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Outcomes of laboratory-confirmed SARS-CoV-2 infection during resurgence driven by Omicron lineages BA.4 and BA.5 compared with previous waves in the Western Cape Province, South Africa

Open AccessPublished:November 24, 2022DOI:https://doi.org/10.1016/j.ijid.2022.11.024

      Abstract

      Objective

      We aimed to compare clinical severity of Omicron BA.4/BA.5 infection with BA.1 and earlier variant infections among laboratory-confirmed SARS-CoV-2 cases in the Western Cape, South Africa, using timing of infection to infer the lineage/variant causing infection.

      Methods

      We included public sector patients aged ≥20 years with laboratory-confirmed COVID-19 between 1-21 May 2022 (BA.4/BA.5 wave) and equivalent prior wave periods. We compared the risk between waves of (i) death and (ii) severe hospitalization/death (all within 21 days of diagnosis) using Cox regression adjusted for demographics, comorbidities, admission pressure, vaccination and prior infection.

      Results

      Among 3,793 patients from the BA.4/BA.5 wave and 190,836 patients from previous waves the risk of severe hospitalization/death was similar in the BA.4/BA.5 and BA.1 waves (adjusted hazard ratio (aHR) 1.12; 95% confidence interval (CI) 0.93; 1.34). Both Omicron waves had lower risk of severe outcomes than previous waves. Prior infection (aHR 0.29, 95% CI 0.24; 0.36) and vaccination (aHR 0.17; 95% CI 0.07; 0.40 for at least 3 doses vs. no vaccine) were protective.

      Conclusion

      Disease severity was similar amongst diagnosed COVID-19 cases in the BA.4/BA.5 and BA.1 periods in the context of growing immunity against SARS-CoV-2 due to prior infection and vaccination, both of which were strongly protective.

      Keywords

      Background
      The Omicron SARS-CoV-2 variant of concern (VOC) has been dominant globally since November 2021, with several sublineages causing surges in infections (Iketani et al., 2022, Tegally et al., 2022, Viana et al., 2022). South Africa experienced an initial large BA.1 infection surge from November 2021 to January 2022. BA.1 was then replaced by BA.2 but with no increase in cases numbers, and this was followed by a BA.4/BA.5 infection surge between April and June 2022 (Tegally et al., 2022, Viana et al., 2022). BA.4 and BA.5 share all mutations with BA.2, except the following: S:69-70del, S:L452R, S:F486V and S:Q493 (reversion to wild type). In addition, BA.4 is defined by ORF7b:L11F and N:P151S, whereas BA.5 is defined by M:D3N and ORF6:D61 (reversion to wild type) (Das et al., 2022, Dhawan et al., 2022, Kimura et al., 2022, Mohapatra et al., 2022). The combination of mutations in BA.4/BA.5 appear to confer a growth advantage over BA.2, as well as immune escape from vaccine-derived and BA.1 elicited antibodies (Khan et al., 2022, Tegally et al., 2022). BA.4 and BA.5 infections have been dominant globally since July 2022 (Bedford et al., 2022, Callaway, 2022, UK Health Security Agency, 2022).
      We therefore compared outcomes of laboratory-confirmed SARS-CoV-2 infections during the April-June 2022 resurgence (proxy for BA.4/ BA.5 infection) with outcomes during each of the four previous waves in South Africa, each of which were caused by a different variant or sublineage, using data on patients with laboratory-confirmed SARS-CoV-2 infection aged ≥20 years using public sector services in the Western Cape Province, South Africa.
      Methods:
      We conducted a cohort study using de-identified data from the Western Cape Provincial Health Data Centre (WCPHDC) of public sector patients aged ≥20 years with a laboratory confirmed COVID-19 diagnosis (positive SARS-CoV-2 PCR or antigen test). The Western Cape has nearly 7 million inhabitants, of whom approximately 75% use public sector health services (Western Cape Department of Health, 2020). The WCPHDC and approach for this study have previously been described in detail (Boulle et al., 2019, Davies et al., 2022, Hussey et al., 2022, Western Cape Department of Health in collaboration with the National Institute for Communicable Diseases, 2020). Briefly, for this analysis, waves of infection were defined as starting and ending when the 7-day moving average of public sector COVID-19 hospital admissions exceeded and dropped below 5 and 12 per million population respectively. We included cases diagnosed from seven days before the wave start to seven days before the wave end date to account for the lag between infection/first symptoms and hospitalization. We thus included data on cases diagnosed from 1-21 May 2022 for the BA.4/BA.5 wave, with follow-up through to 11 June 2022.This corresponds to the period when BA.4/BA.5 dominated in the province, accounting for 90% of sequenced cases in Western Cape (495/548; the remainder were BA.2 (n=51) with one BA.1 and one recombinant) as shown in Figure 1 (Network for Genomic Surveillance in South Africa, 2022).
      Figure 1
      Figure 1Number of SARS-CoV-2 diagnosed infections, proportion of SARS-CoV-2 tests that are positive PTP), number of specimens sequenced and distribution of different SARS-CoV-2 variants and subvariants in the Western Cape (WC), South Africa by epidemiologic week from 1 January 2021 to 25 June 2022. Courtesy Network for Genomics Surveillance in South Africa.
      We used Cox regression adjusted for age, sex, geographic location, comorbidities, service pressure (number of weekly admissions in the health district) at time of diagnosis, prior diagnosed infection (≥1 laboratory confirmed SARS-CoV-2 diagnosis ≥90 days previously) and SARS-CoV-2 vaccination to assess differences in the following COVID-19 outcomes between waves driven by different variants: (i) death and (ii) death or severe hospitalization (admission to intensive care or mechanical ventilation or oral/intravenous steroid prescription). We only included outcomes within 21 days of COVID-19 diagnosis for comparable ascertainment across all waves. All deaths within 21 days of a COVID-19 diagnosis were included unless a clear non-COVID-19 cause of death was recorded. For patients with recorded South African national identity numbers, data are linked to the South African vital registry to identify deaths not recorded in the WCPHDC. Vaccination data was obtained by linking the South African national identifier to the Electronic Vaccine Data System which records all vaccines administered in the country. The only vaccines available in South Africa to date are BNT162b2 and Ad26.COV2.S. For the regression models, vaccination status was categorized into five groups as (i) “≥3 doses” (three or more homologous or heterologous doses of any vaccine), (ii) “two doses” (two doses of any vaccine), (iii) “single dose Ad26.COV2.S” (single dose of Ad26.COV2.S), (iv) “single dose BNT162b2” (single dose of BNTB162b2), or (v) “unvaccinated”. Participants were considered to be in a particular vaccine group if they had received their last dose ≥7 days before COVID-19 diagnosis for “≥3 doses”, ≥14 days before for “two doses” and ≥28 days before for the single dose categories.
      The study was approved by the University of Cape Town and Stellenbosch University Health Research Ethics Committees and Western Cape Government: Health. Individual informed consent requirement was waived for this secondary analysis of de-identified data.
      Results
      We included 3,793 patients diagnosed in the BA.4/BA.5 wave and 27,614 (BA.1), 68,715 (Delta), 54,268 (Beta) and 40,204 (ancestral) in waves driven by previous variants (Table 1). The proportion of patients who died within 21 days of COVID-19 diagnosis varied across waves and was 1.9% (BA.4/BA.5), 2.5% (BA.1), 6.4% (Delta), 6.9% (Beta) and 5.3% (ancestral). The proportion with prior diagnosed infection was substantially higher in the BA.4/BA.5 (18.9%) and BA.1 (11.9%) waves compared to previous waves (<3%). In the BA.4/BA.5 wave, 12.9% of COVID-19 cases had received “single dose Ad26.COV2.S” vaccination, 3.9% “single dose BNT162b2”, 36.1% had received “two doses” and 6.7% had received “≥3 doses”..
      Table 1Characteristics and outcomes of COVID-19 cases included from each infection period in the Western Cape
      Ancestral wave

      25 Apr to 22 Jul 2020
      Date of diagnoses for cases included in each wave. We included cases diagnosed from 7 days prior to the "wave start" to the date of wave end (deemed to occur when 7 day moving average of daily new public sector admissions exceeded 5/million (start) and dropped below 12/million (end) respectively). bVaccination is summarized as vaccine type and number of doses provided diagnosis was ≥28 days after first dose, ≥14 days after second dose, and ≥7 days after third dose


      (n=40,204)
      Beta wave

      3 Nov 2020 to 22 Jan 2021
      Date of diagnoses for cases included in each wave. We included cases diagnosed from 7 days prior to the "wave start" to the date of wave end (deemed to occur when 7 day moving average of daily new public sector admissions exceeded 5/million (start) and dropped below 12/million (end) respectively). bVaccination is summarized as vaccine type and number of doses provided diagnosis was ≥28 days after first dose, ≥14 days after second dose, and ≥7 days after third dose


      (n=54,268)
      Delta wave

      30 May to 10 Sep 2021
      Date of diagnoses for cases included in each wave. We included cases diagnosed from 7 days prior to the "wave start" to the date of wave end (deemed to occur when 7 day moving average of daily new public sector admissions exceeded 5/million (start) and dropped below 12/million (end) respectively). bVaccination is summarized as vaccine type and number of doses provided diagnosis was ≥28 days after first dose, ≥14 days after second dose, and ≥7 days after third dose


      (n=68,750)
      BA.1 wave

      27 Nov 2021 to 12 Jan 2022
      Date of diagnoses for cases included in each wave. We included cases diagnosed from 7 days prior to the "wave start" to the date of wave end (deemed to occur when 7 day moving average of daily new public sector admissions exceeded 5/million (start) and dropped below 12/million (end) respectively). bVaccination is summarized as vaccine type and number of doses provided diagnosis was ≥28 days after first dose, ≥14 days after second dose, and ≥7 days after third dose


      (n=27,614)
      BA.4/BA.5 wave

      1 May to 21 May 2022
      Date of diagnoses for cases included in each wave. We included cases diagnosed from 7 days prior to the "wave start" to the date of wave end (deemed to occur when 7 day moving average of daily new public sector admissions exceeded 5/million (start) and dropped below 12/million (end) respectively). bVaccination is summarized as vaccine type and number of doses provided diagnosis was ≥28 days after first dose, ≥14 days after second dose, and ≥7 days after third dose


      (n=3,793)
      Male sex13,380 (33.3%)19,083 (35.2%)25,948 (37.7%)9,630 (34.9%)1,327 (35.0%)
      Age
      20-39 years18,720 (46.6%)21,839 (40.2%)29,720 (43.2%)13,944 (50.5%)1,783 (47.0%)
      40-49 years8,280 (20.6%)10,594 (19.5%)14,163 (20.6%)4,905 (17.8%)767 (20.2%)
      50-59 years6,982 (17.4%)10,493 (19.3%)13,294 (19.3%)4,216 (15.3%)623 (16.4%)
      60-69 years3,733 (9.3%)6,929 (12.8%)6,780 (9.9%)2,554 (9.3%)333 (8.8%)
      ≥70 years2,489 (6.2%)4,413 (8.1%)4,793 (7.0%)1,995 (7.2%)287 (7.6%)
      Non-communicable diseases
      diabetes8,265 (20.6%)11,509 (21.1%)11,581 (16.9%)3,627 (13.1%)406 (10.7%)
      hypertension13,065 (32.5%)19,070 (35.1%)21,170 (30.8%)7,063 (25.6%)842 (22.2%)
      chronic kidney disease2,013 (5.0%)2,778 (5.2%)3,018 (4.4%)958 (3.5%)124 (3.3%)
      chronic pulmonary disease / asthma3,099 (7.7%)4,661 (8.6%)6,434 (9.4%)3,040 (11.0%)411 (10.8%)
      Tuberculosis
      previous tuberculosis2,777 (6.9%)3,450 (6.4%)4,850 (7.1%)2,229 (8.1%)232 (6.1%)
      current tuberculosis513 (1.3%)555 (1.0%)803 (1.2%)578 (2.1%)76 (2.0%)
      HIV positive6,203 (15.4%)5,512 (10.2%)5,925 (8.6%)3,298 (11.9%)307 (8.1%)
      Prior diagnosed SARS-CoV-2 infection0 (0%)618 (1.1%)1,798 (2.6%)3,179 (11.5%)715 (18.9%)
      Vaccinationb
      noneN/AN/A63,644 (92.6%)14,471 (52.4%)1,535 (40.5%)
      single dose Ad26.COV2.SN/AN/A2,501 (3.6%)4,069 (14.7%)488 (12.9%)
      single dose BNT162b2N/AN/A2,289 (3.3%)1,144 (4.1%)147 (3.9%)
      2 doses Ad26.COV2.SN/AN/A30 (0.04%)1,127 (4.1%)298 (7.9%)
      2 doses BNT162b2N/AN/A286 (0.4%)6,763 (24.5%)1,067 (28.1%)
      2 doses Ad26.COV2.S + BNT162b2N/AN/AN/AN/A5 (0.1%)
      ≥3 doses Ad26.COV2.SN/AN/AN/A36 (0.1%)38 (1.0%)
      ≥3 doses BNT162b2N/AN/AN/A4 (0.01%)192 (5.1%)
      ≥3 doses Ad26.COV2.S + BNT162b2N/AN/AN/AN/A23 (0.6%)
      Outcomes within 21 days of diagnosis
      severe admission (not deceased)
      Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020. N/A = not applicable
      N/A
      Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020. N/A = not applicable
      1,916 (3.5%)2,066 (3.0%)481 (1.7%)61 (1.6%)
      death2,147 (5.3%)3,717 (6.9%)4368 (6.4%)699 (2.5%)70 (1.9%)
      a Date of diagnoses for cases included in each wave. We included cases diagnosed from 7 days prior to the "wave start" to the date of wave end (deemed to occur when 7 day moving average of daily new public sector admissions exceeded 5/million (start) and dropped below 12/million (end) respectively). bVaccination is summarized as vaccine type and number of doses provided diagnosis was ≥28 days after first dose, ≥14 days after second dose, and ≥7 days after third dose
      c Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020. N/A = not applicable
      The adjusted hazard of severe hospitalization or death in the BA.4/BA.5 wave was similar to the BA.1 wave (adjusted hazard ratio [aHR] 1.12; 95% confidence interval [CI]: 0.93; 1.34) (Table 2). Both Omicron-driven waves had lower hazards of severe hospitalization or death than previous waves (Table 2). Prior diagnosed infection was strongly protective against severe hospitalization or death (aHR 0.29; 95% CI 0.24; 0.36) as was vaccination with aHR (95% CI) of 0.17 (0.07; 0.40); 0.37 (0.33; 0.42);0.26 (0.21; 0.32) and 0.61 (0.56; 0.67) for “≥3 doses”, “two doses”, “single dose Ad26.COV2.S” and “single dose BNT162b2”, respectively. In a model not adjusting for vaccination and prior diagnosed infection, the hazard of severe hospitalization or death in the BA.4/BA.5 vs. BA.1 waves was reduced compared to the fully adjusted model (aHR 0.90; 95% CI: 0.75; 1.08). In an analysis restricted to the BA.4/BA.5 period, prior diagnosed infection remained strongly protective against severe hospitalization or death (aHR 0.23; 95% CI 0.10; 0.52) as did vaccination expect for “single dose BNT162b2” (aHR [95% CI]: 0.20 (0.08; 0.49); 0.39 (0.25; 0.59); 0.51 (0.27; 0.99) and 0.94 (0.44; 1.99) for “≥3 doses”, “two doses”, “single dose Ad26.COV2.S” and “single dose BNT162b2”, respectively. Results were all similar when examining the outcome of death alone.
      Table 2Associations between different infection periods and severe COVID-19 outcomes adjusted for patient characteristics, sub-district, vaccination, and prior diagnosed infection using Cox regression.
      Outcome = death

      not adjusted for vaccination and prior infection
      Outcome = death

      adjusted for vaccination and prior infection
      Outcome = severe hospitalization
      Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020.
      /death

      not adjusted for vaccination or prior diagnosed infection
      Outcome = severe hospitalization
      Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020.
      /death

      adjusted for vaccination or prior diagnosed infection
      Adjusted
      Adjusted for all variables shown in the table as well as subdistrict/district, but not for vaccination or prior diagnosed infection cVaccination status is categorized as “single dose BNT162b2” (≥28 days after single dose BNT162b2), “single dose Ad26.COV2.S” (≥28 days after single dose Ad26.COV2.S), “two doses” (≥14 days after second dose of homologous or heterologous vaccination with Ad26.COV2.S and/or BNT162b2), and “boosted” (≥7 days after third dose of homologous or heterologous vaccination with Ad26.COV2.S and/or BNT162b2); HR = Hazard Ratio; CI = Confidence Interval; N/A = not applicable
      HR
      95% CIAdjusted HR95% CIAdjusted
      Adjusted for all variables shown in the table as well as subdistrict/district, but not for vaccination or prior diagnosed infection cVaccination status is categorized as “single dose BNT162b2” (≥28 days after single dose BNT162b2), “single dose Ad26.COV2.S” (≥28 days after single dose Ad26.COV2.S), “two doses” (≥14 days after second dose of homologous or heterologous vaccination with Ad26.COV2.S and/or BNT162b2), and “boosted” (≥7 days after third dose of homologous or heterologous vaccination with Ad26.COV2.S and/or BNT162b2); HR = Hazard Ratio; CI = Confidence Interval; N/A = not applicable
      HR
      95% CIAdjusted HR95% CI
      Male sex (vs. female)1.401.34; 1.451.401.34; 1.451.271.23; 1.311.261.22; 1.30
      Age (vs. 20-39 years)
      40-49 years2.542.30; 2.812.572.33; 2.842.001.87; 2.152.041.90; 2.19
      50-59 years5.464.99; 5.975.565.08; 6.083.423.21; 3.653.503.28; 3.74
      60-69 years12.5511.47; 13.7312.8811.77; 14.106.395.97; 6.836.566.13; 7.01
      ≥70 years23.1921.15; 25.4323.9321.82; 26.2410.359.65; 11.0910.659.94; 11.42
      Comorbidities (vs. comorbidity absent)
      diabetes2.011.92; 2.102.011.93; 2.101.971.89; 2.041.981.91; 2.06
      hypertension1.081.03; 1.131.071.02; 1.121.181.14; 1.231.171.13; 1.22
      chronic kidney disease1.901.80; 2.001.901.81; 2.001.631.56; 1.701.631.56; 1.70
      chronic pulmonary disease / asthma0.980.93; 1.040.990.93; 1.041.181.13; 1.231.191.14; 1.24
      previous tuberculosis1.301.20; 1.401.281.19; 1.381.251.17; 1.331.231.16; 1.31
      current tuberculosis2.532.20; 2.912.442.13; 2.812.892.59; 3.232.792.50; 3.11
      HIV1.601.48; 1.721.601.49; 1.721.541.45; 1.641.541.45; 1.64
      Number of admissions in district in week of diagnosis (vs <1/3 of maximum)
      1/3 to <2/31.111.05; 1.171.121.06; 1.181.030.98; 1.081.040.99; 1.09
      ≥2/31.121.05; 1.201.131.06; 1.211.050.99; 1.111.061.00; 1.12
      Prior diagnosed SARS CoV-2 infection
      Yes (vs none)0.510.42; 0.630.290.24; 0.36
      Vaccination (vs. None)c
      single dose BNT162b20.560.49; 0.630.610.56; 0.67
      single dose Ad26.COV2.S0.240.18; 0.330.260.21; 0.32
      two doses (Ad26.COV2.S and/or

      BNT162b2)
      0.360.31; 0.420.370.33; 0.42
      boosted (≥ 3doses Ad26.COV2.S

      and/or BNT162b2)
      0.060.01; 0.400.170.07; 0.40
      Wave period (dominant variant)
      wave 1 (ancestral)2.081.90; 2.281.301.17; 1.44N/A
      Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020.
      N/A
      Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020.
      wave 2 (Beta)2.352.16; 2.571.471.34; 1.622.061.93; 2.201.281.20; 1.38
      wave 3 (Delta)2.582.37; 2.811.751.59; 1.922.162.03; 2.291.441.35; 1.54
      wave 4 (Omicron BA.1)RefRefRefRef
      wave 5 (Omicron BA.4/BA.5)0.930.72; 1.201.160.90; 1.500.900.75; 1.081.120.93; 1.34
      a Admission to an intensive care unit, mechanical ventilation or prescription of oral or intravenous steroids; not reported for wave 1 as steroids not widely used until after 16 June 2020.
      b Adjusted for all variables shown in the table as well as subdistrict/district, but not for vaccination or prior diagnosed infection cVaccination status is categorized as “single dose BNT162b2” (≥28 days after single dose BNT162b2), “single dose Ad26.COV2.S” (≥28 days after single dose Ad26.COV2.S), “two doses” (≥14 days after second dose of homologous or heterologous vaccination with Ad26.COV2.S and/or BNT162b2), and “boosted” (≥7 days after third dose of homologous or heterologous vaccination with Ad26.COV2.S and/or BNT162b2); HR = Hazard Ratio; CI = Confidence Interval; N/A = not applicable
      Discussion
      Using the period of diagnosis as a proxy for being infected with different Omicron sublineages in the Western Cape, we found no difference in the risk of severe COVID-19 hospitalization or death during the BA.4/BA.5 period compared to the BA.1 period, both of which had better outcomes than previous waves. Strong protection against severe COVID-19 conferred by prior infection and vaccination was retained in the BA.4/BA.5 wave, with three homologous doses of Ad26.COV2.S or BNT162b2 or a heterologous combination of these providing 83% protection (95% CI 60; 93%) against severe COVID-19 hospitalization or death amongst laboratory-confirmed cases.
      A study in animals recently suggested that BA.4/BA.5 may be more pathogenic than BA.2 (Kimura et al., 2022). Although we did not compare BA.4/BA.5 with BA.2 directly as BA.2 did not cause a distinguishable surge in infections in the Western Cape, disease severity of BA.2 and BA.1 are similar (Lewnard et al., 2022) and we found no evidence of worse clinical outcomes with BA.4/BA.5 compared to BA.1. Nonetheless, our findings need to be interpreted in the context of South African SARS-CoV-2 epidemiology with progressively increasing seroprevalence due to prior infection (mostly undiagnosed) and/or vaccination (Bingham et al., 2022, Madhi et al., 2022, Sun et al., 2022). For example, among blood donors, after the BA.1 wave the estimated national prevalence of anti-nucleocapsid antibodies was 87% (indicating previous infection) with a further 10% having anti-spike antibodies only (suggesting vaccination without prior infection) (Bingham et al., 2022). Since anti-nucleocapsid antibodies have lower sensitivity for identifying previous infections and may wane, it is possible that previous exposure to SARS-CoV-2 infections and/or vaccination may even exceed 97%. Indeed, our finding that the aHR shifted towards a lower risk of severe outcomes during BA.4/BA.5 vs. BA.1 in models not accounting for vaccination and prior diagnosed infection, suggests that the observed continued ecologic decoupling of COVID-19 cases and severe outcomes is at least partly due to growing protection against severe disease from both prior infection and vaccination. The observed clinical outcomes of infection with BA.4/BA.5 may therefore be different in settings with different prior variant infection and vaccination exposure. With the progression of the SARS-CoV-2 pandemic globally, it is increasingly difficult to determine the clinical severity of any variant in a completely naïve individual. However, for health service planning this is less relevant than the real-world effect in populations with varying degrees of immune protection (Mefsin et al., 2022). For example, although we showed similar risk of severe hospitalization or death in the BA.4/BA.5 and BA.1 waves when adjusted for vaccination and prior diagnosed infection, the actual burden of admissions and deaths was much lower in the BA.4/BA.5 waves, with the peak 7-day moving average of admissions and deaths being 222 and 36 in the BA.1 wave vs. 66 and 9 in the BA.4/BA.5 wave. The ability to use routine data to rapidly assess the relative severity of waves caused by different lineages and variants adjusted for comorbidities, vaccination and prior infection has been especially valuable for local health service planning (Davies et al., 2022).
      To our knowledge, this is one of the first comparisons of clinical severity of BA.4/BA.5 infections with previous variants with relatively complete adjustment for comorbidities and vaccination among all diagnosed cases. Nonetheless, this type of data and analysis have several limitations which have been described in detail previously (Davies et al., 2022). These include using the time of infection as a proxy for the variant causing infection rather than actual genomic sequencing or PCR test proxies (Wolter et al., 2022) which would be more accurate, could allow assessing the biological effect associated with specific mutations and would overcome challenges with comparing disease severity across waves due to differences in testing practices, treatment availability and health service pressures. Notably, testing in the BA.4/BA.5 wave was at the lowest levels since the start of the pandemic with less testing of patients with milder disease, hence we may have over-estimated disease severity in this wave. For example, the peak weekly testing rate in the BA.4/BA.5 wave in the Western Cape was only 1/3 of that during the BA.1 wave (256 vs 756 tests per week per 100,000 population). While we would have liked to assess the effects of time since vaccination and homologous vs. heterologous vaccine doses, it was not possible to do this analysis due to small numbers of participants with each of the different vaccine combinations and durations since last dose (Lyke et al., 2022). The routine health care data used did not allow us to distinguish between severe hospitalizations and deaths where the diagnosis of COVID-19 may have been incidental or contributory rather than causal. We also had incomplete ascertainment of key covariates especially prior diagnosed infection due to substantial missed diagnoses (only 19% of our BA.4/BA.5 cases had prior diagnosed infection whereas seroprevalence studies suggest at least 87% of the population had previous infection before the BA.4/BA.5 wave) (Bingham et al., 2022) and only including infections that were diagnosed more than 90 days apart. Similarly, due to the small numbers of patients with prior diagnosed infection and severe disease in the BA.4/BA.5 wave (n=6) we were unable to assess whether there were differences in the extent of protection conferred by previous infection with different variants, and even in those with prior diagnosed infection it is possible that they had additional unascertained infections in other waves that may have impacted on their protection against severe disease due to BA.4/BA.5. Further, we had no data on vaccinations received outside of the province or without submitting a South African identity number and undiagnosed comorbidities as we can only adjust for those algorithmically identified in the WCPHDC.
      In conclusion, we found similar disease severity amongst diagnosed COVID-19 cases in the BA.4/BA.5 and BA.1 periods, both of which were associated with less severe outcomes than waves caused by previous SARS-CoV-2 variants. This finding is in the context of growing immunity against SARS-CoV-2 with strong protection against severe outcomes conferred by prior infection and vaccination, especially >3 doses. Three homologous doses of Ad26.COV2.S or BNT162b2 or a heterologous combination provided 83% protection (95% CI 60; 93%) against severe COVID-19 hospitalization or death amongst laboratory-confirmed cases. Ensuring that individuals at high risk of severe COVID-19 outcomes have at least three vaccine doses remains a key strategy to limit the public health impact of further COVID-19 waves. Further research is needed to understand the specific differences in viral phenotype caused by the mutations in BA.4 and BA.5 as these mutations may occur in future variants and subvariants. In addition, it would be useful to quantify the protection provided by different types of immunity such as natural infection with different variants, hybrid immunity (natural infection with vaccination) and heterologous vs. homologous vaccination as well as waning of immunity.
      Acknowledgements
      We would like to acknowledge all patients in the Western Cape and to thank the Western Cape Department of Health Provincial Health Data Centre (WCPHDC), the South African National Department of Health and the Electronic Vaccine Data System, the Western Cape Department of Health COVID-19 Outbreak Response Team, the Western Cape Communicable Disease Control sub-directorate and Western Cape health care workers involved in the COVID-19 response for their contributions to this report.
      Funding Sources
      We acknowledge funding for the Western Cape Provincial Health Data Centre from the Western Cape Department of Health, the US National Institutes for Health (R01 HD080465, U01 AI069924), the Bill and Melinda Gates Foundation (1164272, 1191327), the United States Agency for International Development (72067418CA00023), the European Union (101045989) and the Grand Challenges ICODA pilot initiative delivered by Health Data Research UK and funded by the Bill & Melinda Gates and Minderoo Foundations (INV-017293). Funding was also received from Wellcome (203135/Z/16/Z [RJW, GM, WCPHDC], 222574 [RJW, WCPHDC] 214321/Z/18/Z [GM]) and the Medical Research Council of South Africa (RJW, MAD). RJW additionally receives support from the Francis Crick Institute which is funded by Wellcome (FC0010218), MRC (UK) (FC0010218), and Cancer Research UK (FC0010218). GM is also funded by the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation (NRF) of South Africa (Grant No 64787). The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of this report. The opinions, findings and conclusions expressed in this manuscript reflect those of the authors alone. For the purposes of open access the author has applied a CC-BY public copyright to any author accepted version arising from this submission.
      Ethical approval statement
      The study was approved by the University of Cape Town and Stellenbosch University Health Research Ethics Committees and Western Cape Government: Health. Individual informed consent requirement was waived for this secondary analysis of de-identified data.
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      Declaration of Competing Interest Statement

      All authors declare that they have no conflicts of interest.