Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: 21 October 2021

Characteristics of people testing positive for COVID-19 from the Coronavirus (COVID-19) Infection Survey. This survey is being delivered in partnership with University of Oxford, University of Manchester, Public Health England and Wellcome Trust. This study is jointly led by the ONS and the Department for Health and Social Care (DHSC) working with the University of Oxford and Lighthouse Laboratory to collect and test samples. 

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Cyswllt:
Email Rhiannon Yapp and Eleanor Fordham

Dyddiad y datganiad:
21 October 2021

Cyhoeddiad nesaf:
3 November 2021

1. Main points

  • Those living in a household of three or more people, as well as those living in a multigenerational household were more likely to test positive for coronavirus (COVID-19) in the two weeks up to 3 October 2021.

  • People working in either the manufacturing or education industry sectors were more likely to test positive in comparison to those working in other sectors in the two weeks up to 3 October 2021; the higher likelihood for those working in education is likely related to the high infection levels among school aged children.

  • Across the UK, people testing positive for COVID-19 with a strong positive test continued to be more likely to report "classic" symptoms than gastrointestinal or loss of taste or smell only.

  • In the UK, the most commonly reported symptoms continued to be cough, fatigue and headache.

  • The number of socially distanced and physical contacts that adults and school-age children reported with people outside their household has continued to increase across the UK since March 2021, although school age children had fewer contacts during the school holidays.

About this bulletin

This fortnightly bulletin series presents the latest analysis on the characteristics of people testing positive for SARS-CoV-2, the coronavirus causing the COVID-19 disease in the UK. This is part of our series of analysis on the characteristics of people testing positive for COVID-19.

In this bulletin, we refer to the number of current COVID-19 infections within the population living in private residential households. We exclude those in hospitals, care homes and/or other communal establishments. In communal establishments, rates of COVID-19 infection are likely to be different.

We include current COVID-19 infections, which we define as testing positive for SARS-CoV-2, with or without having symptoms, on a swab taken from the nose and throat.

More about coronavirus

More information on our headline estimates of the overall number of positive cases in England, Wales, Northern Ireland and Scotland are available in our latest weekly bulletin. Our methodology article provides more information on the methods used for our models. In addition, our recent analysis shows that vaccination reduces the risk of testing positive.

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Analysis in this bulletin is for a different time period to the headline figures presented in the weekly COVID-19 Infection Survey bulletin. Reference periods are clearly stated at the start of each section, with more detail on what the analysis covers.

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2. Predictors of positivity, UK

This section examines the characteristics of people who are more likely to test positive for coronavirus (COVID-19) during the two weeks up to 3 October 2021. This analysis is an update of previous results presented in the Coronavirus (COVID-19) Infection Survey technical article: analysis of populations in the UK by risk of testing positive for COVID-19, September 2021, which provides a more detailed explanation of the methods used. An update of data published in the technical article can be found in tables 1a to 3b of the accompanying dataset.

The analysis in this section fits two statistical models to predict the likelihood of an individual testing positive for COVID-19 and can be used to identify subgroups where infections are persisting or arising. It is important to note that people can become infected even if they are fully vaccinated, so it is important to monitor infections by characteristics regularly regardless of whether someone has been vaccinated.

Our technical article also presented the effect of behavioural variables (such as wearing of facemasks and contact with others) on the likelihood of testing positive. We have not included the behavioural model this time, since we are reviewing the model to consider how groups with recent higher infection rates (school children) could affect the results since children’s behaviour is likely to be different from adults.

Those living in a household of three or more people as well as those living in a multigenerational household were more likely to test positive in the two weeks up to 3 October 2021

All analysis described in this section covers the two weeks to 3 October 2021. A longer time series covering 5 April to 3 October 2021 for the key demographic variables and all screening characteristics is available in the accompanying dataset. Estimates of the likelihood of some specific characteristics affecting an individual testing positive can fluctuate from one fortnight to another, meaning that findings which were significant in one period may not necessarily be significant in another period. This may be because the effect of a characteristic is genuinely changing or because we do not have sufficient individuals with that characteristic in a particular fortnight to exclude any differences we find being compatible to chance.

Children and teenagers, those living in a household of three or more people, and those living in a multigenerational household were all separately more likely to test positive for COVID-19. This is in comparison to those of older ages, those living in single person households, and those not living in a multigenerational household, respectively. The trends seen in age and household size have been consistent over previous weeks, whereas the trend for multigenerational households has fluctuated, with some fortnights showing no statistical evidence of a difference. Females were less likely to test positive than males although evidence of a significant difference has fluctuated over recent fortnights. The relationship between deprivation and positivity differs between people of white and non-white ethnicities. For white individuals, those who live in more deprived areas were more likely to test positive, while the opposite was true for non-white individuals. Those who live in less deprived areas were more likely to test positive. This is a new trend in the data which we will continue to monitor over the coming weeks.

Those who work in the manufacturing and education sectors were more likely to test positive in comparison to those working in other sectors

In this latest fortnight’s data, those who work in the manufacturing or education sectors were more likely to test positive in comparison to those working in other sectors. This is the first time we have seen statistical evidence of a difference in recent fortnights for the educational sector. In the previous fortnight, findings suggested people working in manufacturing were less likely to test positive, therefore this finding needs to be interpreted with caution until we have more data. Work sectors are self-reported and cover a wide variety of occupations; for example, someone working in the education sector could be a teacher at a primary school or could be a chef at a college.

Those who lived in a household where someone has had contact with a hospital or care home were less likely to test positive than those who did not. This trend has fluctuated, with some fortnights showing no statistical evidence of a difference. There was no statistical evidence that working in a patient-facing healthcare role affects the likelihood of testing positive, which has been a consistent finding over recent fortnights. Individuals who had travelled abroad in the last 28 days were less likely to test positive than those who had not travelled abroad in the last 28 days. This has been a consistent finding over recent fortnights and may be because a lot of those who travel abroad have, up until recently, been required to self-isolate and take multiple tests before and after flying. This means that those testing positive before a flight would not have travelled, which would potentially reduce the number of people testing positive who travelled abroad in the sample.

Individuals who regularly carry out lateral flow tests are more likely to test positive than those who do not, consistent with lateral flow tests being carried out by those who are otherwise at higher risk. As described below, we have changed our approach to modelling the use of lateral flow tests.

Figure 1: Characteristics of people more or less likely to test positive for COVID-19 in the two weeks ending 3 October 2021

Estimated likelihood of testing positive for coronavirus (COVID-19) on nose and throat swabs by screened characteristic, UK, 20 September to 3 October 2021

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Notes:
  1. The core demographic characteristics from model 1 are included as controls to make sure the analysis adjusts for these factors. We do not draw conclusions about the core demographic characteristics in this model.

  2. An odds ratio indicates the likelihood of an individual testing positive for COVID-19 given a particular characteristic/variable. When a characteristic/variable has an odds ratio of one, this means there is neither an increase nor a decrease in the likelihood of testing positive for COVID-19 compared with the reference category. An odds ratio greater than one indicates an increased likelihood of testing positive for COVID-19 compared with the reference category. An odds ratio less than one indicates a decreased likelihood of testing positive for COVID-19 compared with the reference category.

  3. Only characteristics that show a statistically significant difference to the reference category are included. Data for all variables included in the model can be found in the accompanying dataset.

  4. Odds ratios for those that have received 2 doses of Moderna vaccine more than 14 days ago suggest they are less likely to test positive than those that were not vaccinated, but are not included in the chart. Results can be found in the accompanying dataset.

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About this analysis

The models are fitted at the UK level and include all participants aged 2 years and over. Key demographic variables included in the main demographic model are: age, region, sex, ethnicity, deprivation, household size, multi-generational household, and urban/rural classification. Additional variables included in the subsequent models are included only if found to be significant in the two weeks presented in the bulletin. More information on the methods used in this analysis can be found in our technical article, analysis of populations in the UK by risk of testing positive for COVID-19, September 2021.

We continually review and update our methods and subsequent models. In the analysis presented in this bulletin, we have changed our approach to modelling the use of Lateral Flow Device (LFD) tests. The “use of lateral flow test” variable is now not included in Model 2 but is included in a separate model that contains all of the main demographic variables from Model 1 and significant variables from Model 2. This is because work sector is related to LFD use, and we want to estimate the effect of work sector independently of LFD use.

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3. Symptoms profile of strong positive cases, UK

This section presents analysis that considers individuals with any strong positive test (including repeated positive tests) that had high viral loads (a cycle threshold (Ct) value less than 30) between 1 December 2020 and 30 September 2021 in the UK. We first present analysis for the whole of the UK split by month, and then for the whole time period split by UK country.

The analysis looks at any specific self-reported symptom, including cough, fever, shortness of breath, loss of taste, loss of smell, myalgia, fatigue, sore throat, headache, abdominal pain, diarrhoea, nausea or vomiting, or any symptom compatible with coronavirus (COVID-19). Symptoms are self-reported and were not professionally diagnosed.

From July 2021 onwards, almost all strong positive cases (at least 99%) were compatible with the Delta variant. In June this was 92% and in May 46% of strong positive cases were compatible with the Delta variant. Prior to this, very few positive cases were identified as compatible with the Delta variant. This means that any change from May onwards when compared with previous months may be because the Delta variant has a different symptoms profile to the Alpha variant. However, other changes between May and June may also affect this analysis.

In addition, when the percentage of the population testing positive for COVID-19 is increasing, as it has been recently, the survey is likely to identify more people closer to the start of their infection with higher viral loads (lower Ct values). We have seen that the viral load of strong positive results increased during June and July 2021, as measured by decreases in the average Ct value (see Section 7: Glossary, for more information on Ct values). This will also affect the prevalence of symptoms within these strong positive cases.

Across the UK, people testing positive for COVID-19 with a strong positive test were more likely to report "classic" symptoms than gastrointestinal or loss of taste or smell only

This analysis is based on all individuals who test positive for COVID-19 with a strong positive test (Ct <30) and considers what percentage of these individuals reported symptoms within 35 days of the first positive test.

In September 2021, 62% (95% confidence interval: 60% to 64%) of people testing positive for COVID-19 in the UK with a strong positive test reported any specific symptoms1. In August, 59% (95% confidence interval: 57% to 61%) of people testing positive reported symptoms. There is no statistical evidence that the percentage of people reporting symptoms has changed between August and September 2021. The percentage of people reporting symptoms was lower in the period between March and May 2021. During this period, the positivity rate was also lower in comparison to other months, and there was a lower average viral load during this time. This could potentially explain the lower percentage of people reporting symptoms between March and May 2021.

Symptoms reported were more likely to be "classic" symptoms than gastrointestinal or loss of taste or smell only. The prevalence of “classic”, “loss of taste or smell” and any symptoms was generally lower between March and May 2021 compared with other months, where prevalence was higher. This is consistent with lower average viral load between March and May 2020.

Figure 2: In the UK, people testing positive for COVID-19 with a strong positive test continued to be more likely to report "classic" symptoms than gastrointestinal or loss of taste or smell only

Unweighted percentage of people with symptoms, including only those who have strong positive tests (Ct less than 30) by month, UK, 1 December 2020 to 30 September 2021

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Notes:
  1. All results are provisional and subject to revision.

  2. Symptoms are self-reported and were not professionally diagnosed.

  3. The data presented are unweighted percentages of people with any positive test result that had a Ct value less than 30.

  4. “Classic symptoms” include any of the following: cough, fever, loss of taste, loss of smell.

  5. “Gastrointestinal (GI) symptoms” include any of the following: abdominal pain, nausea or vomiting, diarrhoea.

  6. These statistics refer to infections reported in private households. These figures exclude infections reported in hospitals, care homes or other communal establishments.

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In the UK, the most commonly reported symptoms have consistently been cough, fatigue and headache. The least commonly reported symptoms have consistently been abdominal pain, diarrhoea and nausea or vomiting. The prevalence of loss of smell, loss of taste, fever, cough, fatigue, headache, myalgia, diarrhoea, and nausea and vomiting was lower in the period between March and May 2021 when positivity was lower in comparison to other months. However, confidence intervals are wide and overlap with previous months’ estimates.

Data on the percentage of people reporting specific symptoms by month for the UK, and by country for the total time period studied can be found in the accompanying dataset.

The percentage of strong positive cases where any symptoms were reported appears to be slightly lower in Northern Ireland, although confidence intervals overlap with other countries. This may be driven by slightly fewer people reporting loss of taste and smell (which is a classic symptom) compared with England, Wales and Scotland. In addition, our sampling method for Northern Ireland is different to the other nations, inviting only people who have previously participated in a Northern Ireland Statistics and Research Agency (NISRA) survey, which could result in a sample of individuals who are less likely to report symptoms.

Patterns of the prevalence of specific symptoms are similar for each UK country, and align with data for the whole of the UK.

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Because of a smaller number of tests in Wales, Northern Ireland and Scotland in comparison to England in our sample, the confidence intervals are wider indicating higher uncertainty.

Figure 3: Patterns of the prevalence of symptoms are similar for each UK country

Unweighted percentage of people with symptoms, including only those who have strong positive tests (Ct less than 30) by country, UK, 1 December 2020 to 30 September 2021

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Notes:
  1. All results are provisional and subject to revision.

  2. Symptoms are self-reported and were not professionally diagnosed.

  3. The data presented are unweighted percentages of people with any positive test result that had a Ct value less than 30.

  4. “Classic symptoms” include any of the following: cough, fever, loss of taste, loss of smell.

  5. “Gastrointestinal (GI) symptoms” include any of the following: abdominal pain, nausea or vomiting, diarrhoea.

  6. These statistics refer to infections reported in private households. These figures exclude infections reported in hospitals, care homes or other communal establishments.

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About this analysis

This analysis considers all symptoms reported at survey visits within 35 days of the first positive test of the episode, and at each survey visit we ask about symptoms in the last seven days. This includes symptoms reported even when there is a negative test result within this timeframe or a positive test result with a higher Ct value. The strength of the test is determined by how quickly the virus is detected, measured by a Ct value. The lower the Ct value, the higher the viral load and stronger the positive test. We look at strong positive test results with a Ct of less than 30 to exclude the possibility that symptoms are not identified because we pick up individuals very early or later on in their infection. More details on this analysis can be found in Section 8.

Individuals taking part in the survey were asked at each visit whether they had experienced a range of possible symptoms1 in the seven days before they were tested, and also separately whether they felt that they had symptoms compatible with a coronavirus (COVID-19) infection in the last seven days.

Notes for: Symptoms profile of strong positive cases, UK
  1. The symptoms respondents were asked to report are: fever, muscle ache (myalgia), fatigue (weakness or tiredness), sore throat, cough, shortness of breath, headache, nausea or vomiting, abdominal pain, diarrhoea, loss of taste or loss of smell.
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4. Number and age of people with whom individuals had contact

This section looks at how often individuals are reporting social contact (either socially distanced or physical contact) with other people outside their own household, regardless of whether they have tested positive for coronavirus (COVID-19). We asked school-age children (aged 2 years to School Year 11) and adults (School Year 12 and over) how many people aged 17 years and under, 18 to 69 years, and 70 years and over they have had contact with outside their household up to seven days prior to each survey visit. "Contact" refers to either of the following:

  • socially distanced contact

  • physical contact, such as a handshake or personal care, including while wearing personal protective equipment (PPE)

We report on recent trends in this section, but the full time series for this analysis, which covers the period between 11 July 2020 and 2 October 2021 for England, and 19 September 2020 to 2 October 2021 for Wales, Northern Ireland and Scotland, is available in the accompanying dataset. The analysis for Wales, Northern Ireland and Scotland starts at a later date because data collection started later in these countries. Our estimates have been weighted to be representative of the total population in each of the four UK countries.

Number of reported contacts with people outside the household continued to increase across the UK

The trends in socially distanced and physical contacts are very similar for England, Wales, Northern Ireland and Scotland, and are broadly unchanged since our last bulletin.

Across all four UK nations, the number of socially distanced and physical contacts that adults and school-age children reported with people of all ages outside their household has been increasing since March 2021, although school age children had fewer contacts during the school holidays. Adults appear to consistently have more socially distanced and physical contacts with those aged 18 to 69 years than with those aged under 18 years or aged 70 years and over. School-age children appear to have had more socially distanced and physical contacts with those aged under 18 years.

School term dates, and COVID-19 related school policies vary by nation and this is reflected in the data. For example, in the 14-day period up to 3 September 2021, there was an increase in school age children reporting contact with those aged under 18 years in Northern Ireland and Scotland. A similar increase was seen in England and Wales in the 14-day period up to 2 October 2021. The differing times of these increases correspond to schools reopening at different times after the summer holidays in Northern Ireland and Scotland compared with England and Wales.

Further information on the schedule for school re-openings can be viewed for England, Wales, Northern Ireland and Scotland. Information on lockdown easing can be viewed for England, Wales, Northern Ireland and Scotland.

Our findings are generally similar to those reported in the Opinions and Lifestyle Survey (OPN), which examines the impact of the coronavirus pandemic on people, households and communities in Great Britain. The most recent OPN bulletin reported that among 3,400 adult respondents in Great Britain, from 22 September to 3 October 2021:

  • a smaller proportion of adults (40%) reported that they always or often maintained social distancing when outside their home compared with 45% in the previous period, a figure which has steadily decreased since the start of May 2021

  • just over half of adults (55%) reported that they avoided physical contact with others outside their home in the past seven days, a reduction of 4 percentage points from the previous period (59%)

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5. Characteristics of people testing positive for COVID-19 data

Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK
Dataset | Released 21 October 2021
Characteristics of people testing positive for coronavirus (COVID-19) taken from the COVID-19 Infection Survey.

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6. Collaboration

The logos of the University of Oxford, the University of Manchester, Public Health England (PHE) and the Wellcome Trust

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

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

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

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

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7. Glossary

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. Overlapping confidence intervals indicate that there may not be a true difference between two estimates.

Cycle threshold (Ct) values

The strength of a positive coronavirus (COVID-19) test is determined by how quickly the virus is detected, measured by a cycle threshold (Ct) value. The lower the Ct value, the higher the viral load and stronger the positive test. Positive results with a high Ct value can be seen in the early stages of infection when virus levels are rising, or late in the infection, when the risk of transmission is low.

Odds ratio

An odds ratio indicates the likelihood of an individual testing positive for COVID-19 given a particular characteristic or variable. When a characteristic or variable has an odds ratio of one, this means there is neither an increase nor a decrease in the likelihood of testing positive for COVID-19 compared with the reference category. An odds ratio greater than one indicates an increased likelihood of testing positive for COVID-19 compared with the reference category. An odds ratio less than one indicates a decreased likelihood of testing positive for COVID-19 compared with the reference category.

Deprivation

Deprivation is based on an index of multiple deprivation (IMD) score or equivalent scoring method for the devolved administrations, from 1, which represents most deprived, up to 10, which represents least deprived. The odds ratio/coefficient shows how a one unit increase in deprivation score, which is equivalent to 10 percentiles, affects the likelihood of testing positive for COVID-19.

Multigenerational household

A household was classed as multigenerational if it included individual(s) aged school Year 11 or younger and individual(s) aged school Year 12 to age 49 years and individual(s) aged 50 years or over.

For more information, see our methodology page on statistical uncertainty.

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8. Measuring the data

Additional information on strengths, limitations, appropriate uses, and how the data were created is available in the Coronavirus (COVID-19) Infection Survey Quality Methodology Information (QMI). Our methodology article provides further information around the survey design, how we process data and how data are analysed.

Symptoms analysis

The analysis in Section 2 looks at each person who tested positive for coronavirus (COVID-19) and had a strong positive test in the UK. Participants who only have positive tests with high Cycle threshold (Ct) values (see glossary)) are excluded from this analysis to exclude the possibility that symptoms are not identified because we pick up individuals either very early or later on in their infection. You can find more information on Ct values in a paper written by academic partners at the University of Oxford.

The analysis on the symptoms profile of strong positive cases in the UK considers individuals with any positive test (including repeated positive tests) that had a Ct value less than 30 between 1 December 2020 and 30 September 2021. Positive episodes are now being defined as "a new positive test 120 days or more after an initial first positive test and following a previous negative test, or, if within 120 days, a subsequent positive test following four consecutive negative tests". We now take 120 days as a cut-off point, whereas previously we used 90 days.

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9. Strengths and limitations

More information on strengths and limitations is available in the Coronavirus (COVID-19) Infection Survey statistical bulletin.

Further information on test accuracy can be found in our blog Accuracy and confidence: why we trust the data from the COVID-19 infection survey.

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Manylion cyswllt ar gyfer y Bwletin ystadegol

Rhiannon Yapp and Eleanor Fordham
infection.survey.analysis@ons.gov.uk
Ffôn: +44 1633 560499