Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages in South Africa

doi:10.21203/rs.3.rs-1792132/v1

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Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages in South Africa

https://doi.org/10.21203/rs.3.rs-1792132/v1

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published 04 Oct, 2022

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Omicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. We assessed the severity of BA.4/BA.5 infections using the presence/absence of the S-gene target for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We linked national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assessed severity using multivariable logistic regression comparing the risk of hospitalisation and risk of severe disease, once hospitalised, for Delta, BA.1, BA.2 and BA.4/BA.5 infections. After controlling for factors associated with hospitalisation and severe outcome respectively, BA.4/BA.5-infected individuals had a similar odds of hospitalisation (aOR1.24, 95% CI 0.98–1.55) and severe outcome (aOR 0.71, 95%CI 0.41–1.25) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 continue to show reduced clinical severity compared to previous variants, as observed for Omicron BA.1.

SARS-CoV-2

Omicron

severity

BA.4

BA.5

South Africa

The Omicron SARS-CoV-2 variant of concern (VOC) was first detected in South Africa in mid-November 2021, with the BA.1 lineage driving a fourth wave of infections in the country¹. The BA.2 lineage became dominant in the period when SARS-CoV-2 case numbers were declining from the fourth wave peak, resulting in a slower decline and higher baseline than observed in previous inter-wave periods. New lineages of Omicron (BA.4 and BA.5) were detected by the Network for Genomic Surveillance in South Africa (NGS-SA) in January and February 2022, respectively, and by April were the dominant lineages in the country². BA.4 and BA.5 lineages were responsible for a fifth wave of infections, and varied geographically in dominance between the two lineages.

BA.4 and BA.5 have identical spike proteins, with additional mutations in the NTD (69–70 deletion) and RBD (L452R, F486V and wild-type Q493) regions compared to BA.2². These new lineages were estimated to have a growth advantage over BA.2, and showed reduced neutralization by serum obtained from individuals that had received three doses of COVID-19 vaccine (BNT162b or ChAdOx1-S) compared to BA.1 and BA.2^2,3. In addition, BA.4 and BA.5 have shown escape from BA.1 elicited immunity⁴. An increasing number of countries are reporting detection and increasing prevalence of BA.4 and/or BA.5, despite prior waves of Omicron BA.1 and BA.2.

We previously reported that Omicron BA.1 was associated with a lower risk of hospitalisation and lower risk of severe illness, compared to Delta variant infection⁵. A similar proportion of individuals were hospitalised and developed severe illness when infected with BA.2 compared to BA.1⁶. Reduced severity of BA.1 and BA.2 infections was also observed in other parts of the world^7,8. The BA.1, BA.4 and BA.5 lineages are associated with S-gene target failure (SGTF) when tested using the TaqPath™ COVID‑19 PCR test (Thermo Fisher Scientific, Waltham, MA, USA) due to the 69–70 amino acid deletion in the spike protein. Omicron BA.2 lacks this deletion, and therefore BA.2 infections are S-gene positive on this assay. It is important to understand clinical severity associated with infections due to BA.4 and BA.5, as the prevalence of these new lineages increases in other parts of the world. Leveraging on the presence or absence of the S-gene target, we aimed to assess the severity of BA.4/BA.5 lineages in the South African population.

We performed a data linkage study, using methods that have been previously described in detail⁵. Briefly, we linked national individual-level data from three sources: (i) national COVID-19 case data, (ii) SARS-CoV-2 laboratory test data for public sector laboratories and one large private sector laboratory, and (iii) DATCOV, which is an active surveillance system for COVID-19 hospital admissions in South Africa (including both incidental and attributable admissions). Case and test data were obtained on 26 April 2022, and DATCOV data on 11 May 2022. The dataset was restricted to tests performed on the TaqPath™ COVID‑19 assay (Thermo Fisher Scientific, Waltham, MA, USA). We used a combination of the presence (S-gene target positive, SGTP) or absence (S-gene target failure, SGTF) of the S-gene together with time period (restricted to time periods when the specific variant/lineage was predominant, Supplementary table 1), based on circulating variants/lineages from genomic surveillance in South Africa, as a proxy for the variant and lineage¹. We restricted to tests with a Ct value ≤ 30 for either the ORF1ab or nucleocapsid (N) gene targets to avoid incorrectly classifying infections as SGTF for which S gene was not detected because of low viral load. SGTP infections diagnosed in October and November 2021 were classified as Delta, SGTF infections diagnosed between November 2021 through January 2022 were classified as BA.1, SGTP infections diagnosed from February through April 2022 were classified as BA.2 and SGTF infections diagnosed in April 2022 were classified as BA.4/BA.5.

We used multivariable logistic regression models to assess risk factors for (i) hospitalisation and (ii) severe disease among hospitalised individuals (subset of individuals in model i), comparing Delta, BA.2, BA.4 and BA.5 infections to BA.1. We repeated the analysis comparing Omicron lineage infections to Delta. We controlled for factors associated with hospitalisation (age, sex, presence of co-morbidity, province, healthcare sector and prior SARS-CoV-2 infection) and factors associated with severity (age, presence of co-morbidity, sex, province, healthcare sector, number of days between the dates of specimen collection and hospital admission, known prior SARS-CoV-2 infection and SARS-CoV-2 vaccination status) based on previously described predictors of outcome in South Africa^9,10. Data on co-morbidities and reported SARS-CoV-2 vaccination were only available for hospitalized patients. To allow for at least three weeks of follow up, cases were censored to those with a specimen collected before 27 April 2022. Severity analysis was restricted to admissions that had already accumulated outcomes and all patients still in hospital were excluded.

We performed a sensitivity analysis, by using the same multivariable logistic regression models described above but restricting the time period to March and April 2022 (when BA.2 and BA.4/BA.5 were circulating), and adjusting for epidemiological week of infection in order to reduce bias due to differences in prior infection and vaccine-derived immunity, as well as changes in testing practices over time.

Severe disease was defined as a hospitalised patient meeting at least one of the following criteria: admitted to the intensive care unit (ICU), received any level of oxygen treatment, ventilated, received extracorporeal membrane oxygenation (ECMO), experienced acute respiratory distress syndrome and/or died, based on a modification of World Health Organization recommendations¹¹. Co-morbidity was defined as ≥ 1 of the following conditions: hypertension, diabetes, chronic cardiac disease, chronic kidney disease, asthma, chronic obstructive pulmonary disease, malignancy, HIV, and active or past tuberculosis. Re-infection was defined as an individual with previous positive tests > 90 days prior to the current episode.

Ethical approval was obtained from the Human Research Ethics Committee (Medical) of University of the Witwatersrand for the collection of COVID-19 case and test data as part of essential communicable disease surveillance (M210752), and for the DATCOV surveillance programme (M2010108).

In the period 1 October 2021 through 26 April 2022, 884,379 COVID-19 cases were diagnosed. Of these, 144,086 (16.3%) were known to have been diagnosed using the TaqPath™ COVID‑19 PCR test (Supplementary Fig. 1). The proportion of SGTP and SGTF infections varied throughout the period, with alternating dominance. Using the time period together with the presence/absence of the S-gene target, 98,710 infections could be classified as the likely SARS-CoV-2 variant/lineage: 1273 (1.3%) Delta; 75,563 (76.6%) BA.1; 20,086 (20.3%) BA.2; 1,806 (1.8%) BA.4/BA.5 infections.

Characteristics of individuals by variant/lineage are shown in Table 1. For all variants/lineages, the majority of cases occurred in adults aged ≥ 25 years (Delta 76.2%, BA.1 81.6%, 66.5% BA.2 and 78.7% BA.4/BA.5). A larger proportion of cases with BA.2 infections were children aged 5 to 18 years (24.7% BA.1 compared to 14.5% Delta, 9.1% BA.1 and 13.2% BA.4/BA.5). Among individuals with Delta infections, 13.5% were admitted to hospital, compared to 4.0% BA.1, 3.3% BA.2 and 4.8% BA.4/BA.5 (Table 1). The proportion of infections identified as re-infections was higher for all Omicron-infected individuals (9.7% BA.1, 9.3% BA.2 and 11.7% BA.4/BA.5) compared to Delta-infected individuals (2.9%). Self-reported vaccination status was only available for 44.6% (27,041/60,662) of hospitalised individuals, of which 29.2% (7908/27,041) reported having received at least one dose of SARS-CoV-2 vaccine (BNT162b or Ad26.COV2.S) (9.6%, 31.6%, 35.3% and 52.0% with Delta, BA.1, BA.2 and BA.4/BA.5 infections, respectively).

Table 1

Characteristics of individuals infected with SARS-CoV-2 by variant/lineage type, 1 October – 26 April 2021^a (N = 98710)
		Delta^b n (%)	BA.1^b n (%)	BA.2^b n (%)	BA.4/BA.5^b n (%)
Age group (years)		N = 1273	N = 75563	N = 20068	N = 1806
	< 5	19 (1)	1267 (2)	517 (3)	30 (2)
	5–12	57 (4)	3071 (4)	2369 (12)	134 (7)
	13–18	128 (10)	3809 (5)	2590 (13)	105 (6)
	19–24	99 (8)	5782 (8)	1255 (6)	116 (6)
	25–39	394 (31)	28371 (38)	5264 (26)	581 (32)
	40–59	372 (29)	24624 (33)	5889 (29)	591 (33)
	≥ 60	204 (16)	8639 (11)	2184 (11)	249 (14)
Sex		N = 1255	N = 74692	N = 19984	N = 1795
	Male	577 (46)	32780 (44)	9086 (45)	833 (46)
	Female	678 (54)	41912 (56)	10898 (55)	962 (54)
Province		N = 1243	N = 73921	N = 19948	N = 1790
	Eastern Cape	0 (0)	86 (0)	9 (0)	1 (0)
	Free State	67 (5)	2132 (3)	118 (1)	4 (0)
	Gauteng	44 (37)	38945 (53)	11935 (60)	1141 (64)
	KwaZulu-Natal	398 (32)	16680 (23)	3701 (19)	563 (31)
	Limpopo	26 (2)	2758 (4)	504 (3)	6 (0)
	Mpumalanga	44 (4)	3724 (5)	1862 (9)	28 (2)
	North West	35 (3)	3350 (5)	691 (3)	15 (1)
	Northern Cape	67 (5)	1192 (2)	41 (0)	1 (0)
	Western Cape	152 (12)	5054 (7)	1087 (5)	31 (2)
Hospital admission^C		N = 1273	N = 75563	N = 20068	N = 1806
	No	1101 (86)	72553 (96)	19405 (97)	1719 (95)
	Yes	172 (14)	3010 (4)	663 (3)	87 (5)
Healthcare sector		N = 1273	N = 75563	N = 20068	N = 1806
	Public	635 (50)	24760 (33)	2025 (10)	180 (10)
	Private	638 (50)	50803 (67)	18043 (90)	1626 (90)
Re-infection^d		N = 1273	N = 75563	N = 20068	N = 1806
	No	12336 (97)	68227 (90)	18202 (91)	1594 (88)
	Yes	37 (3)	7336 (10)	1866 (9)	212 (12)
Co-morbidity^e,f		N = 168	N = 2940	N = 637	N = 80
	No	100 (60)	2135 (73)	454 (71)	46 (58)
	Yes	68 (40)	805 (27)	183 (29)	34 (43)
COVID-19 Vaccination^f,g		N = 168	N = 2940	N = 637	N = 80
	No	47 (28)	916 (31)	196 (31)	12 (15)
	Yes	5 (3)	428 (15)	107 (17)	13 (16)
	Unknown	116 (69)	1596 (54)	334 (52)	55 (69)
^a Cases only include individuals whose infection was diagnosed using the TaqPath PCR assay. Individuals were followed-up for outcome until 11 May 2022
^b SGTP infections diagnosed in October and November 2021 were classified as Delta, SGTF infections diagnosed between November 2021 through January 2022 were classified as BA.1, SGTP infections diagnosed from February through April 2022 were classified as BA.2 and SGTF infections diagnosed in April 2022 were classified as BA.4/BA.5.
^c Admission to hospital between 7 days prior to 21 days after diagnosis (specimen collection date)
^d Re-infection was defined as an individual with at least one positive SARS-CoV-2 test > 90 days prior to the current episode
^e Co-morbidity defined as ≥ 1 of the following conditions: hypertension, diabetes, chronic cardiac disease, chronic kidney disease, asthma, chronic obstructive pulmonary disease, malignancy, HIV, and active or past tuberculosis.
^f Only available for hospitalized patients
^g Vaccination defined as defined as ≥ 1 dose of SARS-CoV-2 vaccine (BNT162b or Ad26.COV2.S)

On multivariable analysis, after controlling for factors associated with hospitalisation and compared to BA.1 infection, the odds of being admitted to hospital was higher for Delta-infected individuals (adjusted odds ratio (aOR) 3.41, 95% confidence interval (CI) 2.86–4.07), lower for BA.2-infected individuals (aOR 0.8, 95% CI 0.82–0.98), and was similar for BA.4/BA.5-infected individuals (aOR 1.24, 95% CI 0.98–1.55) (Table 2). In addition to geographic factors, hospital admission was associated with young age (< 5 years, aOR 7.10, 95% CI 5.81-8.67-9.32) and older age (40–59 years, aOR 1.36, 95%CI 1.15–1.60 and ≥ 60 years, aOR 4.77, 95% CI 4.06–5.61) compared to individuals aged 19–24 years, and female sex (aOR 1.09, 95%CI 1.02–1.17). Individuals were less likely to be admitted to hospital in the private sector (aOR 0.58, 95% 0.54–0.63) compared to the public sector. Using this same model, with Delta variant infections as the reference group, all Omicron lineages showed a reduced odds of hospitalisation (BA.1, aOR 0.29, 95% CI 0.25–0.35; BA.2, aOR 0.26, 95% CI 0.22–0.32; BA.4/BA.5, aOR 0.36, 95% CI 0.27–0.48). In the sensitivity analysis for risk of hospitalisation, individuals infected with BA.4/BA.5 had similar odds of being admitted compared to individuals infected with BA.2 (aOR 1.00, 95% CI 0.65–1.53).

Table 2

Multivariable logistic regression analysis evaluating the association between SARS-CoV-2 variant/lineage and hospitalisation, South Africa, 1 October 2021–26 April 2022^a (N = 95,940)
		Hospital admission^b n/N (%)	Adjusted odds ratio (95% CI)	P-value
SARS-CoV-2 variant/lineage^c		N = 98710
	Delta	172/1273 (14)	3.41 (2.86–4.07)	< 0.001
	BA.1	3010/75763 (4)	Ref	-
	BA.2	663/20068 (3)	0.90 (0.82–0.98)	0.021
	BA.4/BA.5	87/1806 (5)	1.24 (0.98–1.55)	0.070
Age group (years)		N = 98710
	< 5	271/1833 (15)	7.10 (5.81–8.67)	< 0.001
	5–12	139/5631 (2)	1.13 (0.90–1.42)	0.278
	13–18	139/6632 (2)	Ref	-
	19–24	184/7252 (3)	0.91 (0.72–1.14)	0.404
	25–39	995/34610 (3)	1.16 (0.98–1.36)	0.077
	40–59	1008/31476 (3)	1.36 (1.15–1.60)	< 0.001
	≥ 60	1196/11276 (11)	4.77 (4.06–5.61)	< 0.001
Sex		N = 97726
	Male	1663/43276 (4)	Ref	-
	Female	2249/54450 (4)	1.09 (1.02–1.17)	0.009
Province		N = 96902
	Eastern Cape	4/96 (4)	1.87 (0.67–5.21)	0.232
	Free State	112/2321 (5)	1.55 (1.20-2.00)	0.001
	Gauteng	1847/52475 (4)	1.54 (1.30–1.82)	< 0.001
	KwaZulu-Natal	1146/21342 (5)	2.16 (1.81–2.57)	< 0.001
	Limpopo	99/3294 (3)	1.64 (1.26–2.12)	< 0.001
	Mpumalanga	237/5658 (4)	2.26 (1.83–2.79)	< 0.001
	North West	190/4091 (5)	2.39 (1.92–2.98)	< 0.001
	Northern Cape	41/1301 (3)	0.92 (0.64–1.31)	0.651
	Western Cape	153/6324 (2)	Ref	-
Healthcare sector		N = 98710
	Public	1499/27600 (5)	Ref	-
	Private	2433/71110 (3)	0.58 (0.54–0.63)	< 0.001
Re-infection^d		N = 98710
	No	3648/89259 (4)	Ref	-
	Yes	284 /9451 (3)	1.01 (0.88–1.16)	0.853
^a Individuals followed-up for hospital admission until 11 May 2022
^b Admission to hospital between 7 days prior to 21 days after diagnosis (specimen collection date)
^c SGTP infections diagnosed in October and November 2021 were classified as Delta, SGTF infections diagnosed between November 2021 through January 2022 were classified as BA.1, SGTP infections diagnosed from February through April 2022 were classified as BA.2 and SGTF infections diagnosed in April 2022 were classified as BA.4/BA.5.
^d Re-infection was defined as an individual with at least one positive SARS-CoV-2 test > 90 days prior to the current episode

Among the 98,710 SARS-CoV-2 infected individuals with variant/lineage assigned and known outcome, 3,825 (3.9%) were admitted to hospital. Among admitted individuals with known outcome, 1276 (33.4%) developed severe disease: 57.7% (97/168) with Delta, 33.7% (990/2940) with BA.1, 26.2% (167/637) with BA.2 and 27.5% (22/80) with BA.4/BA.5 infections. On multivariable analysis compared to BA.1 infection, the odds of severe disease was only higher for Delta infection (aOR 2.40, 95% CI 1.67–3.42), was lower for BA.2 infection (aOR 0.78, 95% CI 0.63–0.97) and did not differ for BA.4/BA.5 infection (aOR 0.71, 95%CI 0.41–1.25) (Table 3). The odds of severe disease was higher among individuals aged 40–59 years (aOR 2.61, 95% CI 1.68–4.06) and ≥ 60 years (aOR 5.33, 95% CI 3.44–8.25) compared to individuals aged 19–24 years, as well as among individuals with underlying illness (aOR1.58, 95% CI 1.33–1.88). The odds of severe disease was lower for females (aOR 0.80, 95% CI 0.69–0.94), individuals hospitalised in the private sector (aOR 0.76, 95% CI 0.63–0.91) and those that had received ≥ 1 SARS-CoV-2 vaccine dose (aOR 0.70, 95% CI 0.54–0.90). The odds of severe disease was lower for individuals with prior infection, although in the multivariable model this finding was not statistically significant (aOR 0.9, 95% CI 0.6–1.3). Using this same model, with Delta variant infections as the reference group, all Omicron lineages showed a reduced odds of severe disease (BA.1, aOR 0.42, 95% CI 0.29–0.60; BA.2, aOR 0.33, 95% CI 0.22–0.49; BA.4/BA.5, aOR 0.30, 95% CI 0.15–0.57). In the sensitivity analysis for risk of severe disease, individuals infected with BA.4/BA.5 had similar odds of severe disease compared to individuals infected with BA.2 (aOR 0.78, 95% CI 0.37–1.62).

Table 3

Multivariable logistic regression analysis evaluating the association between SARS-CoV-2 variant/lineage and severe disease among hospitalised individuals, South Africa, 1 October 2021–26 April 2022^a (N = 3574)
		Severe disease^b n/N (%)	Adjusted odds ratio (95% CI)	P-value
SARS-CoV-2 variant/lineage^c		N = 3825
	Delta	97/168 (58)	2.40 (1.67–3.42)	< 0.001
	BA.1	990/2940 (34)	Ref	-
	BA.2	167/637 (26)	0.78 (0.63–0.97)	0.028
	BA.4/BA.5	22/80 (28)	0.71 (0.41–1.25)	0.238
Age group (years)		N = 3825
	< 5	45/267 (17)	1.00 (0.59–1.72)	0.987
	5–12	11/137 (8)	0.47 (0.22-1.00)	0.051
	13–18	18/134 (13)	0.80 (0.41–1.55)	0.511
	19–24	32/180 (18)	Ref	-
	25–39	188/976 (19)	1.06 (0.68–1.67)	0.768
	40–59	351/968 (36)	2.61 (1.68–4.06)	< 0.001
	≥ 60	631/1163 (54)	5.33 (3.44–8.25)	< 0.001
Sex		N = 3808
	Male	600/1616 (37)	Ref	-
	Female	669/2192 (31)	0.80 (0.69–0.94)	0.006
Province		N = 3727
	Eastern Cape	1/4 (25)	2.37 (0.19-29.00)	0.498
	Free State	43/99 (43)	3.92 (2.08–7.40)	< 0.001
	Gauteng	650/1800 (36)	3.34 (2.12–5.27)	< 0.001
	KwaZulu-Natal	322/1110 (29)	2.21 (1.38–3.54)	0.001
	Limpopo	19/98 (19)	1.59 (0.78–3.25)	0.203
	Mpumalanga	76/237 (32)	2.67 (1.53–4.65)	0.001
	North West	51/189 (27)	2.49 (1.40–4.43)	0.002
	Northern Cape	31/39 (79)	11.79 (4.64–29.99)	< 0.001
	Western Cape	36/151 (24)	Ref	-
Co-morbidity^d		N = 3825
	Absent	772/2735 (28)	Ref	-
	Present	504/1090 (46)	1.58 (1.33–1.88)	< 0.001
Healthcare sector		N = 3825
	Public	559/1436 (39)	Ref	-
	Private	717/2389 (30)	0.76 (0.63–0.91)	0.003
Days between diagnosis and admission		N = 3673
	1–7 days before diagnosis	129/340 (38)	Ref	-
	0–6 days after diagnosis	969/3023 (32)	0.84 (0.64–1.09)	0.193
	7–21 days after diagnosis	112/310 (36)	0.96 (0.67–1.38)	0.846
Re-infection^e		N = 3825
	No	1205/3551 (34)	Ref	-
	Yes	71/274 (26)	0.90 (0.64–1.27)	0.562
SARS-CoV-2 vaccination^f		N = 3825
	No	399/1171 (34)	Ref	-
	Yes	167/553 (30)	0.70 (0.54–0.90)	0.006
	Unknown	710/2101 (34)	0.93 (0.78–1.11)	0.461
^a Individuals followed-up for in-hospital outcome until 11 May 2022
^b Severe disease defined as a hospitalised patient meeting at least one of the following criteria: admitted to ICU, received oxygen treatment, ventilated, received extracorporeal membrane oxygenation (ECMO), experienced acute respiratory distress syndrome (ARDS) and/or died
^c SGTP infections diagnosed in October and November 2021 were classified as Delta, SGTF infections diagnosed between November 2021 through January 2022 were classified as BA.1, SGTP infections diagnosed from February through April 2022 were classified as BA.2 and SGTF infections diagnosed in April 2022 were classified as BA.4/BA.5.
^d Co-morbidity defined as ≥ 1 of the following conditions: hypertension, diabetes, chronic cardiac disease, chronic kidney disease, asthma, chronic obstructive pulmonary disease (COPD), malignancy, HIV, and active or past tuberculosis
^e Re-infection was defined as an individual with at least one positive SARS-CoV-2 test > 90 days prior to the current episode
^f Vaccination defined as ≥ 1 dose of SARS-CoV-2 vaccine (BNT162b or Ad26.COV2.S)

Omicron lineages have continued to emerge, most recently with the detection of BA.4 and BA.5 lineages². Rapidly characterising the new variants and lineages, and the effect on case numbers and thereby the impact on the health care system, is important. In this study, we aimed to determine the severity of Omicron BA.4 and BA.5 in South Africa through analysis of the risk of hospitalisation, and severe outcome once hospitalised. We found that BA.4/BA.5 infected individuals were not more likely to be hospitalised or develop severe disease compared to BA.1. Similarly to what was previously described⁵, Delta variant infection showed increased severity (risk of hospitalisation and severe disease) compared to BA.1.

During the fourth COVID-19 wave in South Africa, driven by Omicron BA.1, the country observed a de-coupling of the incidence of COVID-19 hospitalisations and deaths from incidence of infections¹². Much of this reduced severity is thought to be due to the high population immunity due to previous infection and/or vaccination in the South African population, which prior to the Omicron BA.1 wave was 73%¹². Although the large number of mutations in the spike protein of Omicron facilitates increased immune escape, the cellular immune response elicited by infection and/or vaccination recognises the Omicron variant¹³ and likely protects against severe disease.

In our study, individuals infected with BA.4/BA.5 lineages did not have increased clinical severity compared to individuals infected with BA.1. Recent data from a study conducted in hamsters showed that BA.4/BA.5 was more pathogenic than BA.2¹⁴. However, in our study, this increased pathogenicity did not translate into clinical severity. Recent national seroprevalence data among healthy blood donors post the BA.1 fourth wave in South Africa showed that 97% of individuals had SARS-CoV-2 antibodies, with 87% due to prior infection and an additional 10% due to vaccination alone¹⁵. This extremely high population immunity, and specifically the elicited T-cell responses, could explain the continuing low severity observed despite the emergence of additional Omicron lineages with increased transmissibility and immune escape. Our findings are supported by the low number of COVID-19 hospitalisations and in-hospital deaths reported during the fifth wave that was driven by the BA.4/BA.5 lineages¹⁶. However, this may not translate into reduced severity in other settings that do not have high population immunity as the increased transmissibility and immune escape of BA.4/BA.5 may lead to an increase in infections and thereby an increase in hospitalisations, with implications for healthcare systems.

Our study has a number of limitations. Firstly, the analysis is restricted to infections that were diagnosed using the TaqPath™ COVID-19 PCR assay, which was not used to the same extent throughout the country and therefore may bias the data geographically. Secondly, we used the combination of time period and presence/absence of the S-gene target as a proxy for variant/lineage. There may therefore have been some misclassification of the variants. To limit misclassification, we selected time periods based on sequencing data generated by NGS-SA¹ and restricted to time periods when the specific variant/lineage was predominant. Thirdly, vaccination information was restricted to hospitalised cases and was based on self-report. Fourthly, as only approximately 10% of SARS-CoV-2 are diagnosed¹⁷, it is likely that re-infection was under-ascertained. Fifthly, analysis of the proportion of individuals hospitalised could be affected by changes in testing practices. During the BA.4/BA.5 wave in some provinces there was a shift to preferential testing of hospitalised individuals¹⁰, which would make our estimate a minimum estimate. Lastly, we compared infections through the full Omicron BA.1 wave to infections in the ascending phase of the Omicron BA.4/BA.5 wave, this could bias comparisons if case characteristics differ in the ascending and descending wave phases or if threshold for hospitalisation changed in these time periods.

We found that in South Africa, where almost the entire population has SARS-CoV-2 antibodies, individuals infected with BA.4/BA.5 had a similar risk of hospitalisation and developing severe disease to individuals with BA.1 infection. Despite the emergence of BA.4/BA.5 leading to a fifth resurgence of cases in the country, this did not translate into severity levels observed in waves prior to Omicron. In addition, all Omicron lineages analysed (BA.1, BA.2, BA.4/BA.5) showed reduced severity compared to the Delta variant. As the prevalence of cases due to BA.4/BA.5 lineages increases in other countries, this data may be useful for healthcare resource planning, however our findings may not be fully extrapolated to other settings with different immune landscapes such as those with a higher proportion of immunity due to vaccination and not previous infection.

ACKNOWLEDGEMENTS

We acknowledge all NGS-SA members and laboratory teams, laboratory teams at the Centre for Respiratory Diseases and Meningitis and the Sequencing Core Facility of the NICD (Johannesburg, South Africa) for genomic sequencing data; and the national SARS-CoV-2 NICD surveillance team and NICD Information Technology team for NMCSS case data. We thank all laboratories for submitting specimens for sequencing, all public and private laboratories for COVID-19 diagnostic test data, and all public laboratories and Lancet Laboratories for ThermoFisher TaqPath™ COVID-19 PCR data. We thank all hospitals and health-care workers submitting data through the DATCOV surveillance programme.

FUNDING STATEMENT

This study was funded by the South African Medical Research Council with funds received from the National Department of Health. Sequencing activities for NICD are supported by a conditional grant from the South African National Department of Health as part of the emergency COVID-19 response; a cooperative agreement between the National Institute for Communicable Diseases of the National Health Laboratory Service and the United States Centers for Disease Control and Prevention (grant number 5 U01IP001048-05-00); the African Society of Laboratory Medicine (ASLM) and Africa Centers for Disease Control and Prevention through a sub-award from the Bill and Melinda Gates Foundation grant number INV-018978; the UK Foreign, Commonwealth and Development Office and Wellcome (Grant no 221003/Z/20/Z); and the UK Department of Health and Social Care and managed by the Fleming Fund and performed under the auspices of the SEQAFRICA project. The Fleming Fund is a £265 million UK aid programme supporting up to 24 low- and middle-income countries (LMICs) generate, share and use data on antimicrobial resistance (AMR) and works in partnership with Mott MacDonald, the Management Agent for the Country and Regional Grants and Fellowship Programme. This research was also supported by The Coronavirus Aid, Relief, and Economic Security Act (CARES ACT) through the Centers for Disease Control and Prevention (CDC) and the COVID International Task Force (ITF) funds through the CDC under the terms of a subcontract with the African Field Epidemiology Network (AFENET) AF-NICD-001/2021. Screening for SGTF at UCT was supported by the Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), which is supported by core funding from the Wellcome Trust (203135/Z/16/Z and 222754).

The findings and conclusions in this manuscript are those of the author(s) and do not necessarily represent the official position of the funding agencies.

The funders played no role in the writing of the manuscript or the decision to submit for publication.

DECLARATION OF INTERESTS

CC has received grant support from South African Medical Research Council, UK Foreign, Commonwealth and Development Office and Wellcome Trust, US Centers for Disease Control and Prevention and Sanofi Pasteur. NW has received grant support from Sanofi Pasteur and the Bill and Melinda Gates Foundation. AvG has received grant support from US Centers for Disease Control and Prevention, Africa Centres for Disease Control and Prevention, African Society for Laboratory Medicine (ASLM), South African Medical Research Council, WHO AFRO, The Fleming Fund and Wellcome Trust. RW declares personal shareholding in the following companies: Adcock Ingram Holdings Ltd, Dischem Pharmacies Ltd, Discovery Ltd, Netcare Ltd, Aspen Pharmacare Holdings Ltd. All other authors declare no conflict of interest.

DATA SHARING STATEMENT

Data used in this manuscript are available upon reasonable request. Proposals should be directed to [email protected].

AUTHOR CONTRIBUTIONS

Conception and design of study: NW, WJ, SW, AvG, CC

Data collection and laboratory processing: NW, WJ, SW, RW, HM, DGA, JE, JNB, CS, NT, NC, MdP, NG, AI, AG, KM, WS, FKT, KS, ZM, NH, RP, JW, AvG, CC

Analysis and interpretation: NW, WJ, SW, RW, HM, MG, DGA, JE, JNB, CS, NC, MdP, NG, AI, AG, KM, WS, FKT, ZM, NH, RP, JW, HH, MD, AB AvG, CC

Accessed and verified the underlying data: NW, RW, HM, DGA, JE, AvG

Drafted the Article: NW, AvG, CC

All authors critically reviewed the Article.

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Yes there is potential Competing Interest. CC has received grant support from South African Medical Research Council, UK Foreign, Commonwealth and Development Office and Wellcome Trust, US Centers for Disease Control and Prevention and Sanofi Pasteur. NW has received grant support from Sanofi Pasteur and the Bill and Melinda Gates Foundation. AvG has received grant support from US Centers for Disease Control and Prevention, Africa Centres for Disease Control and Prevention, African Society for Laboratory Medicine (ASLM), South African Medical Research Council, WHO AFRO, The Fleming Fund and Wellcome Trust. RW declares personal shareholding in the following companies: Adcock Ingram Holdings Ltd, Dischem Pharmacies Ltd, Discovery Ltd, Netcare Ltd, Aspen Pharmacare Holdings Ltd. All other authors declare no conflict of interest.

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Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages in South Africa

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