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Background: More than half the global population has been exposed to SARS-CoV-2. Naturally induced immunity influences the outcome of subsequent exposure to variants and vaccine responses. We measured anti-spike IgG responses to explore the basis for this enhanced immunity. Methods: A prospective cohort study of mothers in a South African community through ancestral/beta/delta/omicron SARS-CoV-2 waves (March 2020-February 2022). Health seeking behaviour/illness were recorded and post-wave serum samples probed for IgG to Spike (CoV2-S-IgG) by ECLISA. To estimate protective CoV2-S-IgG threshold levels, logistic functions were fit to describe the correlation of CoV2-S-IgG measured before a wave and the probability for seroconversion/boosting thereafter for unvaccinated and vaccinated adults. Findings: Despite little disease, 176/339 (51·9%) participants were seropositive following wave 1, rising to 74%, 89·8% and 97·3% after waves 2, 3 and 4 respectively. CoV2-S-IgG induced by natural exposure protected against subsequent SARS-CoV-2 infection with the greatest protection for beta and least for omicron. Vaccination induced higher CoV2-S-IgG in seropositive compared to naïve vaccinees. Amongst seropositive participants, proportions above the 50% protection against infection threshold were 69% (95% CrI: 62, 72) following 1 vaccine dose, 63% (95% CrI: 63, 75) following 2 doses and only 11% (95% CrI: 7, 14) in unvaccinated during the omicron wave. Interpretation: Naturally induced CoV2-S-IgG do not achieve high enough levels to prevent omicron infection in most exposed individuals but are substantially boosted by vaccination leading to significant protection. A single vaccination in those with prior immunity is more immunogenic than 2 doses in a naïve vaccinee and may provide adequate protection. Funding: UK NIH GECO award (GEC111), Wellcome Trust Centre for Infectious Disease Research in Africa (CIDRI), Bill & Melinda Gates Foundation, USA (OPP1017641, OPP1017579) and NIH H3 Africa (U54HG009824, U01AI110466]. HZ is supported by the SA-MRC. MPN is supported by an Australian National Health and Medical Research Council Investigator Grant (APP1174455). BJQ is supported by a grant from the Bill and Melinda Gates Foundation (OPP1139859). Stefan Flasche is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant number 208812/Z/17/Z).
We studied participants in an established South African birth cohort, the Drakenstein Child Health Study (DCHS),20 using a convenience sample of sequential maternal participants through the COVID-19 pandemic from 6 March 2020 to 28 February 2022, spanning four waves. The convenience sample included sequential mothers attending follow-up visits with their children with blood sampling through all 4 waves of the pandemic. The study is situated in a low-income peri-urban community, in which there is a strong primary health care program, well established study surveillance systems for illness and high cohort retention as previously described.20 Illness and health seeking behaviour were monitored throughout and additional study visits through each wave were initiated with serum samples obtained. Serological responses to SARS-CoV2 were measured in 4 matched sera obtained following each of the 4 waves. These were defined by the SA National Institute of Communicable Diseases as wave 1 (ancestral strain) week 24-35 2020, wave 2 (beta variant) week 48 2020-week 5 2021, wave 3 (delta variant) week 19-37 2021 and wave 4 (omicron variant) week 45 2021-week 3 2022.21 A national program for SARS-CoV2 vaccination began for health care workers from March 2021 providing a single dose of Ad.26COV2.S (Johnson & Johnson vaccine; AD26.COV.2.S); this was broadened to include all adults (>18 years) from June 2021, in which a single dose Ad26.COV.2.S or 2 doses of BNT162b2 (Pfizer-BioNTech) vaccine (given 6 weeks apart) became available. Booster doses of either AD26.COV.2.S or BNT162b2 became available from January 2022. The national program is the only source of SARS-CoV-2 vaccination available in South Africa. The study was approved by the Human Research Ethics Committee, Faculty of Health Sciences University of Cape Town (HREC 401/2009). Mothers provided written informed consent which was renewed annually. Serum samples from mothers were tested for IgG to spike (S) protein derived from ancestral SARS-CoV-2 (S-ancestral), beta (S-beta), delta (S-delta) or Omicron (S-omicron) variants using an Electrochemiluminescent Immunosorbent Assay (ECLISA) on the Meso Scale discovery platform (MSD® Rockville, MD). The description and qualification of this quantitative binding assay has been described in detail by us previoulsy.22 The binding data generated in this assay is expressed in WHO International Units as the assay is calibrated against the WHO international standard and the assay correlates well with functional measures of SARS-CoV-2 immunity12 The detection of S-ancestral IgG in this assay is highly specific (97.4%) and sensitive (90.3%) for exposure to SARS-CoV-2 and hence was used to define seropositivity (S-ancestral ≥1·09 WHO BAU/ml). Geometric mean concentrations (95% CI) of IgG levels (GMC) for SARS-CoV2 antibodies were calculated. IgG to spike from different strains cross-reacts but higher titres are generated to the infecting strain therefore a ratio of variant S-IgG: S-ancestral IgG was calculated. Data were analyzed using STATA 14.1 (STATA Corporation, College Station, TX USA) and R (R core team 2021, version 4.1.2). Data were summarised as frequencies (percent) if categorical and median (interquartile range (IQR)) if continuous. Wilcoxon rank-sum test (Mann-Whitney U test), Wilcoxon signed-rank test and Chi-square or Fisher’s exact were used for crude comparisons, as appropriate. Seropositivity was measured longitudinally though each wave; once vaccinated, a participant was excluded from calculation of seroprevalence. A Kaplan-Meier plot was used to calculate the time in which unvaccinated participants became seropositive through the 4 waves; a participant was censored at the time of seropositivity. Generalised estimating equations (GEE) were used to identify risk factors associated with seropositivity over the waves. A binomial distribution and logit link function, as well as robust standard errors to account for the presence of heteroscedascity, were used in generating the GEE models. The model was adjusted for age, HIV infection, marital status, maternal education, maternal employment, household income, household size, maternal smoking, asthma diagnosis and maternal weight. To estimate threshold levels of antibodies induced by prior exposure or vaccine which may protect against subsequent SARS-CoV-2 infection, 4-parameter logistic functions were fit to spike IgG titres measured before and after the beta, delta and omicron waves. Similar to a logistic regression the probability of seroconversion (defined as titres increasing by more than 1% post wave after the beta, delta and omicron waves was estimated as a function of the amount of the antibody prior to a wave but using a more flexible link function using uninformative or weakly informative priors. This allowed estimation of infection attack rates in naïve or vaccinated individuals (upper asymptote), the maximal protection achievable from naturally derived or vaccine induced antibodies (lower asymptote) and an antibody threshold associated with protection against seroconversion (the inflection point of the curve where the probability of protection against seroconversion passes the 50% midpoint between the upper and lower asymptote). Sensitivity analyses on the choice of % increase threshold (10% as opposed to 1%, and accounting for waning between samples), were also explored in the Supplement, as well as the inclusion of a vaccine term in the model to estimate a vaccine effect on probability of seroconversion independent of IgG-mediated protection. The software package R2Jags was used for Bayesian model fitting. The model code is available from the github repository: https://github.com/bquilty25/covid_seroconv. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.
