Coronavirus (COVID-19) Infection Survey pilot: England and Wales, 18 September 2020

• An estimated 59,800 people (95% credible interval: 46,900 to 75,200) within the community population in England had the coronavirus (COVID-19) during the most recent week, from 4 to 10 September 2020, equating to around 1 in 900 people (95% credible interval: 1 in 1,200 to 1 in 700).

• The estimate shows the number of infections has increased in recent weeks.

• In recent weeks, there has been clear evidence of an increase in the number of people testing positive for COVID-19 aged 2 to 11 years, 17 to 24 years and 25 to 34 years.

• There is evidence of higher infection rates in the North West and London.

• During the most recent week (4 to 10 September 2020), we estimate there were around 1.10 (95% credible interval: 0.77 to 1.51) new COVID-19 infections for every 10,000 people per day in the community population in England, equating to around 6,000 new cases per day (95% credible interval: 4,200 to 8,300).

• The estimates show that the incidence rate for England has increased in recent weeks.

• During the most recent week (4 to 10 September 2020), we estimate that 1,500 people in Wales had COVID-19 (95% credible interval: 400 to 3,900), which is around 1 in 2,000 people (95% credible interval: 1 in 8,200 to 1 in 800).

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

During the most recent week of the study, we estimate that 59,800 people in England had the coronavirus (COVID-19) (95% credible interval: 46,900 to 75,200).¹ This equates to 0.11% (95% credible interval: 0.09% to 0.14%) of the population in England or around 1 in 900 people (95% credible interval: 1 in 1,200 to 1 in 700). This is based on statistical modelling of the trend in rates of positive nose and throat swab results.

Estimates of infection rates over time are presented in Figure 1. While the percentage of people testing positive for COVID-19 has decreased since the start of the study (26 April 2020), the most recent modelled estimate shows the number of infections has increased in recent weeks.

The modelled estimates for the latest six-week period are based on 208,730 swab tests collected over this period. During these weeks, 136 people from 118 households tested positive.

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: The most recent modelled estimate shows the number of infections in England has increased in recent weeks

Estimated percentage of the population in England testing positive for the coronavirus (COVID-19) on nose and throat swabs since 26 April 2020

Notes:

1. These results are provisional and subject to revision.

2. The break distinguishes between the latest six-week estimates and the earlier period. The earlier estimates will be updated periodically. 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. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

5. Modelled estimates include all swab results that are available at the time the official estimates are produced. Additional swab tests that become available after this are included in subsequent models, meaning that modelled estimates can change slightly as additional data is included.

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The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 2 and 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 most recent estimate shows the number of infections has increased in recent weeks. The 14-day time periods presented in Figure 2 overlap with those presented in the data tables in our previous publication, so direct comparisons are not possible.

The percentage testing positive in the latest 14-day period (28 August to 10 September 2020) was 0.13% (95% confidence interval: 0.10% to 0.17%).

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

We are continuously refining and looking to improve our modelling and presentations. We would welcome any feedback via email: infection.survey.analysis@ons.gov.uk.

For information about the potential impact of false-positive and false-negative test results, see our methods article. We estimate that when different test sensitivity and specificity rates are taken into account, the number of people testing positive for COVID-19 would be fairly similar to the main estimate presented in this section.

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

1. This is based on model estimates from the reference point of the most recent week (4 to 10 September 2020), Monday 7 September 2020. More information on reference dates can be found in Section 11: Measuring the data.

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 (4 to 10 September 2020), there is evidence of variation in COVID-19 infection rates across the regions of England with higher rates of infection in the North West and London. This is based on statistical modelling of nose and throat swab test results.

Looking at trends over time, from this survey there is evidence that the COVID-19 infection rates have increased in most regions, particularly the North West and London. It is likely that infection rates in all other regions have also increased except the South West and West Midlands. 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 lower number of positive tests within each region, compared with England as a whole.

Figure 4: There is evidence that infection rates have increased in most regions, particularly the North West and London in recent weeks

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by region since 31 July 2020, England

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 and/or other institutional settings.

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In recent weeks, there has been clear evidence of an increase in the number of people testing positive for the coronavirus (COVID-19) aged 2 to 11 years, 17 to 24 years and 25 to 34 years. Smaller increases are also evident in those aged 35 to 49 years and 50 to 69 years. Based on the latest data, for those aged 12 to 16 years we cannot determine with certainty the change in trend over time. This is based on statistical modelling of nose and throat swab test results.

In the data used to produce these estimates, the number of people sampled in some age groups who tested positive for COVID-19 is lower relative to England overall. This means there is a higher degree of uncertainty in estimates for some age groups over this period, as indicated by larger credible intervals.

Figure 5: COVID-19 infection rates have increased most in younger age groups

Estimated percentage of the population testing positive for the coronavirus (COVID-19) on nose and throat swabs, daily, by age group since 23 July 2020, England

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 and/or other institutional settings.

3. The modelled estimates are presented at the reference value for a region which is the East Midlands. This does not affect the overall trend over time, but estimated probabilities for other regions would vary in level.

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Based on statistical modelling, we estimate that during the most recent week of the study (4 to 10 September 2020), there were 1.10 new infections per 10,000 people per day (95% credible interval: 0.77 to 1.51).¹ This equates to 6,000 new infections per day (95% credible interval: 4,200 to 8,300).

The official estimate shows that the incidence rate for England has increased in recent weeks.

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.

We are continually refining the way we estimate incidence and continue to present the absolute numbers for transparency in the dataset that accompanies this bulletin. As it takes time to process the swab tests, the amount of information available at the end of the time period decreases relative to the number of tests available in earlier periods. The increased uncertainty at the end of the time period is indicated by wider credible intervals.

Figure 6: The incidence rate for England has increased in recent weeks

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

Notes:

1. All results are provisional and subject to revision.

2. The break distinguishes between the latest six-week estimates and the earlier period. The earlier estimates will be updated periodically. Using data from only the most recent six weeks in the model enables us to continue to provide timely results.

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

4. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

5. Modelled estimates include additional swab test results not available when the official reported estimates were produced.

6. Initial unweighted estimates covering the full study period to date are not included in the official reported estimates chart.

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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 control for any household clustering in new infections, follow a similar trend as for people. 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 the coronavirus (COVID-19), and the calculation of this is defined in Section 10: 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 11: 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 reference point of the most recent week (4 to 10 September 2020), Friday 4 September 2020. More information on reference dates can be found in Section 11: Measuring the data.

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 3,900). This equates to 0.05% (95% credible interval: 0.01% to 0.13%) of the population in Wales or around 1 in 2,000 people (95% credible interval: 1 in 8,200 to 1 in 800). Our modelling suggests that the number of COVID-19 cases in Wales is currently relatively stable. This is based on exploratory modelling of throat and nose swab results.

Because of a relatively small number of tests and a low number of positives in our sample, credible intervals are wide and therefore results should be interpreted with caution.

In Wales, the modelled estimates for the latest six-week period are based on 8,517 swab tests collected over this period. During these weeks, there were fewer than three positive swab tests.

Figure 7: The most recent modelled estimate suggests the number of infections in Wales has remained relatively stable in recent weeks

Estimated percentage of the population in Wales testing positive for the coronavirus (COVID-19) on nose and throat swabs since 31 July 2020

Notes:

1. These results are provisional and subject to revision.

2. 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.

3. Official reported estimates are plotted at a reference point believed to be most representative of the given week. Details of which day was used for each week can be found in the dataset that accompanies this bulletin.

4. Modelled estimates include all swab results that are available at the time the official estimates are produced. Additional swab tests that become available after this are included in subsequent models, meaning that modelled estimates can change slightly as additional data is included.

Download this chart

.XLSX

The estimates for non-overlapping 14-day periods (which underpin our modelled official estimates) are presented in Figure 8 and 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 7: that the most recent estimate suggests the number of infections in Wales has remained relatively stable in recent weeks.

The percentage testing positive in Wales in the latest 14-day period (28 August to 10 September 2020) was 0.04% (95% confidence interval: 0.00% to 0.23%).

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

1. This is based on model estimates from the reference point of the most recent week (4 to 10 September 2020), Monday 7 September 2020. More information on reference dates can be found in Section 11: Measuring the data.

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 the 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 fairly 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' (ONS') academic partners and in our methods article.

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

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 a person has COVID-19 when in fact they do not. By contrast, a false-negative result occurs when the tests suggest a person 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 a person 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 (or maximum of seven days, whichever is later) 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. People who are positive when they join the study are not included in this calculation.

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.

Reference dates

We aim to provide the estimates of positivity rate and incidence that are most timely and most representative of each week. We decide the most recent week we can report on based on the availability of test results for visits that have already happened, accounting for the fact that swabs have to be couriered to the labs, tested and results returned. On most occasions the reference data align perfectly but sometimes this is not feasible. This week, the reference week falls between 4 to 10 September 2020.

Within the most recent week, we provide an official estimate for positivity rate and incidence based on a reference point from the modelled trends. For positivity rates, we can include all swab test results, even from the most recent visits. Therefore, although we are still expecting further swab test results from the labs, there are sufficient data for the official estimate for positivity to be based on a reference point after the start of the reference week. To improve stability in our modelling while maintaining relative timeliness of our estimates we are reporting our official estimates based on the midpoint of the reference week. This week, the reference day for positivity rates is Monday 7 September 2020.

The calculation of incidence uses time between two tests; so, for example, a participant who was last seen two weeks ago and is not due their next visit for another two weeks only contributes to the model up to two weeks ago. Our official estimates of incidence are therefore based on the first day of the reference week. This week, the reference day for incidence was Friday 4 September 2020. The model includes all information up to 10 September (the end of the reference week), and people who tested negative on a test between 10 and 12 September are included as negative up to 10 September.

Response rates

At the start of the pilot study we invited 20,276 households in England to take part, of which 10,330 have enrolled as of 10 September. In responding households, there are 22,300 eligible people. The likelihood of enrolment decreases over time and response rate information for those initially asked to take part at the start of the survey can be considered as relatively final.

We expanded our sampling at the end of May and again at the end of July. The number of households invited to participate in the survey in this expansion in England, as of 10 September, was 543,812, of which 69,402 have enrolled. In responding households, there are 153,245 eligible people. We are significantly expanding the infection survey to 400,000 people in England, making it the UK's largest study tracking COVID-19 in the general population. 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.

The number of households invited to participate in the survey in Wales, as of 10 September, was 6,665, of which 1,981 have enrolled. In responding households, there are 4,189 eligible people.

Response rates for England are found in Table 4 of the dataset that accompanies this bulletin. Initial response rates for Wales are in Table 6. We provide response rates separately for the different sampling phases of the study.

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 set up the survey in 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 3,059,461.

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.

We are giving increasing prominence to the weighted estimates to ensure we are giving appropriate visibility to all available indicators.

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, UK

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.

Each nation of the UK has a testing and tracing system. These ensure that anyone who develops symptoms of COVID-19 can quickly be tested to find out if they have the virus. Some nations also include 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), including people who are not otherwise prioritised for testing. This means that we can estimate the number of people in the community population with COVID-19 who do not report any evidence of symptoms.

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 study, led by Imperial College London, uses antibody finger-prick tests to track past infections and monitor the progress of the pandemic, and the estimates have been published. 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 and the incidence rate. 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 (COVID-19) Infection Survey: characteristics of people testing positive for COVID-19 in England, August 2020, offers more detailed analysis, including further exploration of the characteristics of those with COVID-19, such as age, sex, ethnicity, working location and occupation.

We are significantly expanding the infection survey to 400,000 people in England, making it the UK's largest study tracking COVID-19 in the general population. We have begun this expansion by increasing the sample size in local authorities of interest in the North West, Yorkshire and The Humber, and London. For more information, please see the Office for National Statistics (ONS) expansion press notice, released on 18 August 2020.

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 in the quality of data collected in the questionnaire. Information on the main sources of uncertainty are presented in our methodology article.