Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: 11 May 2022

• Those who reported being vaccinated recently were generally less likely to test positive for coronavirus (COVID-19) than those who reported not being vaccinated, in the fortnight up to 23 April 2022.

• People previously infected with COVID-19 continued to be less likely to test positive than those who had not experienced a prior infection, in the fortnight up to 23 April 2022.

• People who reported that they had travelled abroad in the last 28 days continued to be more likely to test positive for COVID-19 than those who had not, in the fortnight up to 23 April 2022.

• The risk of COVID-19 re-infection continued to be approximately 10 times higher in the period when the Omicron variants were most common (20 December 2021 to 25 April 2022), compared with when the Delta variant was most common (17 May to 19 December 2021).

• People who were unvaccinated continued to be more likely to be re-infected with COVID-19 than people who had been vaccinated, from 2 July 2020 to 25 April 2022.

• The percentage of people testing positive for COVID-19 who reported loss of taste or smell remained at lower levels in April 2022, after decreasing sharply between December 2021 and January 2022 (during the time when the Omicron variants became most common).

About this bulletin

In this bulletin, we present the latest analysis of the characteristics associated with testing positive for SARS-CoV-2, the coronavirus causing the COVID-19 disease in the UK. We also present analysis on re-infections, risk factors associated with re-infection, symptoms reported by strong positive cases, and on socially distanced and physical contacts with others. 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 COVID-19 infections within the population living in private residential households. We exclude those in hospitals, care homes and/or other communal establishments.

We include 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 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.

This analysis was first presented in our Analysis of populations in the UK by risk of testing positive for coronavirus (COVID-19) September 2021 publication, which provides a more detailed explanation of the methods used. We present findings for the most recent fortnight in this section, but a longer data time series covering 7 November 2021 to 23 April 2022 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 that are statistically significant in one period may not necessarily be statistically 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 down to chance.

Our latest data for the fortnight ending 23 April 2022 show similar conclusions to our last publication, specifically that:

• people who received a fourth vaccine 15 to 90 days ago, a third vaccine 15 to 90 days ago, a first vaccine 91 to 180 days ago, or any vaccine up to 14 days ago, were less likely to test positive than those who reported not being vaccinated

• people who had previously been infected [note 1] with COVID-19 continued to be less likely to test positive than those who had not been previously infected

• people who were previously infected with COVID-19 during the period when the Delta variant was most common (May to December 2021) continued to be the least likely to test positive in comparison with those infected prior to this period

• females continued to be less likely to test positive than males

• people from ethnic minority groups continued to be less likely to test positive than those reporting White ethnicity

• people who had contact with hospitals, or live with someone who had contact, were less likely to test positive compared with those living in households where no one had contact with hospitals

• people living in multiple occupancy households were more likely to test positive than those living alone

• people who lived in less deprived areas were more likely to test positive than those who lived in more deprived areas

• people who reported that they travelled abroad in the last 28 days continued to be more likely to test positive than those who had not

• people who reported regularly using lateral flow tests continued to be more likely to test positive compared with those who did not; this is likely related to those at a higher risk of infection being encouraged to take regular lateral flow tests

In the same fortnight:

• Adults living with a child aged 16 years or under were less likely to test positive than those who did not live with a child

Figure 1: People previously infected with COVID-19 and those vaccinated more recently were generally less likely to test positive in the fortnight ending 23 April 2022

Estimated likelihood of testing positive for coronavirus on nose and throat swabs by vaccination status and previous infection, UK, 10 to 23 April 2022

Notes:

1. The core demographic variables, sex, ethnicity, age, geographical region, urban or rural classification of address, deprivation percentile, household size, and whether the household was multigenerational, are included to adjust for these factors when comparing characteristics. When we report on the effect of these core demographic variables only, they are from a separate model that includes only them.

2. An odds ratio indicates the likelihood of an individual testing positive for COVID-19 given a particular characteristic or variable. See Glossary for full definition.

3. Figures 1 and 2 present results from the same model. We have presented the results separately to make the graphs more accessible.

4. The "pre-Alpha variant period" is defined as before 16 November 2020, the "Alpha variant period" is defined as 16 November 2020 to 16 May 2021, and the "Delta variant period" is defined as from 17 May to 19 December 2021.

5. When identifying previous infection, we use all previous positive COVID-19 swab tests, either from the COVID-19 Infection Survey, Test and Trace data in England, or a self-reported positive swab test, to classify an infection as a previous infection if it occurred 120 days or more previously with a prior negative test from the survey, or after four consecutive negative survey test results. Therefore, the sample size of previous infections in the Omicron variants period (20 December 2021 onwards) is currently too low to include in this analysis. We will include data once we have a sufficient sample size. This definition differs from the one currently used in our re-infections analysis in Sections 3 and 4. We are keeping this definition under review.

6. The effect of 'Any number of vaccines, 21 days or less before the last vaccine' is not included in this figure, but is presented in Table 2a of the accompanying dataset. This is because people testing positive before a planned vaccination are advised to postpone their vaccination.

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Figure 2: People who reported travelling abroad in the last 28 days continued to be more likely to test positive for COVID-19 in the fortnight ending 23 April 2022

Estimated likelihood of testing positive for coronavirus on nose and throat swabs by selected characteristics, UK, 10 to 23 April 2022

Notes:

1. The core demographic variables, sex, ethnicity, age, geographical region, urban or rural classification of address, deprivation percentile, household size, and whether the household was multigenerational are included to adjust for these factors when comparing characteristics. When we report on the effect of these core demographic variables only, they are from a separate model that includes only them.
2. An odds ratio indicates the likelihood of an individual testing positive for COVID-19 given a particular characteristic or variable. See Glossary for full definition.
3. Figures 1 and 2 present results from the same model. We have presented the results separately to make the graphs more accessible.

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An additional model examines the effect of behavioural characteristics on the likelihood of testing positive, while controlling for the core demographic variables and significant other characteristics shown earlier in this section. This means that we can identify which behavioural characteristics are associated with testing positive while taking other differences between people reporting different behaviours into account. Results from this behavioural model can be found in Table 4a of the accompanying dataset.

Our findings suggest that in the fortnight ending 23 April 2022:

• people who reported having one to five physical contacts with those aged under 18 years were more likely to test positive than people who had no physical contact with those aged under 18 years

• people who reported having any physical contact with those aged 70 years and over were more likely to test positive than people who had no physical contact with those aged 70 years and over

• people who reported spending more time socialising outside their home continued to be more likely to test positive

• people who reported others spending more time in their home were more likely to test positive

We analyse the effect of socially distanced and physical contacts separately. This means that people who reported having no physical contact, which is the reference group for the physical contact analysis, may have reported having socially distanced contact over the same time period.

Notes for: Characteristics associated with testing positive, UK

1. We use all previous positive COVID-19 swab tests, either from the COVID-19 infection survey or from Test and Trace data, or a self-reported positive swab test, to classify an infection as a previous infection if it occurred 120 days or more previously with a prior negative test from the survey, or after four consecutive negative survey test results. Therefore, the sample size of previous infections in the Omicron variants period (20 December 2021 onwards) is currently too low to include in this analysis. We will include data once we have a sufficient sample size.

This section looks at the rate of coronavirus (COVID-19) re-infections in the UK, from 2 July 2020 to 25 April 2022.

The technical article on re-infections provides a more detailed explanation of the methods used, some of which have since been updated. Tables 5a to 5d in the accompanying dataset for this bulletin contain our re-infections data.

A re-infection was identified in this analysis if any one of the following three conditions were met:

Time since previous infection and number of negative tests, either:

• a positive test 120 or more days after an initial first positive test and following one or more negative tests
• a positive test 90 or more days after an initial first positive test and following two or more negative tests, or, for positive tests on or after 20 December 2021 when Omicron became the main variant, following one or more negative tests
• a positive test 60 or more days after an initial first positive test and following three or more negative tests
• a positive test after an initial first positive test and following four or more negative tests

High viral load:

Where both the first positive test and subsequent positive test have a high viral load, or there has been an increase in viral load between first positive test and subsequent positive tests.

Evidence of different variant types:

Where there is evidence, based on either genetic sequencing data or gene positivity from the polymerase chain reaction (PCR) swab test that the variant differs between positive tests.

This analysis includes individuals who have had at least one positive test recorded in the survey and meet our criteria for being "at risk" of re-infection. An individual is classified as "at risk" if it is possible for a test of theirs to be considered a re-infection if it turns out to be positive. The "at-risk period" refers to the period following the first time we could have defined a re-infection based on the three conditions described. A re-infection is therefore only identified when an "at risk" individual has a positive test.

We have recently updated our definition of a re-infection used in this analysis. This means it now differs from the definition we use for previous infections in analysis of the characteristics associated with testing positive. In addition, this analysis only includes COVID-19 Infection Survey test results, in contrast to the definition we use for previous infections in the characteristics associated with testing positive analysis, which uses data from other sources.

There has been a large increase in the rates for re-infections since the Omicron variants became most common

There has been a large increase in the rates for all re-infections and re-infections with a high viral load since the Omicron variants became most common (20 December 2021 onwards). Viral load is approximated by Cycle threshold (Ct) values, which are lower with a high viral load. Participant days at risk and Ct values are further defined in our Glossary.

This section presents analysis of the risk factors associated with a coronavirus (COVID-19) re-infection identified among participants across the UK who had previously tested positive in the survey. This analysis included 43,522 participants "at risk" of re-infection and 5,086 re-infections identified between 2 July 2020 and 25 April 2022.

Our re-infections technical article outlines the model used to investigate how the rate of re-infection varies over time and between individuals. This model explores multiple factors including:

• age
• sex
• ethnicity
• Cycle threshold (Ct) value observed in the initial infection
• deprivation
• household size
• working in patient-facing healthcare
• long-term health conditions
• vaccination status
• the period during which an individual was at risk

We define the Alpha variant period as prior to 17 May 2021, the Delta variant period as 17 May to 19 December 2021, and the Omicron variants period as 20 December 2021 onwards.

The risk of re-infection continued to be approximately 10 times higher in the period when the Omicron variants were most common

The risk of re-infection by characteristic is measured in terms of hazard ratios and presented in Figure 4. In addition to the variables presented in Figure 4, we also looked at the risk of re-infection during the periods when different variants became most common and the effect of age and of Ct values. A Ct value is a proxy for the quantity of virus (also known as viral load), where a lower Ct value indicates higher viral load.

• Compared with the period when the Delta variant was most common, the risk of re-infection continued to be approximately 10 times higher in the period when the Omicron variants were most common (95% confidence interval: 7 to 12 times higher).
• People who were unvaccinated continued to be more likely to be re-infected than people who had been vaccinated.
• People who reported symptoms within 35 days of the first positive test in their first infection continued to be less likely to be re-infected than those who did not. People continued to be more likely to be re-infected if they had a lower viral load (higher Ct value) in their first infection; both of these findings may be because of a weaker immune response in "milder" primary infections.
• Older people continued to be less likely to be re-infected.
• People who live in less deprived areas continued to be less likely to be re-infected than people living in more deprived areas.

Hazard ratios for all characteristics included in the model, including for age and for Ct values separately, can be found in Tables 6a to 6c in the accompanying dataset. Estimated rates of re-infection over time can be found in Table 6d in the accompanying dataset.

Figure 3: People who were unvaccinated were more likely to be re-infected with COVID-19 compared with people who had been vaccinated

Re-infection hazard ratios for characteristics included in the model, UK, 2 July 2020 to 25 April 2022

Notes:

1. A hazard ratio of greater than 1 indicates more risk in the specified group compared with the reference group, and a hazard ratio of less than 1 indicates less risk.
2. The hazard ratio for deprivation shows how a 10 unit increase in deprivation score, where 1 represents most deprived and 100 represents least deprived, affects the likelihood of testing positive for COVID-19.
3. Although included in the model, the effect of periods in which different variants were most common, and the effect of age and of Ct values, are not included in this figure but are presented in Tables 6a to 6c of the accompanying dataset, respectively. The effect of calendar periods is not included in this figure because of the much larger scale of the effect of the period when the Omicron variants were most common in comparison with other findings.

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This section presents analysis based on people who tested positive for coronavirus (COVID-19) with a strong positive test (Cycle threshold (Ct) value less than 30). It considers what percentage of these people reported individual and groups of symptoms [note 1] within 35 days of the first positive test in each infection episode. We present this analysis for the whole of the UK split by month, which covers 1 December 2020 to 24 April 2022, and for the period from 1 February to 24 April 2022 split by UK country. All of our symptoms analysis can be found in Tables 8a to 8f in the accompanying dataset.

The average viral load of the people testing positive for COVID-19 also affects whether they are likely to report symptoms. We have seen that the viral load of strong positive results increased during January 2022, as measured by decreases in the average Ct value (see Glossary, for more information on Ct values). This will also affect the prevalence of symptoms within these strong positive cases.

People testing positive who reported loss of taste or smell remained at low levels in April 2022

In April 2022, 67% (95% confidence interval: 66% to 68%) of people testing positive for COVID-19 in the UK with a strong positive test reported any specific symptoms [note 1] or any other self-reported symptoms compatible with COVID-19. This was a small decrease from March 2022.

The percentage of people testing positive who reported "classic" symptoms remained at similar levels in March and April 2022. The percentage of people testing positive who reported loss of taste or smell decreased sharply between December 2021 and January 2022 and remained at a lower level in April 2022. This decrease coincided with increasing infections with the Omicron variants of COVID-19. The percentage of people testing positive who reported gastrointestinal symptoms decreased slightly in December 2021 and has remained unchanged since then.

The percentages of people testing positive who reported each group of symptoms are similar for each country between 1 February and 24 April 2022.

Figure 4: The percentage of people testing positive for COVID-19 who reported loss of taste or smell remained at low levels in April 2022

Unweighted percentage of people testing positive for coronavirus with symptoms, including only those who have strong positive tests (cycle threshold (Ct) value less than 30) by month, UK, 1 December 2020 to 24 April 2022

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.

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The percentage of people with a strong positive test who reported a sore throat, cough or fatigue increased in the first few months of 2022, and remained at a high level in April 2022. However, these are symptoms that can occur with a number of other infections circulating at the same time, such as the common cold or flu. The percentage of people with a strong positive test who reported loss of taste or smell decreased sharply in December 2021, when the Omicron variants of COVID-19 became most common.​

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

We report on recent trends in this section, but the full data time series for this analysis, which covers the period between 19 July 2020 and 23 April 2022 for England, and 27 September 2020 to 23 April 2022 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.

Across all four UK countries, the number of contacts adults reported with other adults has increased since January 2022

The number of socially distanced and physical contacts adults reported with other adults has increased since January 2022 in all four UK countries. Trends in the contacts of children vary over time and are likely to be primarily driven by the timing of school holidays.

​Our findings are generally similar to findings on socially distanced and physical contact 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 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, UK Health Security Agency 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
• Anna Seale - University of Warwick, Warwick Medical School: Professor of Public Health; UK Health Security Agency, Data, Analytics and Surveillance: Scientific Advisor

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.

Deprivation

Deprivation is based on an index of multiple deprivation (IMD) (PDF, 2.18MB) score or equivalent scoring method for the devolved administrations, from 1, which represents most deprived up to 100, which represents least deprived. The hazard or odds ratio shows how a 10-unit increase in deprivation score, which is equivalent to 10 percentiles or 1 decile, 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 those aged 49 years and individual(s) aged 50 years and over.

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.

Hazard ratio

A measure of how often a particular event happens in one group compared with how often it happens in another group, over time. When a characteristic (for example, being male) has a hazard ratio of one, this means that there is neither an increase nor a decrease in the risk of re-infection compared with a reference category (for example, being female).

Participant days at risk

The risk of re-infection varies from person to person, depending on when they were first infected. People who were first infected in the early part of the survey have had more opportunity to become re-infected compared with someone who has experienced their first infection more recently. Therefore, this analysis uses "participant days at risk" to determine the number of re-infections.

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

More information on measuring the data is available in the Coronavirus (COVID-19) Infection Survey statistical bulletin.

Our methodology article provides further information around the survey design, how we process data and how data are analysed.

Characteristics associated with testing positive analysis

All estimates of the likelihood of testing positive for COVID-19 by characteristic in Section 2 are unweighted. The sample for this analysis includes only those who have tested positive for COVID-19 on a swab test, and so there was no known population of which weighted estimates could be representative.

The analysis is based on statistical models at the UK level and include all participants aged two years and over. Demographic variables included in all models are age, region, sex, ethnicity, deprivation, household size, multigenerational household, and urban or rural classification. Additional variables 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 Coronavirus (COVID-19) Infection Survey technical article: analysis of populations in the UK by risk of testing positive for COVID-19, September 2021.

Re-infections with COVID-19 analysis

All estimates of COVID-19 re-infections in Sections 3 and 4 are unweighted. The sample for this analysis includes only those who have tested positive for COVID-19 on a swab test, and so there was no known population of which weighted estimates could be representative.

Since the bulletin published 30 March 2022, we have updated our definition of a re-infection to reflect the shorter time between re-infections that have occurred during the period when most infections were with the Omicron variants, compared with earlier variants.

Symptoms analysis

The analysis in Section 5 looks at each person who tested positive for COVID-19 and had a strong positive test in the UK. The strength of the 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.

Participants who only have positive tests with high Ct values (see Glossary) within a positive episode 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.

The analysis considers all symptoms reported at survey visits within 35 days of the first positive test in the episode. At each survey visit individuals are asked whether they had experienced a range of possible symptoms [note 1] in the seven days before they were tested, and also separately whether they felt that they had symptoms compatible with a COVID-19 infection 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. Positive episodes are 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".

Notes for: Measuring the data

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.

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