will be able to tell the active status of the virus within the population. As a result we will know whether the infection rate is stable, falling or increasing very quickly which will influence decisions around loosening lockdown.

    I would like to take this opportunity to thank the input of the SAGE SPI-M modelling team and the Department of Health and Social Care testing team, who continue to support the app’s work and who have enabled this testing to happen. Without them these results would not be possible“


    [*] This analysis requires swab testing, which was kindly provided by the English Department of Health and Social Care. The results do not currently include Wales & Scotland as they are not currently participating in this study, but ZOE hopes to extend testing to those nations shortly.  Testing is happening in Northern Ireland, but the number of participants is too few to generate an accurate estimate. These figures exclude care homes as there is not enough data from the app to estimate this population.

    The regional breakdown of daily new cases per 1M people is: 

    • England overall: 156-199

    • South East: 101-176

    • London: 88-179

    • Midlands: 169-310

    • East of England: 109-224

    • South West: 71-172

    • North East and Yorkshire: 157-304

    • North West: 217-412

    The regional breakdown of total daily new cases is:

    • England overall: 8700-11100

    • South East: 900-1600

    • London: 800-1600

    • Midlands: 1800-3300

    • East of England: 700-1500

    • South West: 400-1000

    • North East and Yorkshire: 1300-2600

    • North West: 1500-2900

    More detail on the analysis

    Our starting population is people on the app in England and Northern Ireland who have reported healthy for at least nine days. Every day, we identify those users who report sick for the first time, and we invite them to take a COVID test. For this particular analysis we only use test results from these selected individuals.

    In the two weeks from 2nd to the 15th of May, 18,000 of these users got tested for COVID and reported their results. We have aggregated these two weeks, so as to get a large enough population to estimate regional variations as well as overall levels in England.

    We consider the number of positive test results in the tested sample as a Binomial random variable to estimate the probability for a recently sick user to have COVID and to get a confidence interval on this estimate.

    Assuming that the proportion of newly sick users per day in our user base is representative of that for the entire population, and by using the estimated probability for a recently sick user to have COVID, we estimated the daily new cases of COVID in the different NHS regions of England. These figures may be an under-estimate if the app population is falling sick less often than the overall population. It also misses individuals who do not feel any symptoms and so do not report unwell, which is true of all approaches except random sampling.

    Additional notes:

    About ZOE

    ZOE is a healthcare science company using data-driven research to tackle the world’s health issues. By using machine learning combined with digital technologies like mobile phones, ZOE enables large-scale scientific studies to tackle issues like COVID-19, inflammation and the impact of nutrition on health. Located in London and Boston, ZOE was founded by Professor Tim Spector of King’s College London, machine learning leader Jonathan Wolf and entrepreneur George Hadjigeorgiou. ZOE has carried out the largest nutritional studies of their kind in the world, and was named one of the Deloitte Fast 50 Rising Stars in 2019 for the company’s contribution to science enabled by technology and machine learning. 

    For more information on ZOE’s mission and science visit www.joinzoe.com.

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