Coronavirus (COVID-19) Infection Survey pilot: England and Wales, 14 August 2020

Results include estimates for England and initial results for Wales. This survey is carried out in partnership with IQVIA, Oxford University and UK Biocentre.

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Cyswllt:
Email Emily Connors and Eleanor Fordham

Dyddiad y datganiad:
14 August 2020

Cyhoeddiad nesaf:
21 August 2020

1. Main points

  • An estimated 28,300 people (95% credible interval: 19,000 to 40,700) within the community population in England had the coronavirus (COVID-19) during the most recent week, from 3 to 9 August 2020, equating to around 1 in 1,900 individuals.

  • There is some evidence of a small increase in the percentage of people testing positive for COVID-19 in July, following a low point in June, but this appears to have now levelled off.

  • During the most recent week (3 to 9 August 2020), we estimate there were around 0.69 (95% credible interval: 0.42 to 1.08) new COVID-19 infections for every 10,000 people in the community population in England, equating to around 3,800 new cases per day (95% credible interval: 2,300 to 5,900).

  • There is evidence that the incidence rate for England has increased in the most recent weeks following a low point in June and appears to have now levelled off.

  • Between 26 April and 26 July, 6.2% of people tested positive for antibodies against SARS-CoV-2 on a blood test, suggesting they had the infection in the past. The percentage of people testing positive for antibodies is higher in London than in Yorkshire and The Humber, the East Midlands, the South East and the South West of England.

  • We have extended the survey to Wales; during the most recent week (3 to 9 August 2020), we estimate that 1,500 people in Wales had COVID-19 (95% credible interval: 400 to 3,500), which is around 1 in 2,100 people.

In this bulletin, we refer to the number of current COVID-19 infections within the community population; community in this instance refers to private residential households and it excludes those in hospitals, care homes or other institutional settings.

We use current COVID-19 infections to mean testing positive for SARS-CoV-2, with or without having symptoms, on a swab taken from the nose and throat.

All analysis was produced with our research partners at the University of Oxford.

How the data in this bulletin can be used

The data can be used for:

  • estimating the number of current positive cases in the community, including cases where people do not report having any symptoms

  • identifying differences in numbers of positive cases between different regions

  • estimating the number of new cases and change over time in positive cases

The data cannot be used for:

  • measuring the number of cases and infections in care homes, hospitals and other institutional settings

  • estimating the number of positive cases and new infections in smaller geographies, such as towns and cities

  • providing information about recovery time of those infected

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2. Number of people in England who had COVID-19

During the most recent week of the study1, we estimate that 28,300 people in England had the coronavirus (COVID-19) (95% credible interval: 19,000 to 40,700). This equates to 0.05% (95% credible interval: 0.03% to 0.07%) of the population in England or around 1 in 1,900 people (95% credible interval: 1 in 2,900 to 1 in 1,300). This is based on statistical modelling of the trend in throat and nose swab results.

Figure 1 presents estimates of infection rates over time. While the percentage of individuals testing positive for COVID-19 has decreased since the start of the study (26 April 2020), the estimates suggest there was a small increase in July since the lowest recorded estimate, which was at the end of June. This trend now appears to have levelled off.

The modelled estimates for the latest six-week period are based on 122,021 swab tests collected over this period. During these weeks, 58 individuals from 58 households tested positive.

Last week, we revised our approach to presenting previous data. To provide stability in estimates, we advise using estimates we published in previous bulletins as these are our official estimates of the rate and spread of COVID-19 infections in the community in England. Both these and the modelled estimates are presented in Figure 1 and are used to interpret change over time.

As this is a household survey, our figures do not include people staying in hospitals, care homes or other institutional settings. In these settings, rates of COVID-19 infection are likely to be different. More information about rates of COVID-19 in care homes can be found in Impact of coronavirus in care homes in England: 26 May to 19 June 2020.

Figure 1: There is some evidence of a small increase in people testing positive for COVID-19 in July 2020 after a low point in June, but this appears to have now levelled off

Estimated percentage of the population in England testing positive on nose and throat swabs for the coronavirus (COVID-19) daily since 29 June 2020

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Notes:

  1. These results are provisional and subject to revision.

  2. The break distinguishes between the latest six-week estimates, and the earlier periods, which were modelled on 22 July. Using data from only the most recent six weeks in the model enables us to continue to provide timely results.

  3. All estimates are subject to uncertainty, given that a sample is only part of the wider population. The model used to provide these estimates is a Bayesian model: these provide 95% credible intervals. A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

  4. Weekly official reported estimates from 6 July onwards are based on the midpoint (Thursday) modelled estimate of the given week.

  5. Weekly official reported estimates between 27 April and 5 July are based on average fortnightly weighted estimates reported each week, and are plotted at the midpoint (Sunday) of each fortnightly period.

  6. Initial weekly official reported estimates covering the full study period to date were not included, because the same time period was covered in the fortnightly weighted estimates.

Data download

We also present the estimates in non-overlapping 14-day periods in the dataset that accompanies this bulletin. These 14-day estimates are provided for context. While the confidence intervals for these estimates are overlapping, they show a similar trend to the modelled estimates in Figure 1 that the percentage of people testing positive for COVID-19 had increased in July, and appears to have now levelled off.

Information about how the modelled and 14-day non-overlapping estimates are calculated can be found in our methods article.

More about coronavirus

  • Find the latest on coronavirus (COVID-19) in the UK.
  • All ONS analysis, summarised in our coronavirus roundup.
  • View all coronavirus data.
  • Find out how we are working safely in our studies and surveys.

  • Notes for: Number of people in England who had COVID-19

    1. This is based on model estimates from the week’s midpoint, Thursday 6 August.
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    3. Regional analysis of the number of people in England who had COVID-19

    In the data used to produce these estimates, the number of people sampled in each region who tested positive for the coronavirus (COVID-19) is low relative to England overall. This means there is a higher degree of uncertainty in the regional estimates for this period, as indicated by larger credible intervals.

    During the most recent week of the study (3 to 9 August 2020), there was no evidence from this survey that there were differences in infection rates by regions. This is based on exploratory modelling of nose and throat swab test results.

    Looking at trends over time, from this survey there is no clear evidence to say that COVID-19 infection rates have changed over the most recent six-week period in any region. The percentage of people testing positive by region was calculated using a similar modelling approach to the national daily estimates in Section 2: Number of people in England who had COVID-19.

    The analysis is conducted over a six-week period, which means specific positive cases move into and then out of the sample. This causes variability between estimates over time, which is expected given the low number of positive tests by region.

    Figure 3: There is high uncertainty within regional estimates

    Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs daily by region since 29 June 2020, England

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    Notes:

    1. All results are provisional and subject to revision.

    2. These statistics refer to infections reported in the community, by which we mean private households. These figures exclude infections reported in hospitals, care homes or other institutional settings.

    Data download

    !

    Estimates of positive COVID-19 cases for the South East are incorrect in Coronavirus (COVID-19) Infection Survey pilot bulletins published between 25 June and 7 August 2020. The correct estimates are presented in this bulletin and a full back series can be found in the accompanying dataset for this bulletin.

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    4. Incidence rate in England

    Based on exploratory modelling (3 to 9 August), we estimate that there were 0.69 new infections per 10,000 people per day (95% credible interval: 0.42 to 1.08). This equates to 3,800 new infections per day (95% credible interval: 2,300 to 5,900).

    Our modelling suggests that the incidence of new cases of the coronavirus (COVID-19) has increased following our lowest estimate, which occurred at the end of June 2020, but there is evidence that this trend appears to have now levelled off.

    The modelling used to calculate the incidence rate is a Bayesian model that is based on the same approach used for estimating the positivity rates in this bulletin. The model uses all swab test results to estimate the incidence rate of new infections for each different type of respondent (by age, sex and region) who tested negative when they first joined the study. It is made to be representative of the overall population using population data. More information on the methodology of this approach is available.

    Figure 4: The number of people newly infected with COVID-19 has increased in the most recent weeks following a low point in June and appears to have now levelled off

    Estimated numbers of new infections with the coronavirus (COVID-19), England, based on tests conducted daily since 11 May 2020

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    Notes:

    1. All results are provisional and subject to revision.

    2. Credible intervals are large at both ends of the plot because there is less information available. At the end, although we know that individuals have been visited, there is a short delay in getting the associated swab results. The model does not include people when their next swab result is not known, so the sample size for the most recent days is smaller, resulting in wider credible intervals. At the start, there were fewer people in the study.

    3. This model does not control for household clustering, where multiple new cases derive from the same household.

    4. Weekly official reported estimates between 8 June and 5 July are based on average fortnightly weighted estimates reported each week and are plotted at the midpoint (Sunday) of each fortnightly period.

    5. Weekly official reported estimates from 6 July to 2 August are based on the midpoint (Thursday) modelled estimate of the given week.

    6. Weekly official reported estimates from 3 August onwards are based on the modelled estimate for the Monday of the given week.

    7. Initial unweighted estimates covering the full study period to date are not included.

    Data download

    For context, we also present the incidence rate in non-overlapping 14-day periods, which are available in the dataset that accompanies this bulletin.

    The incidence rates for households, which controls for any household clustering in new infections, follow a similar trend as for individuals. These are based on 14-day non-overlapping period estimates. The household incidence rates can be found in the dataset.

    The incidence rate measures the occurrence of new cases of COVID-19, and the calculation of this is defined in Section 11: Glossary. The incidence rate is not the same as the reproduction rate (R), which is the average number of secondary infections produced by one infected person.

    To calculate the estimated average number of people becoming newly infected per day, we multiply the daily incidence rate by the community population (see Coverage in Section 12: Measuring the data). We use the unrounded incidence rate to do this, so results will differ if calculated using the rounded estimates from the dataset.

    Notes for: Incidence rate in England

    1. This is based on model estimates from the Monday of the most recent week, Monday 3 August. This differs to previous publications where the week’s midpoint (Thursday) was used. The estimates of new infections have a higher level of uncertainty in the final week, where additional test results are still becoming available from the lab. Following further investigation, taking a point from the model earlier in the week is more representative of the final estimate after all data has been received from the lab and provides greater stability.
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    5. Antibody data for England

    As of 9 August 2020, 6.2% (95% confidence interval: 5.1% to 7.5%) of individuals aged 16 years and over tested positive for antibodies to the coronavirus (COVID-19) from any blood sample taken during the study. This equates to around 1 in 16 people. The estimate is weighted to be representative of the overall population, and suggests that around 2.8 million individuals (95% confidence interval: 2.3 million to 3.4 million) in England would test positive for antibodies if they were tested.1

    The analysis in this bulletin is based on test results from 5,248 individuals received since the start of the study on 26 April 2020. Of those who have provided blood samples, 265 tested positive for antibodies.

    One way the body fights infections like COVID-19 is by producing small particles in the blood called antibodies. It takes between two and three weeks for the body to make enough antibodies to fight the infection but once a person recovers, antibodies remain in the blood at low levels, although these levels can decline over time to the point that tests can no longer detect them. Having antibodies can help to prevent individuals from getting the same infection again, although other parts of the immune system can also protect people.

    We measure the presence of antibodies to understand who has had COVID-19 in the past, although the length of time antibodies remain at detectable levels in the blood is not fully known. It is also not yet known how having detectable antibodies, now or at some time in the past, affects the chance of getting COVID-19 again.

    More information on how our estimates compare with other studies can be found in Section 12: Measuring the data.

    Notes for: Antibody data for England

    1. Changes in the rate of people testing positive for antibodies between bulletins should not be interpreted as a trend over time. This is because it relates to a change in the number of individuals whose blood has now been tested for antibodies. As of the 9 July 2020 publication, antibody data have been weighted. Estimates in earlier bulletins were unweighted.
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    6. Regional analysis of antibody data for England

    We have been able to include regional analysis of antibody data for the first time. There is some evidence of differences in the percentage of people testing positive for antibodies by region. Statistical testing indicates that there is evidence to suggest that the percentage of people testing positive for antibodies to the coronavirus (COVID-19) is higher in London than in Yorkshire and The Humber, the East Midlands, the South East and the South West of England. There is currently no evidence of differences in the percentage of people testing positive for antibodies between other regions of England. This is also reflected in the confidence intervals surrounding estimates, which are generally wide.

    Recent findings from the REACT (REal Time Assessment of Community Transmission of Community Transmission) study, led by Imperial College London, show similar results. More information on REACT and other studies can be found in Other studies in Section 12: Measuring the data of this bulletin.

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    7. Number of people in Wales who had COVID-19

    Survey fieldwork in Wales began on 29 June 2020 and we now have enough data to produce modelled estimates. During the most recent week of the study1, we estimate that 1,500 people in Wales had the coronavirus (COVID-19) (95% credible interval: 400 to 3,500). This equates to 0.05% (95% credible interval: 0.01% to 0.11%) of the population in Wales or around 1 in 2,100 people (95% credible interval: 1 in 7,400 to 1 in 900). This is based on exploratory modelling of throat and nose swab results. In Wales, the sample size was 5,220 tests and there were fewer than three positive swab tests.

    The Welsh Government also publish results from this survey that describe COVID-19 infections in Wales in English and in Welsh.

    The survey has also begun in Northern Ireland and we will publish estimates for Northern Ireland when we have a sufficiently large sample. We are working with authorities to explore the possibility of expanding the survey to Scotland.

    Notes for: Number of people in Wales who had COVID-19

    1. This is based on model estimates from the week’s midpoint, Thursday 6 August.
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    8. Test sensitivity and specificity

    The estimates provided in Section 2: Number of people in England who had COVID-19 are for the percentage of the private-residential population testing positive for the coronavirus (COVID-19), otherwise known as the positivity rate. We do not report the prevalence rate. To calculate the prevalence rate, we would need an accurate understanding of the swab test's sensitivity (true-positive rate) and specificity (true-negative rate).

    While we do not know the true sensitivity and specificity of the test, as COVID-19 is a new virus, our data and related studies provide an indication of what these are likely to be. To understand the potential impact of false-positives and false-negatives, we have estimated what prevalence would be in two scenarios using different test sensitivity and the same specificity rates. The results of these scenarios show that when these estimated sensitivity and specificity rates are taken into account, the prevalence rate would be similar to the main estimate presented in Section 2: Number of people in England who had COVID-19.

    For this reason, we do not produce prevalence estimates for every analysis, but we will continue to monitor the impacts of sensitivity and specificity in future.

    You can find more information on sensitivity and specificity in a paper written by the Office for National Statistics' academic partners and in our methods article.

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    9. COVID-19 Infection Survey data

    COVID-19 Infection Survey
    Dataset | Released 14 August 2020
    Latest findings from the pilot phase of the Coronavirus (COVID-19) Infection Survey.

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    10. Collaboration

    University of Oxford logo
    University of Manchester logo
    Public Health England logo
    Wellcome Trust logo

    The Coronavirus (COVID-19) Infection Survey analysis was produced by the Office for National Statistics (ONS) in collaboration with our research partners at the University of Oxford, the University of Manchester, Public Health England (PHE) and Wellcome Trust. Of particular note are:

    • Sarah Walker – University of Oxford, Nuffield Department for Medicine: Professor of Medical Statistics and Epidemiology and Study Chief Investigator

    • Koen Pouwels – University of Oxford, Health Economics Research Centre, Nuffield Department of Population Health: Senior Researcher in Biostatistics and Health Economics

    • Thomas House – University of Manchester, Department of Mathematics: Reader in mathematical statistics

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    11. Glossary

    Community

    In this bulletin, we refer to the number of coronavirus (COVID-19) infections within the community. Community in this instance refers to private households, and it excludes those in hospitals, care homes or other institutional settings.

    Confidence interval

    A confidence interval gives an indication of the degree of uncertainty of an estimate, showing the precision of a sample estimate. The 95% confidence intervals are calculated so that if we repeated the study many times, 95% of the time the true unknown value would lie between the lower and upper confidence limits. A wider interval indicates more uncertainty in the estimate. For more information, see our methodology page on statistical uncertainty.

    Credible interval

    A credible interval gives an indication of the uncertainty of an estimate from data analysis. 95% credible intervals are calculated so that there is a 95% probability of the true value lying in the interval.

    False-positives and false-negatives

    A false-positive result occurs when the tests suggest an individual has COVID-19 when in fact they do not. By contrast, a false-negative result occurs when the tests suggest an individual does not have COVID-19 when in fact they do. For more information on false-positives and false-negatives, see our methods article.

    Incidence rate

    The incidence rate is an estimate of how often new cases of COVID-19 occur over a given period of time. In our study, it is calculated by dividing the number of times an individual has a positive test for the first time in the study, having first tested negative, by the total time everyone is in the study. We include the time people are in the study between successive negative tests for those who never have a positive test, and the time up to halfway between their last negative and first positive test for those that have a positive test. This reflects the fact that we do not actually know when a person first becomes positive, only when we tested them. Individuals who are positive when they join the study are not included in this calculation.

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    12. Measuring the data

    Data presented in this bulletin come from the Coronavirus (COVID-19) Infection Survey, which looks to identify the percentage of the population testing positive for COVID-19 and whether they have symptoms or not. The survey helps track the current extent of infection and transmission of COVID-19 among the population as a whole.

    This section of the bulletin provides a short summary of the study data and data collection methods. Our methodology article provides further information around the survey design, how we process data, and how data are analysed. The study protocol specifies the research for the study.

    Response rates

    The current number of households invited to participate in the survey in England is 85,915, of which 30,933 have enrolled. In responding households, there are 65,725 eligible individuals. Response rates for England are found in Table 4 of the reference tables that accompany this bulletin, and initial response rates for Wales are in Table 6. The response rates cannot be regarded as final response rates to the survey since those who are invited are not given a time limit in which to respond.

    Coverage

    Survey fieldwork for the pilot study began in England on 26 April 2020. Survey fieldwork in Wales began on 29 June and since 7 August, we have reported headline figures for Wales. The survey has also begun in Northern Ireland and we will publish estimates for Northern Ireland when we have a sufficiently large sample. We are working with authorities to explore the possibility of expanding the survey to Scotland.

    Only private residential households, otherwise known as the target population in this bulletin, are included in the sample. People in hospitals, care homes and other institutional settings are not included.

    The overall target population for England used in this study is 54,628,600. The overall target population for Wales used in the study is 3,057,800.

    Analysing the data

    All estimates presented in this bulletin are provisional results. As swabs are not necessarily analysed in date order by the laboratory, we have not yet received test results for all swabs taken on the dates included in this analysis. Estimates may therefore be revised as more test results are included.

    This is a pilot study where the analysis is developed at pace, and these quality enhancements may lead to minor changes in estimates, for example, the positive test counts across the study period.

    Other studies

    This study is one of a number of studies that look to provide information around the coronavirus pandemic within the UK.

    Department of Health and Social Care (DHSC) data, England

    Public Health England (PHE) present data on the total number of laboratory-confirmed cases in England, which capture the cumulative number of people in England who have tested positive for COVID-19. Equivalent data for Wales, Scotland and Northern Ireland are also available. These statistics present all known cases of COVID-19, both current and historical. The large sample size means it is possible to present known cases at local authority level.

    The NHS Test and Trace scheme was launched on 28 May. The Test and Trace service ensures that anyone who develops symptoms of COVID-19 can quickly be tested to find out if they have the virus. It includes targeted asymptomatic testing of NHS and social care staff and care home residents. Additionally, it helps trace close recent contacts of anyone who tests positive for COVID-19 and, if necessary, notify them that they must self-isolate.

    In comparison with PHE data and NHS Test and Trace data, the statistics presented in this bulletin take a representative sample of the community population (those in private residential households) in England, including people who are not otherwise prioritised for testing. This means that we can estimate the number of people in the community population in England with COVID-19 who do not report symptoms. This is something that is currently missing from PHE and Test and Trace data.

    COVID Symptom Study (ZOE app and King's College London), UK

    The COVID Symptom Study app allows users to log their health each day, including whether or not they have symptoms of COVID-19. The study aims to predict which combination of symptoms indicate that someone is likely to test positive for COVID-19. The app was developed by the health science company ZOE with data analysis conducted by King's College London. Anyone over the age of 18 years can download the app and take part in the study. Respondents can report symptoms of children.

    The study estimates the total number of people with symptomatic COVID-19 and the daily number of new cases of COVID-19 based on app data and swab tests taken in conjunction with the Department of Health and Social Care (DHSC). The study investigates the "predictive power of symptoms", and so the data do not capture people who are infected with COVID-19 but who do not display symptoms.

    Unlike the data presented in this bulletin, the COVID Symptom Study is not a representative sample of the population. It is reliant on app users and so captures only some cases in hospitals, care homes and other communities where few people use the app. To account for this, the model adjusts for age and deprivation when producing UK estimates. The larger sample size allows for detailed geographic breakdown.

    Real-time Assessment of Community Transmission-1 and -2 (REACT-1 and -2), England

    Like our study, the Real-time Assessment of Community Transmission-1 (REACT-1) survey involves taking swab samples to test for COVID-19 antigens to estimate the prevalence and transmission of the virus that causes COVID-19 in the community. The study currently involves around 120,000 participants aged five years and above, selected from a random cross-section sample of the general public from GP registration data, which allows for more detailed geographic breakdowns of infection rates than are currently possible within our study. Trends in infection by characteristics, such as age, sex, ethnicity, symptoms and key worker status, are also possible through the study. The REACT-2 study uses a finger prick test to generate data for antibody analysis.

    One of the main differences from our COVID-19 Infection Survey is that the REACT surveys do not require follow-up visits, as the study is interested primarily in prevalence at a given time point. Consequently, the incidence rate cannot be calculated from the REACT studies. It is also important to note that blood samples in the REACT-2 study are self-administered, rather than taken by a trained nurse, phlebotomist or healthcare assistant.

    Other antibody estimates

    PHE also publish an estimate of the prevalence of antibodies in the blood in England using blood samples from healthy adult blood donors. PHE provide estimates by region and currently do not scale up to England. Estimates in this bulletin and those published by PHE are based on different tests; PHE estimates are based on testing using the Euroimmun assay method, while blood samples in our survey are tested for antibodies by research staff at the University of Oxford using a novel ELISA. For more information about the antibody test used in this bulletin, see the COVID-19 Infection Survey protocol.

    In addition, the REACT (REal Time Assessment of Community Transmission) study, led by Imperial College London, use antibody finger-prick tests to track past infections and monitor the progress of the pandemic and have published their estimates. Estimates in this bulletin and the REACT study use different tests and different methods, for example the REACT estimates are based on self-administered and self-read finger prick tests, whereas tests in this survey are carried out by a trained nurse, phlebotomist or healthcare assistant.

    Next steps

    This edition of the bulletin presents headline analysis of the overall number of people infected with COVID-19, the regional positivity rate, incidence rate and antibodies. We provide headline figures once a week, to give regular, concise and high-quality information on COVID-19 within the community.

    Our recent release, Coronavirus infections in the community in England, offers more detailed analysis, which includes further exploration of the characteristics of those with COVID-19, such as age, sex, working location and occupation. We will also include further exploration of ethnicity when we have a large enough sample size to provide reliable analysis.

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    13. Strengths and limitations

    These statistics have been produced quickly in response to developing world events. The Office for Statistics Regulation, on behalf of the UK Statistics Authority, has reviewed them against several important aspects of the Code of Practice for Statistics and regards them as consistent with the Code's pillars of trustworthiness, quality and value.

    The estimates presented in this bulletin contain uncertainty. There are many sources of uncertainty, including uncertainty in the test, in the estimates and the quality of data collected in the questionnaire. Information on the main sources of uncertainty are presented in our methodology article.

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    Manylion cyswllt ar gyfer y Bwletin ystadegol

    Emily Connors and Eleanor Fordham
    infection.survey.analysis@ons.gov.uk
    Ffôn: +44 (0)203 973 4761