Coronavirus (COVID-19) Infection Survey, characteristics of people testing positive for COVID-19, UK: 22 June 2022

• The risk of coronavirus (COVID-19) re-infection was approximately seven times higher in the period when the Omicron variants were most common (20 December 2021 to 4 June 2022), compared with when the Delta variant was most common (17 May to 19 December 2021).
• Those in older age groups were less likely to be re-infected than those in younger age groups, from 2 July 2020 to 4 June 2022.
• 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 4 June 2022.
• The percentage of people testing positive for COVID-19 in the survey who reported symptoms decreased in May 2022 compared with April 2022; this may partly be because of overall decreasing infections in May 2022.
• The percentage of people testing positive for COVID-19 who reported loss of taste or smell remained at lower levels in May 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 on re-infections, risk factors associated with re-infection and symptoms reported by strong positive cases of coronavirus (COVID-19). 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 section looks at the rate of coronavirus (COVID-19) re-infections in the UK, from 2 July 2020 to 11 June 2022.

The technical article on re-infections provides a more detailed explanation of the methods used, some of which have since been updated. Tables 1a to 1d in the accompanying dataset for this bulletin contain our re-infections data.

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 a combination of the number of days between initial and subsequent positive tests and the number of immediately preceding negative tests, and the viral load and variant type of initial and subsequent positive tests. Full details of the definition used to identify a re-infection in this analysis can be found in Section 8: Measuring the data. A re-infection is therefore only identified when an "at risk" individual has a positive test.

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.

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 was approximately seven 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 1. In addition to the variables presented in Figure 1, we also looked at the risk of re-infection during the periods when different variants became most common and the effect 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 was approximately seven times higher in the period when the Omicron variants were most common (95% confidence interval: five to nine 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.

Those in older age groups were less likely to be re-infected than those in younger age groups, from 2 July 2020 to 4 June 2022.

Hazard ratios for all characteristics included in the model, including for Ct values separately, can be found in Tables 2a and 2b in the accompanying dataset. Estimated rates of re-infection over time can be found in Table 2c in the accompanying dataset.

Figure 1: 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 4 June 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 effects of periods in which different variants were most common, and the effect of Ct values, are not included in this figure but are presented in Tables 2a and 2b 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. 

Download the data

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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 31 May 2022, and for the period from 1 March to 2 June 2022 split by UK country. All of our symptoms analysis can be found in Tables 3a to 3f 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 May 2022

In May 2022, 60% (95% confidence interval: 58% to 61%) 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 April 2022. This may be because of a decrease in overall positive infections in May 2022 compared with April 2022. As positivity declines, a greater percentage of the positive cases we identify in the survey are identified towards the end of their infection and therefore, may be less likely to report symptoms.

The percentage of people reporting loss of taste or smell decreased sharply between December 2021 and January 2022 and remained at a lower level in May 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 remained at low levels in May 2022.

The percentages of people testing positive who reported each group of symptoms are similar for each country between 1 March and 2 June 2022.

Figure 2: The percentage of people testing positive for COVID-19 who reported loss of taste or smell remained at low levels in May 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 31 May 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, shortness of breath, fatigue, headache and myalgia, decreased in May 2022 compared with April 2022.

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.

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.

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.

Re-infections with COVID-19 analysis

All estimates of COVID-19 re-infections in Sections 2 and 3 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.

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

For time since previous infection and number of negative tests, if there is 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

For 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.

For 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.

Symptoms analysis

The analysis in Section 4 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.