The Impact Of Severe Acute Respiratory Syndrome Coronavirus 2 Vaccination And Infection On Neutralizing Antibodies: A Nation-wide Cross-sectional Analysis

Background.

Neutralizing antibodies (nAbs) play a critical role in the protection against severe COVID-19. In the era of vaccine boosters and repeated SARS-CoV-2 outbreaks, identifying individuals at risk represents a public health priority.

Neutralizing antibodies are antibodies that block the invasion of host cells by binding to antigens on the surface of pathogens. In the immune response, when the body is invaded by pathogens, the immune system will release antibodies to neutralize the pathogens and prevent them from continuing to infect.

Various immune cells and molecules in the immune system are involved in the neutralization of pathogens. T cells, B cells, antibodies, and other immune molecules can work together to prevent pathogens from entering cells.

The production of neutralizing antibodies mainly depends on the body's immune cells, B cells. When the body is invaded by pathogens, B cells will produce specific antibodies to neutralize the pathogens. Therefore, the enhancement of immunity can improve the production capacity of neutralizing antibodies, thereby more effectively eliminating pathogens and protecting the health of the body.

In short, neutralizing antibodies are closely related to immunity. The stronger the immunity, the more fully and effectively the production of neutralizing antibodies. Therefore, we need to pay close attention to the improvement of our immunity. Cistanche can significantly improve immunity. Meat ash contains a variety of biologically active ingredients, such as polysaccharides, two mushrooms, and Huangli, etc. These ingredients can stimulate the immune system. Various types of cells, increase their immune activity.

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Methods.

Relying on the Monaco COVID Public Health Programme, we evaluated nAbs from July 2021-June 2022 in 8,080 SARS-CoV-2 vaccinated and/or infected children and adults, at their inclusion visit. We stratified by infection status and investigated variables associated with nAbs using a generalized additive model.

Results. 

Infected and vaccinated participants had high and consistent nAbs (>800 IU/mL), which remained stable over time since injection, regardless of the number of vaccine doses, body mass index, sex, or age. By contrast, uninfected participants showed larger variability (two doses [V2] median 157.6; interquartile range [IQR] 43.3-439.1 IU/mL) versus three doses [V3] median 882.5; [829.5-914.8] IU/mL). NAbs decreased by 20% per month after V2 (adjusted ratio 0.80; 95%CI [0.79-0.82]) but remained stable after V3 (adjusted ratio 0.98; 95%CI [0.92-1.05]).

Conclusions.

Hybrid immunity provided stable, high, and consistent nAbs over time. The benefit of boosters was marked to restore decaying nAbs in uninfected participants. NAbs could identify individuals at risk of severe COVID-19 and provide more targeted vaccine boosters campaigns.

Keywords.

COVID-19; Keywords SARS-CoV-2; hybrid immunity; neutralizing antibodies; vaccination.

More than 18 months after the launch of vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), distinguishing individuals who are protected against severe disease from those who do not represent a public health priority. Vaccine boosters are progressively being recommended worldwide, arguing that immunity may wane a few months after vaccination, especially against variants such as Delta (B.1.617.2) or Omicron (BA.1, BA.2, BA.2.12.1, BA.2.75, BA.4, and BA.5) [1–3]. However, generalizing repeated vaccine boosters remains controversial, while both scientists and public health authorities highlight the importance of identifying those with the highest risk of developing a severe form of coronavirus disease 19 (COVID-19) [4–6]

Given the constant emergence of new circulating variants, protection against severe COVID-19 is the primary objective of SARS-CoV-2 vaccination [7–9]. Protection is often measured through humoral immunity, based on neutralizing antibodies (nAbs) [10–12], which represent an acknowledged indicator of the prognosis of severe COVID-19 [13]. However, predicting nAb levels after vaccination is challenging, with substantial variations according to factors such as age, sex, and weight [14–16]. All this evidence relies on studies carried out over limited periods, with small sample sizes, and restricted to particular age categories. The available evidence on the humoral response after SARS-CoV-2 infections are similarly limited [17], and this also seems difficult to predict; a longitudinal study identified 5 different nAb profiles, from late persistence to rapid decline [18]. Therefore, the impact of both SARS-CoV-2 vaccination and infection on humoral immunity warrants large and long-term evaluations in the general population. In the current study, using a real-world setting, we assessed SARS-CoV-2 nAb levels after SARS-CoV-2 vaccination and infection in children and adults, 24 months after the beginning of the pandemic.

METHODS

Study Setting

Monaco is the most densely populated country in the world, with 38 359 inhabitants living in a 2.02 km2 territory and with a median age of 46.4 years [19]. It's demographics and health system are similar to those of larger neighboring Western European countries. Migrant workers mainly from France and Italy commute daily to Monaco, doubling the local population [20].

The Monaco COVID Public Health Programme (MCPHP) offers free-of-charge SARS-CoV-2 screening and vaccination services to all residents, in a unique public community health center. Screening consists of nasopharyngeal and salivary reverse-transcriptase polymerase chain reaction (RT-PCR) testing. The vaccination protocol follows World Health Organization (WHO) recommendations, has exclusively relied on the BNT162b2 vaccine, and started on 31 December 2020.

On July 2021, the Monaco government added a serological component to the MCPHP, which offers SARS-CoV-2 nAb measurement to all residents, regardless of age, meeting ≥1 of the following criteria: (1) a documented SARS-CoV-2 infection, confirmed by nasopharyngeal or salivary RT-PCR or antigenic rapid diagnostic test result, validated by the French National Authority for Health (https://COVID-19.sante.gouv. fr/tests) or documented vaccination.

The objective of the MCPHP is to inform each participant of their risk level against severe COVID-19, by measuring nAbs which are a demonstrated indicator of protection [13].

Participants are also informed about their levels of total binding antibodies (bAbs) against SARS-CoV-2 nucleocapsid (anti-N), indicating a past COVID-19 infection [21, 22] and total bAbs against the SARS-CoV-2 receptor-binding domain (anti-RBD) of the spike protein, indicating a past COVID-19 infection and/or an immune reaction to SARS-CoV-2 vaccination [23, 24]. All serological results are communicated to the participant within 72 hours after sampling, and a follow-up visit is recommended every 6 months.

Study Design and Population

The MonaVacc study is nested within the MCPHP, aiming to analyze nAbs, compare levels within and between participants, and identify subgroups that may present a weakened humoral immune response. The MonaVacc baseline analysis focused on the enrollment visit and excluded the following participants (Figure 1): (1) those without a nAb measurement; (2) those with an ambiguous infection or vaccination status, including those with qualitative results missing for either anti-RBD or anti-N antibodies (Supplementary Table 1); those with an unusual vaccination course using a non–European Union–approved vaccine (ie, Sputnik V); those who received 4 vaccine doses; and those with >1 year between nAb measurement and the last vaccine dose.

Ethics Statement

An information sheet was first provided either in French or in English, explaining in plain language both the MCPHP and the MonaVacc study. Then, a written consent form was obtained for participants >18 years old signed by the legal representative or guardian for those <18 years old [25]. It is emphasized that collected data are anonymized for any statistical analysis purposes. The protocol, informed consent form, and case record form were reviewed and approved by the Monaco ethics committee for biomedical research, (reference 2021.5365 AP/jv; dated 10 June 2021). The study is registered at clinicaltrials.gov (NCT05084950).

Individual Participant Data

A questionnaire was administered on-site by a community health worker to document demographic data and reported both vaccination and infection dates. Participants provided a 3-mL blood sample for serological analysis. In addition, their medical records were extracted from the national public health database using their unique identification codes, including documented SARS-CoV-2 testing and vaccination records.

Biological Sample Management and Laboratory Analyses

Blood samples are collected by community health workers in serum clot activator tubes (Greiner Bio-One) and stored onsite at +4°C in a fridge. Four times a day, whole-blood samples are transported in a cool box to the public health laboratory. Whole blood is then centrifuged, and serum is collected and aliquoted into 3 tubes. One tube is kept in a −80°C freezer and archived for future use if required. One tube is tested for total bAbs, using Elecsys Anti-SARS-CoV-2 S (Cobas pro; Diagnostics Roche), specifically targeting the RBD of the SARS-CoV-2 spike protein, and Anti-SARS-CoV-2 (Cobas pro; Diagnostics Roche), specifically targeting the SARS-CoV-2 nucleocapsid. Total bAb levels are quantitatively measured, and the values are expressed according to the manufacturer’s recommendations [26].

The third tube of serum is tested for SARS-CoV-2 nAbs using a Food and Drug Administration (FDA)–approved surrogate virus neutralization test, the accuracy of which has been reported elsewhere [27–32]. The GenScript (class) is a commercial kit, based on a blocking enzyme-linked immunosorbent assay; it uses purified RBD of the spike protein from SARS-CoV-2 and the host receptor angiotensin-converting enzyme 2 to mimic the virus-host interaction. The targeted strain of the neutralizing assay is Wuhan-Hu-1. The level of nAbs was determined as the percentage of inhibition, according to the FDA-approved method [28]. The quantification of nAbs was then converted to international units per milliliter, after calibration of the assay to the WHO international standard for anti–SARS-CoV-2 immunoglobulins [33].

Definitions

Participants’ infection and vaccination status at baseline were determined as presented in Supplementary Table 1. Briefly, infection and vaccination status were defined using the Monaco national public health database, which includes recorded infections, vaccination, and serology. In the absence of recorded infections and/or vaccination, a participant’s status was established based on baseline serology results for anti-RBD and anti-N, while the dates of events (infection or vaccination) and the number of doses were specified as stated in the MCPHP baseline questionnaire.

A previously recorded SARS-CoV-2 infection was defined as one or several positive RT-PCR or antigenic rapid diagnostic test results within 60 days, with the date of infection defined as the date of the first positive test. Multiple infections were identified as 2 positive test results >60 days apart. The time since the last infection was defined as the number of days since the last known infection date. Participants vaccinated on the day of their sample collection were considered to have their previous vaccination status (eg, 2 vaccine doses if sampled on the day of their third vaccine dose ). Finally, we defined a participant’s exposure status as the combination of the number of documented vaccine doses they had received at baseline (V0, V1, V2, or V3 for 0, 1, 2, or 3 doses) and a documented past infection (uninfected or infected), yielding 8 categories (uninfected V0, infected V0, etc).

Statistical Analysis

We carried out this analysis at the inclusion visit in the MCPHP for all eligible children and adult participants. We analyzed nAb levels since vaccination and/or infection, overall and by age. Participants’ baseline characteristics were analyzed according to vaccine and infection status. Descriptive statistics for continuous variables with normal distribution used means and standard deviations, with medians and interquartile ranges (IQRs) used for nonnormally distributed continuous variables. Comparisons between groups used t-tests for normally distributed variables, Mann-Whitney tests for nonnormally distributed variables, and χ 2 tests for categorical variables.

When representing smoothed lines for the relationship between nAb levels and time since the last vaccination, we excluded participants with over 24 months since the last vaccination compared with those of the same vaccination and infection status. Participants with a time since the last vaccination longer than the mean time +2 standard deviations or above the 99th percentile were excluded, corresponding, respectively, to 51 uninfected V2, 3 uninfected V3, 8 infected V1, 9 infected V2, and 1 infected V3 participants.

Data analyses were performed with Stata software (version 17; StataCorp), and R software (version 4.1.1; R Foundation for Statistical Computing). We used a generalized additive model (R software; mgcv package) to estimate the effects of covariates on nAb levels on vaccinated participants corresponding to the main groups—uninfected V2 and V3 as well as infected V1, V2, and V3— after excluding participants with 24 months since last vaccination, as detailed above.

nAb values were log-transformed to compose variables that are not normally distributed. Based on known factors associated with SARS-CoV-2 immunity levels, we included the following variables in the multivariate model: age, sex, vaccination status (number of vaccine doses received), time since last vaccine dose (in days or months), and body mass index (BMI) category (underweight, <18.5 [calculated as weight in kilograms divided by height in meters squared]; normal, 18.5–24.9; 25– overweight, 29.9; obese, >30 obese; and a “missing” category to accommodate multiple missing observations) [15, 34]. We evaluated interactions between vaccination and age, as well as vaccination and time since the last dose. We stratified the multivariate analysis and produced one model for noninfected participants and one for infected participants.

For infected participants, we included a categorical variable for time since the last infection, divided it according to quartiles, and included an “unknown” category without a date of infection. When necessary, we used thin-plate splines to estimate the effects of continuous variables (age, time since last vaccine dose, week) without assuming a linear relationship with the outcome. Where possible, we restricted the analysis to a shorter period allowing the estimation of a linear decreasing trend of antibodies over time. Owing to log transformation, the model estimates were exponentiated to obtain nAb value ratios (ie, nAb value if factor present/nAb value if factor absent).

In this analysis, we deliberately analyzed the evolution of nAb values of infected participants since their last standardized exposure to antigens through vaccination. This did not account for the possibility that participants could have been infected during the interval between their last vaccine dose and baseline visit, which could act as a natural booster. We conducted a sensitivity analysis of infected participants according to the duration since their last contact with antigens. We used similar sets of covariates and models and conducted a stratified analysis according to the type of last known exposure to SARS-CoV-2 antigens, either from an infection or from a vaccination (Supplementary Figures 3–9 and Supplementary Tables 5–9).

RESULTS

Between 1 July 2021 and 30 June 2022, a total of 8080 children and adults were enrolled in the MCPHP, of whom 543 (6.7%) were excluded from the analysis (Figure 1). The baseline characteristics of participants analyzed in the MonaVacc study are summarized in Supplementary Table 2. In brief, the median age (IQR) of the 7537 analyzed participants was 62 ( 50–74) years; 4174 participants (55.4%) were female. The median (IQR) time to the first serological visit at enrollment was 204 (120–312) days since the SARS-CoV-2 infection and 194 (152–229) days since the last vaccine dose.

Vaccinated Uninfected

Among the 5673 vaccinated uninfected participants, the median (IQR) nAb level was 33.8 (13.3–146) IU/mL after the first dose (V1), rising to 157.6 (43.3–439.1) IU/mL after the second dose (V2) and 882.5 (820.5–914.8) IU/mL after the third dose (V3) (Figure 2). nAb levels were lower for V2 participants who had longer durations since the last dose, while no clear trend appeared for V3 participants (Figure 3). For all categories, the number of participants with the longest follow-ups (ie, >250 days) was low, leading to more imprecision. In addition, older participants seemed to reach lower maximal nAb values immediately after vaccination, leading to constantly lower nAb levels over time (Supplementary Figure 1).

In the multivariate analysis, uninfected V3 participants had >4-fold higher antibody levels than uninfected V2 participants (adjusted nAb ratio, 4.39 [95% confidence interval (CI), 3.56– 5.42]; P < .001), as indicated in Table 1. In V2 participants, nAb levels were 20% lower per additional month elapsed since the last vaccination (adjusted nAb ratio per additional month, 0.80 [95% CI, .79–.82]; P < .001), suggesting waning immunity in the absence of stimulation. For V3 participants, the time since the last vaccination was not associated with significantly lower nAb levels over six months (observed from day 1 to day 200 only; adjusted nAb ratio per additional month, 0.98 [95% CI, .92– 1.05]; P = .56).

In uninfected V2 participants, increasing age was associated with lower nAb levels, with a steeper decrease per year in participants aged >67 years compared with younger participants (Figure 4A). The effect of age was more limited among V3 participants, with nAb levels decreasing only for those aged 60–80 years (Figure 4B). Among V3 participants, we found large heterogeneity in nAb levels among older participants (Supplementary Figure 2). Compared with the normal BMI group, having a lower BMI (<18.5) was associated with 18% lower nAb levels (adjusted nAb ratio, 0.82 [95% CI, .70–.95]) and obesity (BMI >30) with 10% lower nAb levels (0.90 [.81– 1.01]), while no significant difference was found in the overweight group (Table 1). Finally, female participants had higher nAb values than male participants (adjusted nAb ratio, 1.49 [95% CI, 1.39–1.58]).

Vaccinated Infected

In participants with previous SARS-CoV-2 infection, nAb levels appeared more stable and homogenous, irrespective of the number of vaccine doses (Figure 2) or the time between the last vaccine and nAb measurement (Figure 3). In detail, the median nAb (IQR) was 892.4 (799.7–931.9) IU/mL after the first dose, 904 (848.0–935.1) IU/mL after the second, and 891.5 (866.5–915.3) IU/mL after the third. A sustained nAb titer was also observed when we considered age categories separately (Supplementary Figure 1). Overall, the multivariate model showed a poor ability to explain these limited differences among infected participants (Table 1). Previously infected V1 participants had 16% lower nAb levels (adjusted nAb ratio, 0.84 [95% CI, .73–.95]) compared with V2 participants, and no significant difference was observed for V3 participants (1.13 [.92–1.39]). The time since the last infection was associated with lower levels for participants with unknown dates (possibly the longest in the absence of recorded RT-PCR or antigenic rapid diagnostic test). The time since the last vaccination did not significantly affect nAb levels among V2 or V3 participants (P = .92 and P = .73, respectively), and the effect was marginal for V1 participants, with levels increasing from the day of vaccination to month 2 (P = .048). Sex was not associated with nAb levels, and neither was BMI (Table 1). Age was associated only with a marginal nAb decrease in participants aged >75 years (Figure 4F).

In the sensitivity analysis, we considered the time since the last exposure for infected participants, and their last known antigenic exposure type (ie, SARS-CoV-2 infection or vaccine). In either group, >75% of participants showed nAb levels >800 IU/mL (Supplementary Figures 3–9 and Supplementary Tables 5–9). Only V1 participants last exposed to infection had lower nAb levels, as confirmed in the multivariate regression. V2 participants last exposed to an infection presented with a limited decrease over time since last exposure (−6% per month). Overall, nAb levels were high and stable over time since the last exposure in infected participants, irrespective of the last exposure type.

DISCUSSION

Based on a real-world observational setting, we quantified nAb levels in a large proportion of the national population, including SARS-CoV-2–vaccinated and/or SARS-CoV-2–infected children and adults, 2 years after the beginning of the pandemic. A SARS-CoV-2 infection combined with ≥1 vaccine dose provided the highest and most stable nAb level, over 12 months. By contrast, vaccinated uninfected V2 participants showed a nAb decline early in the first weeks after vaccination. This finding is coherent with a >3.5 million-individual cohort in Sweden, showing that hybrid immunity (ie, both infection and vaccination) provides the highest degree of protection against SARS-CoV-2 reinfection and COVID-19 hospitalization [34]. We further analyzed our findings by considering the type of last antigenic exposure (ie, SARS-CoV-2 infection or vaccine dose). Consistent with the main analysis, the sensitivity analysis showed that most infected participants had high nAb levels, stable over time since the last exposure, irrespective of the exposure type. Limited differences were observed in some subgroups, which warrants caution owing to small sample sizes. If not artifactual, these differences could reflect different immune stimulations from infection exposures or different immune backgrounds.

Consistent with the literature, age was confirmed to affect humoral response in our cohort [16, 35]. Elderly vaccinated uninfected participants consistently had the lowest nAb levels, further characterized by increasing heterogeneity. This highlights the importance of both booster vaccines and nonpharmaceutical protective measures in this age group. On the contrary, humoral response remained stable among participants with previous SARS-CoV-2 infection, including the elderly population. Similar to age, sex had a significant impact on uninfected participants: female participants had higher nAb levels than male participants after vaccination, consistent with previous observations [36]. Whether these differences are due to a combination of genetic, hormonal, and environmental factors remains unclear, but implications for SARS-CoV-2 vaccine dosage may be important about the greater occurrence of adverse effects among female vaccine recipients [37]. In contrast, we did not observe any difference between male and female participants with previous SARS-CoV-2 infection. Likewise, after adjustment for all other factors, BMI affected nAb levels only in vaccinated uninfected participants and not in those with previous SARS-CoV-2 infection. All of this evidence indicates the utility of serology as a tool to guide (re)vaccination and promote evidence-based booster recommendations.

By providing individualized information on nAbs, the MCPHP may allow a tailored vaccination scheme. With new variants modifying the nAb response and escaping traditional vaccine targets, generalizing future boosters to a whole set of so-called high-risk groups (usually owing to age or comorbid conditions) may be politically challenging [38]. In contrast, individualized information on protection levels may encourage population adherence to vaccine campaigns.

Several comments should be made regarding our observational, cross-sectional analysis of the MonaVacc cohort. First, our findings originate from Monaco, a small, densely populated country neighboring France and Italy. Its demographic features and overall health system are typical of Western European countries, including the large-scale use of RNA-based COVID-19 vaccines. Results are therefore relevant for Western, high-income countries with aging populations. Second, there was an imbalanced distribution among vaccine groups, especially for nonstandard vaccine regimens. Thus, the uninfected V1 and infected V3 participants were small samples, while most uninfected V3 participants were older with many observations within 50 days of V3 or over six months after vaccination, by local public health recommendations. Children <10 years of age were few and none were vaccinated. In consequence, the conclusions obtained are not as strong as for the larger and more homogenous groups, such as uninfected V2 or infected V1 participants. Similarly, there were few uninfected V3 participants with high BMI, indicating that the impact of BMI was driven mainly by V2 participants.

We included most participants with routinely recorded vaccinations and infections. In the absence of records, a limited number of participants were included based on whether their antibody detection results matched the profile (eg, positive anti-RBD and anti-N results for infected or positive anti-RBD and negative anti-N results for vaccinated uninfected participants). We did not assess SARS-CoV-2 T-cell response, though it is an essential pillar of acquired immunity. Our analysis did not focus on a potential nAb threshold protecting against the occurrence of infection. By reporting nAb levels using WHO international units as published in 2022, our data may be compared with data from other settings, to identify such protective thresholds [33, 39]. It has to be stressed that nAb levels represent an acknowledged indicator of severe disease protection, with a demonstrated association between these levels and severe COVID-19 outcomes [13]. Furthermore, measured nAb levels corresponded to those produced by the BNT162b2 vaccine, while other studies have found a lower yet persistent neutralizing activity against Omicron subvariants [40–42]. Finally, given evidence of limited cross-immunization and humoral response to Omicron subvariants, objectivizing immunization by measuring nAb levels alongside repeated vaccination campaigns is warranted [43–45].

In conclusion, in this nationwide cross-sectional study, we performed a large and long-term evaluation of nAb levels after SARS-CoV-2 vaccination and/or infection. While the combination of SARS-CoV-2 infection and vaccination offered the highest and most sustained nAb levels, V2 vaccination alone led to heterogeneous and waning humoral response following the first weeks after vaccination, especially among elderly participants. Public health policies should maintain their efforts to keep a high level of immunization against SARS-CoV-2 and should consider the utility of nAb measurements to document the need for vaccine boosters, thus improving individual compliance with public health recommendations.

Supplementary Data

Supplementary materials are available in The Journal of Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.

Notes

Acknowledgments. We would like to sincerely thank all Monaco residents who participated in the MCPHP; the Ministers of Social Affairs & Health Didier Gamerdinger and Christophe Robino; the laboratory technicians of the Monaco Scientific Centre Eva Jacquesson and Guillaume Groshenry; Bertrand Vanzo, Alexa Troël, Vincent Trevigny, and AnneCécile Turek for the Monaco dataset management; the president of the Global Virus Network Christian Bréchot, the head of the Health Department Alexandre Bordero for his constant support; and all the nurses and secretaries implementing the MCPHP at the community center Auditorium Rainier III.

Author contributions.

T. A. and E. V. had the idea for the study and contributed to the study design. T. A., J. L., H. R., A. C., S. X., L. F. W., and E. V. contributed to the epidemiological investigation and data collection. T. A., J. L., F. Z., G. M., and L. F. W. contributed to the analysis and interpretation of epidemiological data. T. A. and J. L. wrote the report, and F. Z., H. R., O. D., C. L., P. R., G. M., S. X., L. F. W., and E. V. contributed to critical revision.

Financial support.

The work was supported by the Monaco government (funding the MCPHP) and the National Research Foundation Singapore (grants STPRG-FY19-001, COVID19RF-003, COVID19RF-060, and OFLCG19May-0034 to F. Z. and L. F. W. [Duke-NUS Medical School]).

Potential conflicts of interest.

All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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