Vaccine-surveillance-report-week-13.pdf

COVID-19 vaccine surveillance report – week 13

women of black ethnicity who delivered between June and August 2021 to 20.5% of these women delivering between September and November 2021 and further to 24.9% in December 2021. The difference in coverage between black and white women was 26.5 percentage points for women delivering between October to December, compared to 28.3 percentage points in the September to October period. In women living in the most deprived areas in England coverage increased from 7.8% to 25.5% to 32.7% in the same period. In addition, 24% of Black women and 28.4% of women living in the most deprived areas who were unvaccinated went on to be vaccinated post-partum. It is very reassuring that women who had received at least one dose of the vaccine in pregnancy were as likely to deliver live born babies at term without low birthweight as women who were not vaccinated in pregnancy. In addition, the group of women who were most likely to be immunised on the basis of their age group alone (vaccinated from 16 April 2021 and giving birth from 17 April 2021) were significantly more likely to deliver live born babies at term without low birthweight than women giving birth in the same period who were not vaccinated in pregnancy.

The specific outcomes that were considered (stillbirth, low birthweight and premature delivery) were similar or lower in women who were vaccinated whilst pregnant compared to women who were not vaccinated during their pregnancy.

36

COVID-19 vaccine surveillance report – week 13

Vaccination status in cases, deaths and hospitalisations From 1 April 2022, the UK Government will no longer provide free universal COVID-19 testing for the general public in England, as set out in the plan for living with COVID-19. Such changes in testing policies affect the ability to robustly monitor COVID-19 cases by vaccination status, therefore, from the week 14 report onwards this section of the report will no longer be published. Updates to vaccine effectiveness data will continue to be published elsewhere in this report. Please note that from 31 January 2022, UKHSA moved all COVID-19 case reporting in England to use a new episode-based definition which includes possible reinfections. Each infection episode is counted separately if there are at least 91 days between positive test results. Each infection episode begins with the earliest positive specimen date. Further information can be found on the UK COVID-19 dashboard. Vaccination status of COVID-19 cases, deaths and hospitalisations by week of specimen date over the past 4 weeks up to week 12 (up to 27 March 2022) are shown in tables 11 to 13. This data is published to help understand the implications of the pandemic to the NHS, for example understanding workloads in hospitals, and to help understand where to prioritise vaccination delivery. This raw data should not be used to estimate vaccine effectiveness.

We have published a blog post to accompany this section of the vaccine surveillance report.

Methods COVID-19 cases and deaths identified through routine collection from the Second Generation Surveillance System (SGSS) and from UKHSA EpiCell's deaths data, as described in the technical summary, were linked to the National Immunisation Management System (NIMS) to derive vaccination status, using an individual’s NHS number as the unique identifier. Attendance to emergency care at NHS trusts was derived from the Emergency Care Data Set (ECDS) managed by NHS Digital. The same data source was used to identify COVID-19 cases where the attendance to emergency care resulted in admission to an NHS trust. ECDS is updated weekly, and cases are linked to this data twice weekly. Data from ECDS is subject to reporting delays as, although NHS trusts may update data daily, the mandatory deadline for submission is by the 21st of every month. This means that for weeks immediately following the 21st of a month, numbers may be artificially low and are likely to be higher in later versions of the report. Data from ECDS also only reports on cases who have been presented to emergency care and had a related overnight patient admission and do not show those who are currently in hospital with COVID-19. As such, it is not appropriate for use for surveillance of those currently 37

COVID-19 vaccine surveillance report – week 13

hospitalised with COVID-19. In addition, this data will not show cases who were directly admitted as inpatients without presenting to emergency care. The outcome of overnight inpatient admission following presentation to emergency care, was limited to those occurring within 28 days of the specimen date for a COVID-19 case. Deaths include those who died (a) within 28 days of the most recent episode of infection or (b) within 60 days of the episode specimen date or more than 60 days after the episode specimen date with COVID-19 mentioned on the death certificate. The rate of COVID-19 cases, hospitalisation, and deaths in fully vaccinated and unvaccinated groups was calculated using vaccine coverage data for each age group extracted at the midpoint of the reporting period from NIMS.

Results The rate of a positive COVID-19 test varies by age and vaccination status. This is likely to be due to a variety of reasons, including differences in the population of vaccinated and unvaccinated people as well as differences in testing patterns. The rate of hospitalisation within 28 days of a positive COVID-19 test increases with age, and is substantially greater in unvaccinated individuals compared to vaccinated individuals. The rate of death within 28 days or within 60 days of a positive COVID-19 test increases with age, and again is substantially greater in unvaccinated individuals compared to fully vaccinated individuals.

Interpretation of data This data should be considered in the context of the vaccination status of the population groups shown in the rest of this report. In the context of very high vaccine coverage in the population, even with a highly effective vaccine, it is expected that a large proportion of cases, hospitalisations and deaths would occur in vaccinated individuals, simply because a larger proportion of the population are vaccinated than unvaccinated and no vaccine is 100% effective. This is especially true because vaccination has been prioritised in individuals who are more susceptible or more at risk of severe disease. Individuals in risk groups may also be more at risk of hospitalisation or death due to non-COVID-19 causes, and thus may be hospitalised or die with COVID-19 rather than from COVID-19. The vaccination status of cases, inpatients and deaths should not be used to assess vaccine effectiveness because of differences in risk, behaviour and testing in the vaccinated and unvaccinated populations. The case rates in the vaccinated and unvaccinated populations are crude rates that do not take into account underlying statistical biases in the data. There are likely to be systematic differences between vaccinated and unvaccinated populations, for example: 38

COVID-19 vaccine surveillance report – week 13

• testing behaviour is likely to be different between people with different vaccination status, resulting in differences in the chances of being identified as a case • many of those who were at the head of the queue for vaccination are those at higher risk from COVID-19 due to their age, their occupation, their family circumstances or because of underlying health issues • people who are fully vaccinated and people who are unvaccinated may behave differently, particularly with regard to social interactions and therefore may have differing levels of exposure to COVID-19 • people who have never been vaccinated are more likely to have caught COVID-19 in the weeks or months before the period of the cases covered in the report. This gives them some natural immunity to the virus which may have contributed to a lower case rate in the past few weeks These biases become more evident as more people are vaccinated and the differences between the vaccinated and unvaccinated population become systematically different in ways that are not accounted for without undertaken formal analysis of vaccine effectiveness. Vaccine effectiveness has been formally estimated from a number of different sources and is described on pages 4 to 13 in this report.

Denominator The potential sources of denominator data are either the National Immunisation Management Service (NIMS) or the Office for National Statistics (ONS) mid-year population estimates. Each source has its strengths and limitations which have been described in detail on the NHS website and GOV.Wales. NIMS may over-estimate denominators in some age groups, for example because people are registered with the NHS but may have moved abroad. However, as it is a dynamic register, such patients, once identified by the NHS, are able to be removed from the denominator. On the other hand, ONS data uses population estimates based on the 2011 census and other sources of data. When using ONS, vaccine coverage exceeds 100% of the population in some age groups, which would in turn lead to a negative denominator when calculating the size of the unvaccinated population. UKHSA uses NIMS throughout its COVID-19 surveillance reports including in the calculation rates of COVID-19 infection, hospitalisation and deaths by vaccination status because it is a dynamic database of named individuals, where the numerator and the denominator come from the same source and there is a record of each individual’s vaccination status.

Additionally, NIMS contains key sociodemographic variables for those who are targeted and then receive the vaccine, providing a rich and consistently coded data source for evaluation of the vaccine programme. Large scale efforts to contact people in the register will result in the identification of people who may be overcounted, thus affording opportunities to improve accuracy in a dynamic fashion that feeds immediately into vaccine uptake statistics and informs local vaccination efforts. 39

COVID-19 vaccine surveillance report – week 13

Sources of further information UKHSA has published a blog post to accompany this section of the report. The Office of the Statistics Regulator has published a blog post. UKHSA has published a significant amount of research into vaccine effectiveness which is summarised on pages 4 to 13 of this report. ONS has published research into the risk of testing positive for COVID-19 by vaccination status, impact of Delta on viral burden and vaccine effectiveness (4), and the risk of death by vaccination status.

40

COVID-19 vaccine surveillance report – week 13

Table 11. COVID-19 cases by vaccination status between week 9 2022 and week 12 2022 Please note that corresponding rates by vaccination status can be found in Table 14. Cases reported by specimen date between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022)

Total

Unlinked*

Not vaccinated

Received one Received one Second dose Third dose ≥14 dose (1 to 20 dose, ≥21 days ≥14 days days before days before before before specimen specimen date) specimen date specimen date1 date1

[This data should be interpreted with caution. See information below in footnote about the correct interpretation of these figures]

Under 18

234,919

9,694

172,743

1,331

21,201

27,633

2,317

18 to 29

212,638

13,906

28,140

290

9,843

47,550

112,909

30 to 39

279,848

13,330

29,166

177

7,082

44,727

185,366

40 to 49

253,592

9,312

15,437

49

3,497

26,565

198,732

50 to 59

242,471

8,162

7,669

27

1,834

14,514

210,265

60 to 69

166,870

4,948

3,013

10

764

5,486

152,649

70 to 79

105,126

3,129

1,266

6

391

1,903

98,431

80 or over

58,145

4,155

923

3

361

2,219

50,484

* Individuals whose NHS numbers were unavailable to link to the NIMS. 1 In the context of very high vaccine coverage in the population, even with a highly effective vaccine, it is expected that a large proportion of cases, hospitalisations and deaths would occur in vaccinated individuals, simply because a larger proportion of the population are vaccinated than unvaccinated and no vaccine is 100% effective. This is especially true because vaccination has been prioritised in individuals who are more susceptible or more at risk of severe disease. Individuals in risk groups may also be more at risk of hospitalisation or death due to non-COVID-19 causes, and thus may be hospitalised or die with COVID-19 rather than because of COVID-19.

41

COVID-19 vaccine surveillance report – week 13

Table 12. COVID-19 cases presenting to emergency care (within 28 days of a positive specimen) resulting in an overnight inpatient admission by vaccination status between week 9 2022 and week 12 2022 Please note that corresponding rates by vaccination status can be found in Table 14. Cases presenting to emergency care (within 28 days of a positive test) resulting in overnight inpatient admission, by specimen date between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022)

Total Unlinked*

Not vaccinated

Received one Received one dose (1 to 20 dose, ≥21 days days before before specimen date) specimen date

Second dose ≥14 days before specimen date1

Third dose ≥14 days before specimen date1

[This data should be interpreted with caution. See information below in footnote about the correct interpretation of these figures]

Under 18

1,096

27

965

5

56

38

5

18 to 29

690

8

246

3

47

190

196

30 to 39

692

5

200

0

38

156

293

40 to 49

582

10

124

0

34

111

303

50 to 59

892

1

127

1

37

155

571

60 to 69

1,054

5

116

0

24

135

774

70 to 79

2,014

5

140

1

29

171

1,668

80 or over

3,369

2

147

1

55

224

2,940

* Individuals whose NHS numbers were unavailable to link to the NIMS. 1 In the context of very high vaccine coverage in the population, even with a highly effective vaccine, it is expected that a large proportion of cases, hospitalisations and deaths would occur in vaccinated individuals, simply because a larger proportion of the population are vaccinated than unvaccinated and no vaccine is 100% effective. This is especially true because vaccination has been prioritised in individuals who are more susceptible or more at risk of severe disease. Individuals in risk groups may also be more at risk of hospitalisation or death due to non-COVID-19 causes, and thus may be hospitalised or die with COVID-19 rather than because of COVID-19.

42

COVID-19 vaccine surveillance report – week 13

Table 13. COVID-19 deaths (a) within 28 days and (b) within 60 days of positive specimen or with COVID-19 reported on death certificate, by vaccination status between week 9 2022 and week 12 2022 Please note that corresponding rates by vaccination status can be found in Table 14. (a) Death within 28 days of positive COVID-19 test by date of death between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022)

Total**

Unlinked*

Not vaccinated

Received one dose (1 to 20 days before specimen date)

Received one Second dose Third dose ≥14 days before dose, ≥21 days ≥14 days specimen before specimen before date1 date specimen date1

[This data should be interpreted with caution. See information below in footnote about the correct interpretation of these figures]

Under 18

2

0

1

0

1

0

0

18 to 29

6

0

1

0

0

1

4

30 to 39

20

0

8

0

1

3

8

40 to 49

26

1

5

0

1

9

10

50 to 59

72

0

16

0

5

17

34

60 to 69

163

1

31

0

11

39

81

70 to 79

435

3

48

0

6

70

308

80 or over

1,420

5

104

1

23

175

1,112

* Individuals whose NHS numbers were unavailable to link to the NIMS. ** number of deaths of people who had had a positive test result for COVID-19 and either died within 60 days of the first positive test or have COVID-19 mentioned on their death certificate. 1 In the context of very high vaccine coverage in the population, even with a highly effective vaccine, it is expected that a large proportion of cases, hospitalisations and deaths would occur in vaccinated individuals, simply because a larger proportion of the population are vaccinated than unvaccinated and no vaccine is 100% effective. This is especially true because vaccination has been prioritised in individuals who are more susceptible or more at risk of severe disease. Individuals in risk groups may also be more at risk of hospitalisation or death due to non-COVID-19 causes, and thus may be hospitalised or die with COVID-19 rather than because of COVID-19.

43

COVID-19 vaccine surveillance report – week 13

(b) Death within 60 days of positive COVID-19 test by date of death between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022)

Total**

Not vaccinated

Unlinked*

Received one dose (1 to 20 days before specimen date)

Received one dose, ≥21 days before specimen date

Second dose ≥14 days before specimen date1

Third dose ≥14 days before specimen date1

[This data should be interpreted with caution. See information below in footnote about the correct interpretation of these figures]

Under 18

3

0

2

0

1

0

0

18 to 29

15

0

6

0

1

3

5

30 to 39

44

0

13

0

4

10

17

40 to 49

61

1

11

0

2

18

29

50 to 59

155

0

24

0

8

45

78

60 to 69

350

1

48

0

16

77

208

70 to 79

825

3

72

0

19

120

611

80 or over

2,614

5

145

2

36

320

2,106

* Individuals whose NHS numbers were unavailable to link to the NIMS. ** number of deaths of people who had had a positive test result for COVID-19 and either died within 60 days of the first positive test or have COVID-19 mentioned on their death certificate. 1 In the context of very high vaccine coverage in the population, even with a highly effective vaccine, it is expected that a large proportion of cases, hospitalisations and deaths would occur in vaccinated individuals, simply because a larger proportion of the population are vaccinated than unvaccinated and no vaccine is 100% effective. This is especially true because vaccination has been prioritised in individuals who are more susceptible or more at risk of severe disease. Individuals in risk groups may also be more at risk of hospitalisation or death due to non-COVID-19 causes, and thus may be hospitalised or die with COVID-19 rather than because of COVID-19.

44

COVID-19 vaccine surveillance report – week 13

Table 14. Unadjusted rates of COVID-19 infection, hospitalisation and death in vaccinated and unvaccinated populations. Please note that the following table should be read in conjunction with pages 37 to 40 of this report, and the footnotes provided on page 45.

Cases reported by specimen date between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022)

Cases presenting to emergency care (within 28 days of a positive test) resulting in overnight inpatient admission, by specimen date between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022)

Death within 28 days of positive COVID- Death within 60 days of positive COVID19 test by date of death between week 9 19 test by date of death between week 9 2022 (w/e 6 March 2022) and week 12 2022 (w/e 6 March 2022) and week 12 2022 (w/e 27 March 2022) 2022 (w/e 27 March 2022)

[see information on population bases and unadjusted rates in footnotes 1 and 2 below this table] Unadjusted rates Unadjusted rates among persons among persons vaccinated with at not vaccinated (per least 3 doses (per 100,000)1,2 100,000)

Unadjusted rates Unadjusted rates among persons among persons vaccinated with at not vaccinated (per least 3 doses (per 100,000)2 100,000)

Unadjusted rates Unadjusted rates among persons among persons vaccinated with at not vaccinated (per least 3 doses (per 100,000)2 100,000)

Unadjusted rates Unadjusted rates among persons among persons vaccinated with at not vaccinated (per least 3 doses (per 100,000)2 100,000)

Under 18

1,454.0

1,711.7

3.1

9.6

0.0

0.0

0.0

0.0

18 to 29

3,118.8

941.6

5.4

8.2

0.1

0.0

0.1

0.2

30 to 39

4,324.7

1,085.6

6.8

7.4

0.2

0.3

0.4

0.5

40 to 49

3,957.8

955.3

6.0

7.7

0.2

0.3

0.6

0.7

50 to 59

3,303.4

779.8

9.0

12.9

0.5

1.6

1.2

2.4

60 to 69

2,814.9

572.8

14.3

22.1

1.5

5.9

3.8

9.1

70 to 79

2,161.5

532.1

36.6

58.8

6.8

20.2

13.4

30.3

80 or over

2,023.7

775.6

117.9

123.5

44.6

87.4

84.4

121.8

1 Comparing case rates among vaccinated and unvaccinated populations should not be used to estimate vaccine effectiveness against COVID-19 infection. Vaccine effectiveness has been formally

estimated from a number of different sources and is summarised on pages 4 to 14 in this report.

The rates are calculated per 100,000 in people who have received either 3 doses of a COVID-19 vaccine or in people who have not received a COVID-19 vaccine. These figures are updated each week as the number of unvaccinated individuals and individuals vaccinated with 3 doses in the population changes. The case rates in the vaccinated and unvaccinated populations are unadjusted crude rates that do not take into account underlying statistical biases in the data and there are likely to be systematic differences between these 2 population groups. For example: • testing behaviour is likely to be different between people with different vaccination status, resulting in differences in the chances of being identified as a case • many of those who were at the head of the queue for vaccination are those at higher risk from COVID-19 due to their age, their occupation, their family circumstances or because of underlying health issues • people who are fully vaccinated and people who are unvaccinated may behave differently, particularly with regard to social interactions and therefore may have differing levels of exposure to COVID-19 • people who have never been vaccinated are more likely to have caught COVID-19 in the weeks or months before the period of the cases covered in the report.

This gives them some natural immunity to the virus which may have contributed to a lower case rate in the past few weeks Case rates are calculated using NIMS, a database of named individuals from which the numerator and the denominator come from the same source and there is a record of each individuals vaccination status. Further information on the use of NIMS as the source of denominator data is presented on page 39 of this report. 2

Unadjusted case rates among persons not vaccinated have been formatted in grey to further emphasise the caution to be employed when interpreting this data. 45

COVID-19 vaccine surveillance report – week 13

Vaccine impact on proportion of population with antibodies to COVID-19 Seroprevalence The results from testing samples provided by healthy adult blood donors aged 17 years and older, supplied by the NHS Blood and Transplant (NHS BT collection) between weeks 35 2020 and week 8 of 2022 are summarised. As of week 44 of 2020, approximately 250 samples from each geographic NHS region are tested each week. The COVID-19 vaccination campaign began on the 8 December 2020 (week 50) with a phased roll out by age and risk group. From the beginning of September 2021, a third dose was offered to individuals with severe immunosuppression. A booster dose was introduced from 16 September 2021 for individuals aged 50 years and over, frontline health and social care staff, individuals aged 16 to 49 with certain underlying health conditions and household contacts of immunosuppressed individuals. Eligibility for booster doses was extended to individuals aged 40 years and over from 22 November and from December to those aged 18 to 39 in a phased rollout by age group. Booster doses are generally given at least 6 months after the second dose, although the minimum interval was reduced to at least 3 months from the second or third dose in an effort to accelerate the roll out with the emergence of the Omicron variant. Please note that this section will be updated monthly.

Last update was published on 10 March 2022.

Seroprevalence in blood donors aged 17 years and older The results presented here are based on testing samples with Roche nucleoprotein (N) and Roche spike (S) antibody assays. Nucleoprotein (Roche N) assays only detect post-infection antibodies, whereas spike (Roche S) assays will detect both post-infection antibodies and vaccine-induced antibodies. Thus, changes in seropositivity for the Roche N assay reflect the effect of natural infection. Increases in seropositivity as measured by S antibody reflect both infection and vaccination. Antibody responses to both targets reflect infection or vaccination occurring at least 2 to 3 weeks previously given the time taken to generate a COVID-19 antibody response. Currently donors are asked to defer donations for at least 48 hours post vaccination (previously 7 days), and for at least 10 full days after a positive COVID-19 test as well as 7 days following resolution of any symptoms (previously 28 days, changes were implemented during January 2022). This report presents Roche N and Roche S seropositivity estimates on the same set of samples, using a 12-week rolling prevalence for national, age group and regional estimates. Seropositivity estimates are plotted using the mid-point of a 12-weekly rolling period that reduces to 8 weeks in the most recent weeks to allow for a more representative current 46

COVID-19 vaccine surveillance report – week 13

estimate of seropositivity. However, this also means the data will reflect seroprevalence several weeks previously. Seroprevalence estimates reported are based on seropositivity which are unadjusted for the sensitivity and specificity of the assays used.

National prevalence Overall population weighted (by age group, sex and NHS region) antibody prevalence among blood donors aged 17 years and older in England was 36.0% (95% CI 35.1% - 36.8%) using the Roche N assay and 99.3% (95% CI 99.1% - 99.5%) using the Roche S assay for the period 4 January to 27 February (weeks 1 2022 to 8 2022). 5,325 out of 14,989 were Roche N positive and 14,904 out of 14,996 samples were Roche S positive. This compares with 23.6% (95% CI 22.9% - 24.2%) Roche N seropositivity and 98.5% (95% CI 98.3% - 98.7%) Roche S seropositivity for the period of 11 October to 31 December 2021 (weeks 41 to 52 2021). Seropositivity (weighted by region, age group and sex) varies over time. Figure 11 shows the overall 12-weekly rolling proportion seropositive over time for the Roche N and Roche S assays. Seropositivity estimates are plotted weekly using the mid-point of a rolling 12-weekly period. Figure 11. Overall 12-weekly rolling SARS-CoV-2 antibody seroprevalence (% seropositive) in blood donors

Regional prevalence of infection over time Seropositivity (weighted by age group and sex) using the Roche N assay which detects infection only, varies by region (Figure 12). 47

COVID-19 vaccine surveillance report – week 13

Figure 12. 12-weekly rolling SARS-CoV-2 antibody seroprevalence (% seropositive) in blood donors by region, using Roche N test; error bars show 95% confidence intervals.

Table 15. Roche N seropositivity (95%CI) estimates by NHS region NHS region

Weeks 41 to 52 2021

Weeks 1 to 8 2022

East of England

17.0% (15.6% - 18.5%)

26.8% (24.8% - 28.9%)

London

30.3% (28.5% - 32.1%)

44.9% (42.9% - 46.9%)

Midlands

24.2% (22.5% - 26.0%)

37.8% (35.6% - 40.0%)

North East and Yorkshire

26.8% (25.0% - 28.6%)

40.3% (38.0% - 42.6%)

North West

28.2% (26.5% - 30.1%)

43.1% (40.7% - 45.5%)

South East

18.2% (16.7% - 19.8%)

27.9% (25.7% - 30.2%)

South West

17.3% (15.9% - 18.8%)

26.4% (24.5% - 28.4%)

Increases in Roche N seropositivity have recently been observed across all regions (Table 15) compared to the previous 12-week period with the most notable increases in London, Midlands, North West and North East and Yorkshire regions. These increases are beginning to slow across all regions and plateauing of Roche N seropositivity can be seen in London in most recent weeks. This earlier plateauing in London is likely due to it being the first region to see large increases in case rates due the Omicron wave and peaking before other regions as well as already having the highest Roche N seropositivity. 48

COVID-19 vaccine surveillance report – week 13

Whilst seropositivity has consistently been lowest in the South West, recent increases have resulted in the region now having similar levels as observed in the East of England. With the emergence of the Omicron variant considerable increases in COVID-19 case rates in England have been observed across all regions which are now continuing to fall across all regions. (Weekly national Influenza and COVID-19 surveillance report week 8). Since it takes approximately 2 to 3 weeks to develop an antibody response following infection, recent rises in seroprevalence will likely reflect infection during the peak of the Omicron wave up to the end of January 2022.

Prevalence by age group Seropositivity estimates by age group using the Roche N assay are presented below. Figure 13. Population weighted 12-weekly rolling SARS-CoV-2 antibody seroprevalence (% seropositive) in blood donors from the Roche N assay by age group

Based on testing samples using the Roche N assay (Figure 13) as a marker of infection, the highest seropositivity continues to be observed in those aged 17 to 29 and the lowest in those aged 70 to 84.

49

COVID-19 vaccine surveillance report – week 13

Table 16. Roche N seropositivity (95%CI) estimates by age group Age group

Weeks 41 to 52 2021

Weeks 1 to 8 2022

17 to 29

33.4% (31.4% - 35.4%)

48.4% (45.9% - 50.8%)

30 to 39

25.0% (23.6% - 26.4%)

40.2% (38.4% - 42.1%)

40 to 49

27.9% (26.4% - 29.4%)

42.9% (41.1% - 44.8%)

50 to 59

22.7% (21.6% - 24.0%)

35.4% (33.9% - 37.0%)

60 to 69

17.0% (15.8% - 18.4%)

24.0% (22.3% - 25.6%)

70 to 84

9.6% (8.1% - 11.5%)

16.6% (14.3% - 19.2%)

Increases in Roche N seropositivity have recently been observed across all age groups (Table 16) compared to the previous 12-week period. In the most recent period, the largest increase in seropositivity was observed in the 3 youngest age groups. In England, COVID-19 case rates for weeks 4 2021 to week 8 2022, have decreased across most adult age groups with the highest rates currently seen in individuals aged 30 to 39 followed by 40 to 49 years old (Weekly national Influenza and COVID-19 surveillance report week 8). Roche S seropositivity in blood donors has plateaued and is now over 96% across all age groups. Seropositivity estimates for S antibody in blood donors are likely to be higher than would be expected in the general population and this probably reflects the fact that donors are more likely to be vaccinated. Seropositivity estimates for N antibody will underestimate the proportion of the population previously infected due to (i) waning of the N antibody response over time and (ii) observations from UK Health Security Agency (UKHSA) surveillance data that N antibody levels are lower in individuals who acquire infection following 2 doses of vaccination. These lower N antibody responses in individuals with breakthrough infections (post-vaccination) compared to primary infection likely reflect the shorter and milder infections in these patients.

Patients with breakthrough infections do have significant increases in S antibody levels consistent with boosting of their antibody levels. Vaccination has made an important contribution to the overall Roche S increases observed since the roll out of the vaccination programme, initially amongst individuals aged 50 years and above who were prioritised for vaccination as part of the phase 1 programme and subsequently in younger adults as part of phase 2 of the vaccination programme. The impact of the booster vaccination programme can be assessed by monitoring Roche S antibody levels across the population over time.

Roche S levels by age group and month The Roche S assay that the UK Health Security Agency (UKHSA) uses for serological surveillance is fully quantitative, meaning that it measures the level of antibodies in a blood sample; an antibody level above 0.8 au/ml (approximately 1 IU/ml using the WHO standard) is 50

COVID-19 vaccine surveillance report – week 13

deemed positive. The PHE/ UKHSA surveillance over the past few months has found that over 98% of the population of blood donors test positive for S-antibodies, which may have resulted from either COVID-19 infection or vaccination. With such high seropositivity, it is important to look at population antibody levels in order to assess the impact of the vaccination booster programme. In the previous report, groupings of antibody level ranges were updated to better illustrate changes over time. Figure 14 shows monthly categorised Roche S levels in N-antibody negative individuals by age group over the past year. In the 3 oldest age groups, the impact of first vaccine dose, then second vaccine dose, can be seen from March through June 2021, as the profile of population antibody levels increases. Then from June through September the profile of antibody levels in these cohorts gradually decreases, consistent with waning. During October there was a small increase in percentage of donors with very high antibody levels of 10,000+ au/ml for the 50 to 84 age group, following the initiation of the booster programme. In November the proportion of donors with very high antibody levels of 10,000+ au/ml increased further particularly in those aged 70 to 84 years. In December large increases were observed in the proportion of donors aged 50 to 69 with very high antibody levels of 10,000+ au/ml.

By January 2022 large increases were also observed in younger age groups as the booster programme was accelerated due to the emergence of the Omicron variant, however the slightly decreasing profile of antibody levels among all age groups in February shows signs of waning. Given the evidence of waning, those most at risk are being offered a booster vaccine in the Spring. Figure 15 shows categorised Roche S levels in N-antibody positive individuals, those likely to have experienced past infection. Pre-vaccination antibody levels will be influenced by time since infection, variant and severity of infection, as well as individual factors such as underlying health conditions and age. In November more than half of donors aged 70 to 84 years had very high antibody levels of 25,000+ au/ml. By January 2022 increases in the proportion of donors with very high antibody levels of 25,000+ AU/ml were observed across all age groups. Comparing Figure 14 with Figure 15, the overall higher profile of antibody levels in those who have experienced past infection is evident; both vaccination post infection and breakthrough infection following vaccination are expected to boost existing antibody levels. Researchers across the globe are working to better understand what antibody levels mean in terms of protection against COVID-19.

Current thinking is that there is no threshold antibody level that offers complete protection against infection, but instead that higher antibody levels are likely to be associated with lower probability of infection.

51

COVID-19 vaccine surveillance report – week 13

Figure 14. Categorised Roche S antibody levels by age group and month in N negative samples, March 2021 to February 2022

Figure 15. Categorised Roche S antibody levels by age group and month in N positive samples, March 2021 to February 2022

52

COVID-19 vaccine surveillance report – week 13

Direct impact on hospitalisations The analysis estimates the number of hospitalisations averted by booster vaccinations in the period since 13 December 2021 when Omicron infections started to become more dominant. The booster vaccination programme was accelerated and expanded to all adults aged 18 years and over from November 2021 in response to a rapid increase in Omicron infections. The number of hospitalisations averted is estimated by incorporating vaccine effectiveness against hospitalisation, vaccine coverage and observed hospitalisations. The focus of the calculation in this model is hospitalisations averted in the Omicron period given the coverage of booster vaccinations. This allows us to model the expected number of hospitalisations in the absence of the booster vaccination programme. The most recent estimates for vaccine effectiveness against hospitalisations are used: 85% from the booster against Omicron in the period 5-9 weeks post booster and 35% for the second dose for the period 25+ weeks after that dose. This gives a relative effectiveness (rVE) of the booster compared to 2 doses of 1-(10.85)/(1-0.35) = 77%.

The expected cases in the absence of boosting is calculated as O 0/1+ [O2/boost / (1- (booster cover/(booster cover + 2 dose cover))*rVE)], where O 0/1 is observed hospitalised cases with 0 or 1 doses and O2/boost is observed cases with 2 doses or more (note that these observed totals are in fact estimated using information from the subset of SARIWatch cases where this information is ascertained, with weekly proportions with each dose number applied to the daily overall hospitalisation numbers). The daily expected cases are calculated per age group and summed for an overall total in the period. The overall total per age group is summed to provide the all age total across the period. This is the same for the observed calculation. Based on the direct effect of the booster vaccination and booster vaccine coverage rates, UKHSA estimates that around 192,900 hospitalisations have been prevented in those aged 25 years and over in England from 13 December 2021 to 20 March 2022 inclusive. The total number averted by age group is approximately 159,700 in those aged 65 years and over, 25,700 in those aged 45 to 64 years and 7,500 in those aged 25 to 44 years as a result of the booster vaccination programme (Figure 16). All those aged 25 to 64 years in this analysis are inclusive of healthy and at-risk individuals. Several caveats are necessary to consider.

The indirect effect of protection from infection and onwards transmission is not considered. Any indirect effects are likely to be small given the low and rapidly waning vaccine effectiveness against mild disease/infection observed with the Omicron variant. The vaccine effectiveness estimates used in this model are based on all age estimates. Work is being done to further assess VE against different hospitalisation end points and how this differs by age which could lead to changes in these impact estimates. Finally, these estimates currently do not take into account waning following a booster dose. Please note this analysis will be updated every 2 weeks. The next update will be in the report for week 14 2022. 53

COVID-19 vaccine surveillance report – week 13

Figure 16. Estimated number of hospitalisations averted by booster vaccinations since 13 December 2021 100% 90%

Number of hospitalisations

5000

80% 70%

4000

60% 3000

50% 40%

2000

30% 20%

1000

10% 0

0%

Date Observed ≥25y

Expected ≥25y

D3 Coverage (11 days earlier) 65y+

D3 Coverage (11 days earlier) 45-64y

D3 Coverage (11 days earlier) 25-44y

54

Percentage vaccine coverage (cumulative)

6000

COVID-19 vaccine surveillance report – week 13

References 1. 2. 3.

4.

5.

6.

7.

8.

9.

10. 11.

12.

PHE. ‘COVID-19: vaccine surveillance strategy 2021’ Medicines and Healthcare Products Regulatory Agency. ‘Coronavirus vaccine – weekly summary of Yellow Card reporting 2021’ Andrews N, Stowe J, Kirsebom F, Toffa S, Rickeard T, Gallagher E, Gower C, Kall M, Groves N, O'Connell A, Simons D, Blomquist PB, Dabrera G, Myers R, Ladhani SN, Amirthalingam G, Gharbia S, Barrett JC, Elson R, Ferguson N, Zambon M, Campbell CNJ, Brown K, Hopkins S, Chand M, Ramsay M, Lopez Bernal J. ‘Effectiveness of COVID-19 vaccines against the Omicron (B.1.1.529) variant of concern’ medRxiv 2021: 14 December 21267615 Whitaker H, Tsang R, Byford R, Andrews N, Sherlock J, Sebastian Pillai P and others. ‘Pfizer-BioNTech and Oxford AstraZeneca COVID-19 vaccine effectiveness and immune response among individuals in clinical risk groups’ Amirthalingam G, Bernal JL, Andrews NJ and others. ‘Serological responses and vaccine effectiveness for extended COVID-19 vaccine schedules in England.’ Nature Communications 12, 7217 (2021). https://doi.org/10.1038/s41467-021-27410-5 Lopez Bernal J, Andrews N, Gower C, Robertson C, Stowe J, Tessier E and others.

‘Effectiveness of the Pfizer-BioNTech and Oxford-AstraZeneca vaccines on COVID19-related symptoms, hospital admissions, and mortality in older adults in England: test negative case-control study.’ British Medical Journal 2021: volume 373, n1,088 Vasileiou E, Simpson CR, Robertson C, Shi T, Kerr S, Agrawal U and others. ‘Effectiveness of first dose of COVID-19 vaccines against hospital admissions in Scotland: national prospective cohort study of 5.4 million people.’ 2021 Hyams C, Marlow R, Maseko Z, King J, Ward L, Fox K and others. ‘Effectiveness of BNT162b2 and ChAdOx1 nCoV-19 COVID-19 vaccination at preventing hospitalisations in people aged at least 80 years: a test-negative, case-control study.’ Lancet Infectious Diseases 2021 Ismail SA, Vilaplana TG, Elgohari S, Stowe J, Tessier E, Andrews N and others. ‘Effectiveness of BNT162b2 mRNA and ChAdOx1 adenovirus vector COVID-19 vaccines on risk of hospitalisation among older adults in England: an observational study using surveillance data.’ PHE Preprints. 2021 Effectiveness of COVID-19 vaccines against Omicron and Delta hospitalisation: test negative case-control study Lopez Bernal J, Andrews N, Gower C, Stowe J, Tessier E, Simmons R and others. ‘Effectiveness of BNT162b2 mRNA vaccine and ChAdOx1 adenovirus vector vaccine on mortality following COVID-19.’ medRxiv.

2021 Andrews N, Tessier E, Stowe J, Gower C, Kirsebom F, Simmons R and others. ‘Vaccine effectiveness and duration of protection of Comirnaty, Vaxzevria and Spikevax against mild and severe COVID-19 in the UK’. medRxiv 2021

55

COVID-19 vaccine surveillance report – week 13

13.

14.

15.

16.

17.

18.

19.

20. 21.

22.

23.

24. 25.

Pritchard E, Matthews PC, Stoesser N, Eyre DW, Gethings O, Vihta K-D and others. ‘Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK’s COVID-19 Infection Survey.’ medRxiv 2021: 2021.04.22.21255913 Hall VJ, Foulkes S, Saei A, Andrews N, Oguti B, Charlett A and others. ‘COVID-19 vaccine coverage in health-care workers in England and effectiveness of BNT162b2 mRNA vaccine against infection (SIREN): a prospective, multicentre, cohort study.’ Lancet 2021 Shrotri M, Krutikov M, Palmer T, Giddings R, Azmi B, Subbarao S and others. ‘Vaccine effectiveness of the first dose of ChAdOx1 nCoV-19 and BNT162b2 against SARS-CoV-2 infection in residents of long-term care facilities in England (VIVALDI): a prospective cohort study.’ Lancet Infectious Diseases 2021 Menni C, Klaser K, May A, Polidori L, Capdevila J, Louca P and others. ‘Vaccine side-effects and SARS-CoV-2 infection after vaccination in users of the COVID-19 Symptom Study app in the UK: a prospective observational study.’ The Lancet Infectious Diseases 2021 Harris RJ, Hall JA, Zaidi A, Andrews NJ, Dunbar JK, Dabrera G. ‘Effect of Vaccination on Household Transmission of SARS-CoV-2 in England’ New England Journal of Medicine 2021 V Shah AS, Gribben C, Bishop J, Hanlon P, Caldwell D, Wood R and others.

‘Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households.’ medRxiv 2021: 2021.03.11.21253275 Eyre DW, Taylor D, Purver M, Chapman D, Fowler T, Pouwels KB, Walker S, Peto T. ‘The impact of SARS-CoV-2 vaccination on Alpha and Delta variant transmission’ medRxiv 2021: 2021.09.28.21264260 COVID-19 Vaccine Effectiveness against the Omicron BA.2 variant in England Clifford S, Waight P, Hackman J, Hue S, Gower CM, Kirsebom FCM, Skarnes C, Letley L, Lopez Bernal J, Andrews N, Flasche S, Miller E. ‘Effectiveness of BNT162b2 and ChAdOx1 against SARS-CoV-2 household transmission: a prospective cohort study in England’ medRxiv 2021.11.24.21266401; doi: https://doi.org/10.1101/2021.11.24.21266401 Zauche LH and others. ‘Receipt of mRNA COVID-19 vaccines and risk of spontaneous abortion.’ New England Journal of Medicine, 2021 volume 385, issue 16, pages 1533-5 Kadiwar S and others. Were pregnant women more affected by COVID-19 in the second wave of the pandemic?. The Lancet 2021: volume 397, issue 10,284, pages 1,539-40 University of Edinburgh. ‘Outputs and information for the public’ Public Health Scotland. ‘Scottish Intensive Care Society Audit Group report on COVID-19, 23 September 2021’

56

COVID-19 vaccine surveillance report – week 13

26.

27. 28. 29. 30.

31. 32.

33.

34. 35. 36. 37. 38.

39.

40. 41.

42.

Zambrano LD and others. ‘Update: characteristics of symptomatic women of reproductive age with laboratory-confirmed SARS-CoV-2 infection by pregnancy status - United States, January 22 to October 3’ JCVI issues new advice on COVID-19 vaccination for pregnant women Pregnant women urged to come forward for COVID-19 vaccination JCVI announcement regarding COVID-19 vaccination during pregnancy and next steps Goldshtein I and others. ‘Association between BNT162b2 vaccination and incidence of SARS-CoV-2 infection inpregnant women.’ Journal of the American Medical Association, 2021, volume 326 issue 8, pages 728-35 Dagan N and others. ‘Effectiveness of the BNT162b2 mRNA COVID-19 vaccine in pregnancy.’ Nature Medicine 2021: volume 27, issue 10, pages 1,693-5 Gray KJ and others. ‘Coronavirus disease 2019 vaccine response in pregnant and lactating women: a cohort study.’ American Journal of Obstetrics and Gynecology. 2021: volume 225, issue 3, pages 303 e1-e17 Halasa NB, Olson SM, Staat MA and others. ‘Effectiveness of maternal vaccination with mRNA COVID-19 vaccine during pregnancy against COVID-19–associated hospitalization in infants aged under 6 months — 17 States, July 2021–January 2022’. MMWR Morbidity and Mortality Weekly Report 2022: volume 71, pages 264270 Key information on COVID-19 in pregnancy | UKOSS | NPEU Stock S and others.

‘COVID-19 vaccination rates and SARS-CoV-2 infection in pregnant women in Scotland.’ Research Square, 2021 Public Health Wales. Rapid COVID-19 virology - Public | Tableau Public Centers for Disease Control and Prevention. Vaccine Pregnancy Registry Shimabukuro TT and others. ‘Preliminary findings of mRNA COVID-19 vaccine safety in pregnant persons.’ New England Journal of Medicine 2021: volume 384, issue 24, pages 2273-82 Kharbanda EO and others. ‘Spontaneous abortion following COVID-19 vaccination during pregnancy.’ Journal of the American Medical Association 2021; volume 326, issue 16, pages 1629-1631 Magnus MC and others. ‘COVID-19 vaccination during pregnancy and first- trimester miscarriage.’ New England Journal of Medicine 2021 Vousden N and others. ‘Impact of SARS-CoV-2 variant on the severity of maternal infection and perinatal outcomes: data from the UK Obstetric Surveillance System national cohort.’ medRxiv, 2021 Wilson EB. ‘Probable inference, the law of succession, and statistical inference.’ Journal of the American Statistical Association: volume 1,927, issue 22, pages 209-12

57

About the UK Health Security Agency UKHSA is responsible for protecting every member of every community from the impact of infectious diseases, chemical, biological, radiological and nuclear incidents and other health threats. We provide intellectual, scientific and operational leadership at national and local level, as well as on the global stage, to make the nation heath secure. UKHSA is an executive agency, sponsored by the Department of Health and Social Care.

© Crown copyright 2022

Published: 31 March 2022 Publishing reference: GOV-11859 For queries relating to this document, please contact: enquiries@ukhsa.gov.uk

You may re-use this information (excluding logos) free of charge in any format or medium, under the terms of the Open Government Licence v3.0. To view this licence, visit OGL. Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned.

58