COVID-19 Vaccination and Serological Profile of a Brazilian University Population

Abstract

Background:
COVID-19 led to the suspension academic activities worldwide, affecting millions of students and staff.

Methods:
In this study, we evaluated the presence of IgM and IgG anti-SARS-CoV-2 antibodies in an academic population during the return to classes after a one-year suspension. The study took place over five months at a Brazilian university and included 942 participants.

Results:
We found that most participants had reactive IgG and non-reactive IgM. All received at least one dose, and 940 received two or more doses, of different COVID-19 vaccines. We obtained a higher average of memory antibodies (IgG) in participants who received the CoronaVac/ChAdOx1 combination. IgG was consistently distributed for each vaccine group, but individuals who completed the vaccination schedule had higher levels. There were no differences between antibodies and gender, presence of symptoms, and previous COVID-19 infection, but older participants (>53 years) and contacts of infected individuals had higher IgM levels.

Conclusion:
This study makes significant contributions to the assessment of antibodies in the academic environment, allowing us to infer that most participants had memory immunity and low indications of recent infection when returning to face-to-face classes, as well as demonstrating the need to monitor immunity and update vaccinations.

Full text

Life 2023, 13, 1925. https://doi.org/10.3390/life13091925 www.mdpi.com/journal/life
Article
COVID-19 Vaccination and Serological Profile of a Brazilian
University Population
Marina dos Santos Barreto
1
, Beatriz Soares da Silva
1
, Ronaldy Santana Santos
1
,
Deise Maria Rego Rodrigues Silva
1
, Eloia Emanuelly Dias Silva
1
, Pedro Henrique Macedo Moura
1
,
Jessiane Bispo de Souza
1
, Lucas Alves da Mota Santana
2
, Dennyson Leandro M. Fonseca
3
,
Igor Salerno Filgueiras
4
, Adriana Gibara Guimarães
1
, Otavio Cabral-Marques
3,4,5,6,7,8,9,
*
,†
,
Lena F. Schimke
4,5,
*
,†
and Lysandro Pinto Borges
1,
*
,†
1
Department of Pharmacy, Federal University of Sergipe, São Cristóvão 49100-000, SE, Brazil;
sbarretomarina@outlook.com (M.d.S.B.); biaisas@hotmail.com (B.S.d.S.); ronaldyss19@gmail.com (R.S.S.);
deisemaria588@gmail.com (D.M.R.R.S.); eloiaemanuelly@gmail.com (E.E.D.S.);
phmm694@gmail.com (P.H.M.M.); jeisse.nik@hotmail.com (J.B.d.S.);
adrianagibara@academico.ufs.br (A.G.G.); lysandro.borges@gmail.com (L.P.B.)
2
Graduate Program in Dentistry, Federal University of Sergipe, São Cristóvão 49100-000, SE, Brazil;
lucassantana.pat@gmail.com (L.A.d.M.S.)
3
Interunit Postgraduate Program on Bioinformatics, Institute of Mathematics and Statistics (IME),
University of São Paulo (USP), Sao Paulo 05508-090, SP, Brazil; dennyson@usp.br
4
Department of Immunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000,
SP, Brazil; igor.filgueiras@usp.br (I.S.F.); schimkelena@gmail.com (L.F.S.)
5
Department of Medicine, Division of Molecular Medicine, School of Medicine, University of São Paulo,
São Paulo 01246-903, SP, Brazil; otavio.cmarques@usp.br (O.C.-M.); schimkelena@gmail.com (L.F.S.)
6
Department of Pharmacy and Postgraduate Program of Health and Science,
Federal University of Rio Grande do Norte, Natal 59012-570, RN, Brazil; otavio.cmarques@usp.br (O.C.-M.)
7
Laboratory of Medical Investigation 29, University of São Paulo School of Medicine, São Paulo 01246-903,
SP, Brazil; otavio.cmarques@usp.br (O.C.-M.)
8
Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São
Paulo, São Paulo 05508-000, SP, Brazil; otavio.cmarques@usp.br (O.C.-M.)
9
Network of Immunity in Infection, Malignancy, Autoimmunity (NIIMA), Universal Scientific Education and
Research Network (USERN), São Paulo 05508-000, SP, Brazil; otavio.cmarques@usp.br (O.C.-M.)
* Correspondence: otavio.cmarques@usp.br (O.C.-M.); schimkelena@gmail.com (L.F.S.);
lysandro.borges@gmail.com (L.P.B.)
† Contributed equally.
Abstract: Background: COVID-19 led to the suspension academic activities worldwide, affecting
millions of students and staff. Methods: In this study, we evaluated the presence of IgM and IgG
anti-SARS-CoV-2 antibodies in an academic population during the return to classes after a one-year
suspension. The study took place over five months at a Brazilian university and included 942
participants. Results: We found that most participants had reactive IgG and non-reactive IgM. All
received at least one dose, and 940 received two or more doses, of different COVID-19 vaccines. We
obtained a higher average of memory antibodies (IgG) in participants who received the
CoronaVac/ChAdOx1 combination. IgG was consistently distributed for each vaccine group, but
individuals who completed the vaccination schedule had higher levels. There were no differences
between antibodies and gender, presence of symptoms, and previous COVID-19 infection, but older
participants (>53 years) and contacts of infected individuals had higher IgM levels. Conclusion: This
study makes significant contributions to the assessment of antibodies in the academic environment,
allowing us to infer that most participants had memory immunity and low indications of recent
infection when returning to face-to-face classes, as well as demonstrating the need to monitor
immunity and update vaccinations.
Citation: Barreto, M.d.S.;
Silva, B.S.d.; Santos, R.S.;
Silva, D.M.R.R.; Silva, E.E.D.;
Moura, P.H.M.; Souza, J.B.d.;
Santana, L.A.d.M.; Fonseca, D.L.M.;
Filgueiras, I.S.; et al. COVID-19
Vaccination and Serological Profile
of a Brazilian University Population.
Life 2023, 13, 1925. hps://doi.org/
10.3390/life13091925
Academic Editor: Yoshiyuki Suzuki
Received: 29 August 2023
Revised: 12 September 2023
Accepted: 14 September 2023
Published: 16 September 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Swierland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Aribution (CC BY) license
(hps://creativecommons.org/license
s/by/4.0/).

Life 2023, 13, 1925 2 of 14
Keywords: COVID-19; antibodies; universities; academic population; vaccines; Brazil
1. Introduction
The coronavirus disease (COVID)-19 pandemic spread rapidly worldwide after its
discovery in December 2019 [1]. The World Health Organization (WHO) recommended
several preventive measures since no effective treatment was approved for severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2) infection [2]. Among them were
hygiene of hands and environmental surfaces, social distancing, and using masks to
minimize viral spread [3,4]. In addition, several countries [5], including Brazil, suspended
in-person classes in schools and universities in March 2020 [6] when the government
declared a Public Health Emergency of National Importance (ESPIN) [7] and reported 291
cumulative cases and the first death confirmed by the Brazilian Ministry of Health [8].
University students generally do not present the severe form of the disease due to their
young age and low rate of comorbidities. However, they are highly socially active,
representing a critical population spreading the SARS-CoV-2 to older individuals in their
residences or other environments [9,10].
During the COVID-19 pandemic, more than 168 million students were affected by
the suspension of classes worldwide, and after eighteen months of the pandemic, this
number still exceeded 70 million [11]. The withdrawal of students from schools and
universities negatively impacted this population’s quality of life and learning
development [12–16]. Thus, one of the initiatives that made a safe return of academic
activities possible in the first half of 2022 [6] was the development of vaccines against
SARS-CoV-2 [17–19]. In Brazil, vaccines from Pfizer/BioNTech (BNT162b2),
Oxford/AstraZeneca (ChAdOx1), Janssen-Cilag (Ad26.COV2.S), and Sinovac
(CoronaVac) have been approved by the Brazilian Health Regulatory Agency (ANVISA)
and are available to the population [8]. Vaccines produced with mRNA technology, such
as BNT162b2, make the mRNA available for processing and antigen presentation [20].
ChAdOx1 and Ad26.COV2.S vaccines use a non-recombinant viral vector, which does not
have the gene responsible for the disease but can enter the host cells by causing the
immune system to recognize the remaining viral proteins [21]. Another technology is the
chemically or physically inactivated virus, used by CoronaVac, which promotes the
recognition of various virus proteins by the immune system without viral infection [22].
Notably, all these immunizers activate the immune response and stimulate antibody
production against SARS-CoV-2 from the presentation of the virus antigen [19,23].
Assessing the seroprevalence of anti-SARS-CoV-2 antibodies, either induced by
natural infection or by vaccination, during the return to in-person classes is essential for
evaluating disease epidemiology and vaccination effectiveness [3,24–27]. Therefore, here
we assessed the serum prevalence of anti-SARS-CoV-2 antibodies in 942 individuals
enrolled at the Federal University of Sergipe (UFS) in São Cristóvão, Brazil, which
registered more than 34,000 students, employees, and teachers at the time of the university
reopening in January 2022 [28]. The SARS-CoV-2 Omicron variant was prevalent at this
moment, and was responsible for Brazil’s third wave of COVID-19 [29].
2. Materials and Methods
2.1. Study Population and Sample Collection
The study was approved by the Research Ethics Commiee (CAAE
31018520.0.0000.5546). The inclusion criteria selected study participants without specific
underlying diseases, no comorbidities, and who were connected to the Federal University
of Sergipe as a student, faculty, or staff member when signing the informed consent. The
study included 942 (490 female and 452 male) volunteers between January and May 2022.
The Omicron variant of SARS-CoV-2 was the predominant variant in this period [29]. The

Life 2023, 13, 1925 3 of 14
age of the study participants ranged from 18 to 73 years, with a mean of 30.27 ± 11.38 (95%
CI 29.5–31.0). Figure 1 summarizes the workflow of this study. Briefly, a basic
questionnaire adapted from the notification forms for COVID-19 of the Brazilian Ministry
of Health [8] was applied to obtain gender, date of birth, symptoms of COVID-19 in the
last 15 days, recent contact with individuals with a positive COVID-19 diagnosis, and
vaccination status. Then, blood samples using gel separator tubes were obtained to
evaluate the serum levels of the anti-SARS-CoV-2 antibodies (described below).
Figure 1. Study workflow showing steps taken to collect serological samples, analyze the IgM and
IgG antibody levels, and release results for participants. Initially, we collected demographic data of
the participants from a questionnaire. Subsequently, participants were directed to blood puncture.
The collected samples were sent to centrifugation and further processed for laboratory analysis.
Following sample preparation and insertion into the cassee, samples were analyzed in the
ichroma™ COVID-19 device, which performed the reading and expression of the result obtained
for the COI value for IgM and IgG antibodies. The results were transmied to the patient online. Ig:
immunoglobulin, COI: Cut-off index.
2.2. Laboratory Analysis
To assess serum levels of anti-SARS-CoV-2 antibodies (Ab), we used the
immunofluorescence assays applying the ichroma™ COVID-19 Ab test following the
manufacturer’s recommendation, which uses a sandwich immunodetection methodology
(hps://www.boditech.co.kr/en/support/id/226 accessed on 09 November 2021) [30]. This
method has a sensitivity of 95.8% and a specificity greater than 97%, as reported by the
manufacturer [31]. This approach allows us to determine the immunoglobulin (Ig)G and
IgM levels against SARS-CoV-2. The results obtained were accessible for each participant
through a QRcode®.
2.3. Statistical Analysis and Data Visualization
We used IBM® SPSS® Statistics software (version 26.0 for Windows) [32] for data
analysis. The Mann–Whitney and Kruskal–Wallis independent sample tests were used to
differentiate antibody distribution between two or more groups. Percentages were
calculated. The device calculates the results of antibody levels, expressing them in an
auxiliary value, which is displayed as a cut-off index (COI) for IgM and IgG. Values equal
to or greater than 1.1 are classified as reactive, and values less than 1.1 as non-reactive.
According to the manufacturer’s package insert, values between 0.9 and 1.1 are considered
indeterminate. A p-value of <0.05 was considered statistically significant. Spearman’s
Correlation test was performed for correlation of quantitative variables, with “*” = p < 0.05,

Life 2023, 13, 1925 4 of 14
“**” = p < 0.01. Graphs were visualized using jamovi
®
(version 2.3.28 for Windows) [33] to
analyze the distribution of IgG antibodies in each vaccine group and GraphPad Prism
®
(version 9.5.1 (733) Windows) [34] to investigate the dispersion of IgM and IgG antibodies
in individuals who have or have not had contact with someone infected, symptomatic and
asymptomatic, and in those who had previous COVID-19 and those who never had. The
online web tool Circos
®
plot (hp://circos.ca/ accessed on 17 June 2022) [35] was used to
correlate the total number of participants with the number of individuals for each vaccine
group.
3. Results
We obtained an average mean of 23.84 ± 7.64 COI (95% CI 23.4–24.3; p < 0.01) for the
IgG antibody and 0.74 ± 1.40 COI (95% CI 0.65–0.83, p < 0.01) for IgM. Seven hundred fifty-
seven individuals (80.4% of the total number of participants) presented results below 1.1
COI for IgM, and only six (0.6%) showed non-reactive IgG levels (below 1.1 COI). In con-
trast, 99.4% showed reactive IgG levels. Three (0.23%) individuals had non-reactive results
for both types of antibodies (Supplementary Table S1). This result indicates that most of
the study population presents reactive results for anti-SARS-CoV-2 IgG antibodies. How-
ever, only a small number of participants expressed reactive results for IgM.
Evaluating the kind of vaccination received by each individual, we obtained ten dif-
ferent vaccine combinations of four different vaccination types (BNT162b2, ChAdOx1,
Ad26.COV2.S, and CoronaVac) offered in the Brazilian territory (Supplementary Table
S2). As shown in Figure 2, the five groups of vaccines received most by the participants
were BNT162b2 (A) (n = 400), BNT162b2/ChAdOx1 (AB) (n = 226), ChAdOx1 (B) (n = 116),
CoronaVac/BNT162b2 (BC) (n = 78), and BNT162b2/Ad26.COV2.S (AD) (n = 49). Combi-
nations with the Ad26.COV2.S vaccine was less present in this study group, probably be-
cause this vaccine was the least used in the Brazilian population [8] (Figure 2).
Figure 2. Distribution of the number of participants according to vaccine or vaccination combination
group. The graph shows the total number of individuals (n = 942) and the distribution according to
each vaccine and vaccine combinations applied to the study population. Aside from the Circos
®,
the

Life 2023, 13, 1925 5 of 14
figure legend denotes the vaccines and their respective combinations by leers and different ribbon
colors.
We performed the independent samples Kruskal–Wallis test to assess whether vac-
cine groups affect the distribution of participants’ IgG antibodies. We determined that the
distribution of IgG antibodies is different (p = 0.004) across the vaccination groups. Figure
3a shows the distribution of IgG levels in each vaccine group. A higher mean was obtained
for the ChAdOx1/CoronaVac (BC) combination (m = 27.43 ± 12.19), followed by
BNT162b2/CoronaVac (AC) (m = 25.37 ± 7.98). BNT162b2 (A) presented a higher average
(m = 24.66 ± 6.41) in the homologous vaccine groups, followed by Ad26.COV2.S (D) (m =
24.16 ± 9.13), CoronaVac (C) (m = 23.76 ± 12.01), and ChAdOx1 (B) (m = 22.71 ± 8.87) vac-
cine. The other combinations reached a lower average, as shown in Figure 3b and Supple-
mentary Table S2. The BNT162b2 (A) vaccine showed a concentrated result at higher IgG
levels. In contrast, other vaccines, such as ChAdOx1 (B), CoronaVac (C), and the combi-
nation of the two, showed a more expanded distribution for the antibody, including shal-
low levels (Figure 3b). It can also be seen that the same group of vaccines generated varied
individual responses, contributing to the vast difference in antibody level distribution.
a
b

Life 2023, 13, 1925 6 of 14
Figure 3. Distribution and means of anti-SARS-CoV-2 IgG antibodies in the different vaccine groups.
(a) Boxplots show the distribution of IgG values for each vaccine group. Blue boxes indicate the
normal distribution of the antibody, with the mean (m) flagged in the middle of each box. The black
dots represent the outliers, considered abnormal values that deviate from the normal distribution.
(b) The histograms indicate the antibody level distribution (wave line) and antibody level concen-
tration peaks (colored bars) in each vaccine group. The larger bars indicate that more individuals
present the indicated mean value (concentration peak), while smaller bars correspond to fewer in-
dividuals with this mean antibody level. Ig: immunoglobulin. The vaccine groups are indicated by
leers and different colors, with A = BNT162b2 (m = 24.66 ± 6.41), B = ChadOx1 (m = 22.71 ± 8.87), C
= CoronaVac (m = 23.76 ± 12.01) D = Ad26.COV2.S (m = 24.16 ± 9.13), AB = BNT162b2 and ChadOx1
(m = 22.68 ± 7. 44), AC = BNT162b2 and CoronaVac (m = 25.37 ± 7.98), AD = BNT162b2 and
Ad26.COV2.S (m = 22.40 ± 6.63), CB = ChadOx1 and CoronaVac (m = 27.43 ± 12.19), CD = CoronaVac
and Ad26.COV2. S (m = 22.20 ± 5.03), and DB = Ad26.COV2.S and ChadOx1 (m = 20.70 ± 9.21).
All study participants had used at least one dose of any of the four COVID-19 vac-
cines. Figure 4 shows the IgM and IgG antibodies distribution for each vaccine dose. Only
two participants had not updated their vaccination schedule, leaving them with only one
dose administered. The remaining participants received either up to the second vaccina-
tion dose (completed the vaccination schedule; two doses group) or had updated the vac-
cination schedule for the booster dose (third dose of the vaccine, reinforcing the vaccina-
tion schedule; booster dose group). The average antibody level for the one-dose individ-
uals (n = 2) was 1.00 ± 0.42 for IgM and 17.3 ± 3.54 for IgG. The two-dose group (n = 429)
and the booster dose group (n = 511) showed an average antibody level of 0.59 ± 1.10 and
0.74 ± 1.40 for IgM and 24.41 ± 8.17 and 23.39 ± 7.15 for IgG, respectively. Using the Krus-
kal–Wallis test of independent samples, we evaluated the distribution of IgM and IgG per
different vaccine doses applied to the participants. We discovered that the distribution of
IgM was the same (p = 0.092), and that IgG antibody levels were distributed differently
according to the number of doses (p = 0.031). However, the significant difference in sample
size between the one-dose group and the two- or booster-dose group may impact this
result. Despite this, Figure 4 shows that the distribution of both antibodies is similar in
individuals who received two or three vaccine doses. Spearman’s correlation indicates
that the number of doses applied increases with age (r = 0.276 **, p < 0.01). In this regard,
it is worth mentioning that the vaccination schedule in Brazil occurred by age group, with
older people having priority over younger people [8].

Life 2023, 13, 1925 7 of 14
Figure 4. Distribution of IgM and IgG anti-SARS-CoV-2 antibodies in different COVID-19 vaccine
dose groups. The scaer plot shows the distribution of IgM and IgG for individuals who used only
one vaccine dose (n = 2), two doses (n = 429), and the booster dose (n = 511). The densities, displayed
at the top and right side, help visualize the antibodies’ distribution in the three groups analyzed. Ig:
immunoglobulin.
The Kruskal–Wallis test was performed to evaluate the difference in IgG antibody
distribution during the months of the study. The analysis points out that the IgG antibod-
ies were distributed differently among the five consecutive months of the study (p = 0.001),
decreasing their levels progressively during the five months of the study (January to May)
(Table 1). It is essential to note that the face-to-face classes returned in January, and in
May, the UFS entered the vacation period. This may explain the low adherence to sero-
logical testing in this month compared to the other months of the study. Also, it is worth
mentioning that the first booster dose was released in November 2021 for the public over
18 years of age and without comorbidity [36], which could have impacted higher IgG lev-
els measured at the beginning of our study in 2022.
Table 1. Distribution of antibody serological mean for anti-SARS-CoV-2 IgM and IgG antibodies
during the five months of data acquisition of this study (January to May 2022). The antibody means
are divided by sex groups and month of sample acquisition, showing a slight variation in low IgM
levels throughout the study but high IgG levels at the beginning with a tendency to decrease as the
months of the study pass. Ig: immunoglobulin, CI: Confidence interval
Antibodies Serological Mean (COI)
Month (n) Sex (n) IgM CI 95% p
January (29) Female (14) 0.40 ± 0.62 0.04–0.76 0.030
Male (15) 0.69 ± 1.25 0.00–1.38 0.049
February (448) Female (232) 0.89 ± 1.38 0.71–1.07 0.001
Male (216) 0.75 ± 1.51 0.55–0.96 0.001
March (279) Female (151) 0.57 ± 0.99 0.41–0.73 0.001
Male (128) 0.84 ± 1.84 0.52–1.16 0.001
April (161) Female (86) 0.71 ± 1.30 0.44–1.00 0.001
Male (75) 0.54 ± 1.26 0.25–0.83 0.001
May (25) Female (7) 0.53 ± 0.55 0.02–1.04 0.045
Male (18) 0.60 ± 1.28 −0.04–1.24 0.064
Sex (n) IgG CI 95% p
January (29) Female (14) 27.27 ± 4.17 24.86–29.68 0.001
Male (15) 26.21 ± 7.97 21.80–30.63 0.001
February (448) Female (232) 24.0 ± 8.68 22.92–25.17 0.001
Male (216) 24.64 ± 8.25 26.53–25.74 0.001
March (279) Female (151) 24.07 ± 5.22 23.23–24.91 0.001
Male (128) 23.04 ± 6.99 21.82–24.27 0.001
April (161) Female (86) 23.10 ± 7.68 21.46–24.75 0.001
Male (75) 22.71 ± 6.95 21.11–24.31 0.001
May (25) Female (7) 20.81 ± 7.45 13.92–27.71 0.001
Male (18) 20.21 ± 9.93 15.27–25.15 0.001
Regarding the distribution of antibodies according to sex, the Mann–Whitney test
indicates that IgM is distributed differently for females and males (p = 0.001), while IgG is

Life 2023, 13, 1925 8 of 14
equally distributed by sex (p = 0.839). However, this difference concerning the mean is not
significant, as the total mean IgM levels for females (m = 0.74 ± 1.24) and males (m = 0.73 ±
1.55) are very similar, as is IgG (m = 23.93 ± 7.48 for females and m = 23.74 ± 7.82 for males).
Table 1 shows the distribution of IgM and IgG antibodies by sex in each month of the
study, with similar values between these antibody averages. Spearman’s correlation
showed significant correlations between age and IgM (r = 0.149 ** and p < 0.01) and IgG (r
= −0.116 ** and p > 0.01) (Supplementary Table S3), whereas younger individuals tended
to have higher titers for IgG. Table 2 shows the averages of IgM and IgG antibodies in age
groups, indicating the increase in IgM in older age groups and the increase in IgG in
younger groups.
Table 2. Distribution of means for IgM and IgG antibodies according to different age groups. The
table shows the variation of the means of the antibody levels for each age group, with IgM levels
tending to increase with age and IgG levels higher in younger groups. Ig: immunoglobulin, CI: Con-
fidence interval.
Age Group n Antibody Mean (SD) 95% CI p
18–23 Years 373 IgM 0.54 ± 1.13 0.43–0.66 0.001
IgG 24.51 ± 7.69 23.73–25.30 0.001
24–29 Years 216 IgM 0.54 ± 0.95 0.42–0.67 0.001
IgG 24.51 ± 6.78 23.60–25.42 0.001
30–35 Years 86 IgM 0.83 ± 1.12 0.59–1.08 0.001
IgG 22.50 ± 7.75 20.84–24.16 0.001
36–41 Years 88 IgM 1.26 ± 1.92 0.85–1.67 0.001
IgG 23.15 ± 8.00 21.46–24.85 0.001
42–47 Years 70 IgM 0.68 ± 1.11 0.42–0.94 0.001
IgG 23.69 ± 7.18 21.98–25.41 0.001
48–53 Years 54 IgM 1.17 ± 1.81 0.67–1.66 0.001
IgG 23.49 ± 7.42 21.46–25.51 0.001
>53 Years 55 IgM 1.50 ± 2.72 0.77–2.24 0.001
IgG 20.41 ± 9.45 17.85–22.96 0.001
When questioned about flu symptoms in the last 15 days, 182 (19.32%) participants
claimed to be symptomatic, and 760 (80.68%) were asymptomatic. Applying the Mann–
Whitney test, IgM and IgG were equally distributed in the asymptomatic group compared
to the symptomatic group (p = 0.057 and p = 0.059, respectively) (Figure 5a). The mean IgM
for the symptomatic group is 0.95 ± 1.73, and for the asymptomatic group, 0.69 ± 1.30. The
mean IgG for the symptomatic groups is 23.00 ± 8.54 and for the asymptomatic group,
24.04 ± 7.40. However, we must emphasize that we did not perform additional diagnostic
tests for the presence of the SARS-CoV-2 virus by RT-PCR, so being asymptomatic or
symptomatic should not suggest the presence of active infection. In addition, 197 partici-
pants reported they had recent contact with someone diagnosed positive for COVID-19,
and the remaining 745 had no contact with someone infected. The mean IgM was statisti-
cally similar for those individuals with contact with someone positive for COVID-19 (0.80
± 1.39) and those individuals without contact (0.72 ± 1.40), as was the mean for IgG in these
respective groups (24.44 ± 8.58 and 23.68 ± 7.37, respectively. The Mann–Whitney test in-
dicated that there is only a difference in IgM antibody distribution (p = 0.022) but not in
IgG distribution (p = 0.371) regarding contact with COVID-19-positive individuals (Figure
5b).

Life 2023, 13, 1925 9 of 14
Regarding the history of diagnosis for SARS-CoV-2, more than half of the partici-
pants (n = 522) had never been positive for COVID-19, while the remaining (n = 420) had
already been diagnosed with COVID-19 at least once. The antibodies IgM (p = 0.957) and
IgG (p = 0.110) were equally distributed between the group with positive history of
COVID-19 (IgM mean of 0.80 ± 1.54, and IgG mean of 24.29 ± 7.85) and the group that had
never been infected (IgM mean of 0.66 ± 1.20, and IgG mean of 23.48 ± 7.46) (Figure 5c)
indicating that the antibody levels measured were not influenced by the combination of
natural with vaccine-induced immunity or vaccine-induced immunity alone.
a
b
c
Figure 5. Distribution of anti-SARS-CoV-2 IgM and IgG antibodies among individuals with COVID-
19 symptoms, recent contact, or previous natural SARS-CoV-2 infection. (a) The scaer plot shows
IgM and IgG antibody levels (COI) distribution between symptomatic and asymptomatic individu-
als for COVID-19 15 days before sample acquisition; (b) Distribution of IgM and IgG antibody levels
in individuals with recent contact with someone diagnosed with COVID-19 positive and those with-
out contact with COVID-19 individuals; (c) IgM and IgG antibody level distribution in individuals
who had ever been diagnosed with COVID-19 and those who reported having never been infected
with SARS-CoV-2. Ig: immunoglobulin.
4. Discussion
Brazil was one of the countries most affected by the COVID-19 pandemic in the num-
ber of deaths and cases [37]. To contain the impact of the virus, one of the measures
adopted was suspending face-to-face classes and moving to the remote model. In this

Life 2023, 13, 1925 10 of 14
scenario, millions of students carried out their academic activities from home until this
group obtained vaccines against COVID-19 and face-to-face classes could be resumed
more than a year after the suspension [6]. Seeking to evaluate the development of the im-
mune response of academics through antibodies, we assessed the prevalence of IgM and
IgG anti-SARS-CoV-2 antibodies in an academic population in the first five months of re-
turning to face-to-face classes. Our results suggest that, in general, study participants did
not have an acute or recent infection due to the low prevalence of reactive IgM antibodies.
However, the high presence of memory antibodies (IgG) against SARS-CoV-2 shows that
they had contact with the virus or parts of the virus, either by asymptomatic/mild natural
infection or by vaccination. In a previous study by our group conducted one month after
the reopening of schools in Sergipe and before vaccination campaigns had started, we
reported high virus circulation with few IgG-reactive individuals [38]. In contrast, in this
study, we observed a low indication of recent infection, and most participants had already
developed memory antibodies, bringing the importance of vaccination to this result.
All vaccines offered in the Brazilian territory and evaluated in this study proved sol-
idly effective in producing memory antibodies. The vaccine combination Coro-
naVac/ChAdOx1 (group BC in Figure 3) showed the highest mean for IgG. However,
63.6% (7/11) of the individuals who used this combination also reported natural infection,
which means that the higher IgG production may be linked to hybrid immunity. This type
of immunity results from the combination of infection-induced and vaccine-induced im-
munity and is associated with increased antibody production [39]. Nevertheless, our
study did not generally identify altered seroprevalence concerning vaccine-induced or
hybrid immunity or the type of vaccine combination applied. In addition, we did not eval-
uate the time interval between natural infection, vaccination, and testing time for this
study, which may influence the level and prevalence of antibodies subject to natural decay
[40]. In addition, Brazil was a country marked by underreporting and under-testing
COVID-19 cases due to limited capacities, which may impact this result.
The state Sergipe, where the study was conducted, released the booster dose of the
COVID-19 vaccine in the second half of November 2021 for the adult public [36]. When
we evaluated the number of vaccine doses and antibody levels, we found that individuals
who had only one dose of the vaccine had lower mean IgG levels than those with two
doses or a booster dose (third dose), but this may be affected by the significant difference
in sample size, where the distribution of participants with one dose is disproportionate to
those with two and three doses. Our results also show a trend of progressive decrease in
IgG antibody levels over the months, which has already been reported in some studies
with vaccinated individuals [40,41]. These findings reinforce the importance of updating
the vaccination schedule to maintain antibody levels.
We found no differences in the IgG antibody levels between women and men, cor-
roborating studies that found no differences between sex and IgG seroprevalence [42–47].
Despite showing a different distribution between the two groups, the mean IgM for males
and females is statistically similar. Not all vaccinated individuals seroconverted to IgG, as
found in other studies [48,49], and this may be linked to several extrinsic inter-individual
and intrinsic (e.g., genetic) factors interfering with the development of the immune re-
sponse [50].
Although some studies have found no relationship between age and seropositivity
[42–44,47,51], other studies corroborate our findings, suggesting that IgG is higher in
younger people [46,52–56]. The higher IgG levels in young people may be caused by hy-
brid immunity, as they are more socially active and at higher risk of infection, which often
remains asymptomatic [57]. Therefore, when vaccinated, they may generate a hybrid im-
mune response, which correlates with higher IgG levels [39]. Regarding the correlation
between higher levels of IgM and older individuals, a study in a population of blood do-
nors found the same result, aributing it to possible false positives and preferential sero-
conversion to IgM [53].

Life 2023, 13, 1925 11 of 14
This study has some limitations. The fact that not all samples were evaluated on the
same date but during a period of five months may cause slight experimental variation in
antibody results, as well as behavioral and sociocultural differences in participants. In ad-
dition, responses regarding the presence of symptoms, contact with someone infected
with SARS-CoV-2, and previous COVID-19 infection were recorded according to the par-
ticipant’s statement and are, therefore, subject to recall bias. In addition, the experimental
workflow of this study did not include diagnostic tests, such as RT-PCR, or neutralizing
antibodies and SARS-CoV-2-specific T cells, which would complement our results and
further evaluate the immune response to SARS-CoV-2.
In summary, we demonstrated that the academic population showed a significant
memory antibody response after vaccination and during the resumption of face-to-face
classes, and we did not detect a high prevalence of antibodies signaling active/recent in-
fection in participants. The association of anti-SARS-CoV-2 IgG antibodies with vaccina-
tion doses and combination groups did not highlight a more prominent immune response
for a specific vaccination. Still, it showed a tendency for higher IgG levels in participants
who received more than one vaccination dose. Therefore, besides offering a parameter of
seroprevalence in Brazilian universities post-vaccination and post-reopening of universi-
ties, our study suggests a possible necessity of vaccine application to establish a robust
anti-SARS-CoV-2 immune response. However, it is essential to remember that further re-
search is needed to fully understand the immune response and the efficacy of vaccination
in protecting against aggravation and death caused by COVID-19.
Supplementary Materials: The following supporting information can be downloaded at
hps://www.mdpi.com/article/10.3390/life13091925/s1, Table S1: Distribution of patients’ sociodem-
ographic and clinical (IgM and IgG COI) data, according to the questionnaire: gender, age, vaccines,
and doses received, presence of symptoms up to 15 days before sample acquisition, previous
COVID-19, and recent contact with someone positive. It also contains the month and date of sample
testing. Ig: immunoglobulin; COI: Cut-off index; Table S2: IgM and IgG (COI) results for each par-
ticipant grouped by vaccine or combination of vaccines received. Ig: immunoglobulin; COI: Cut-off
index; Table S3: Correlation matrix showing correlations between the number of vaccine doses re-
ceived, participants’ age, and IgM and IgG COI levels.
Author Contributions: Conceptualization, M.d.S.B., B.S.d.S. and L.P.B.; methodology, M.d.S.B.,
B.S.d.S., R.S.S., E.E.D.S., L.P.B., D.M.R.R.S., P.H.M.M. and J.B.d.S.; investigation, M.d.S.B., B.S.d.S.,
R.S.S., E.E.D.S., L.P.B., D.M.R.R.S., P.H.M.M. and J.B.d.S.; data curation, M.d.S.B., B.S.d.S., R.S.S.,
E.E.D.S., L.P.B., D.M.R.R.S., P.H.M.M. and J.B.d.S.; writing—original draft preparation, M.d.S.B.,
B.S.d.S. and L.P.B.; writing—review and editing, O.C.-M., L.P.B., L.F.S., D.L.M.F., I.S.F., L.A.d.M.S.
and A.G.G.; supervision, L.P.B. and O.C.-M.; project administration, L.P.B. All authors have read
and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: The study was conducted in accordance with the Declara-
tion of Helsinki, and approved by the Ethics Commiee of research in Brazil (Comite de etica em
pesquisa seres humanos; CEP platform) under the protocol code 31018520.0.0000.5546 at September
2020.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study.
Data Availability Statement: If you are interested in further data on the results, please contact the
corresponding author.
Acknowledgments and Funding: We thank the São Paulo State Research Support Foundation
(FAPESP grants: 2018/18886-9 to OCM, 2020/16246-2 to DLMF, and 2023/07806-2 to ISF). We
acknowledge the National Council for Scientific and Technological Development (CNPq), Brazil
(grants: 309482/2022-4 to OCM and 102430/2022-5 to LFS). We thank the Government of the State of
Sergipe as the State Health Department. Finally, we thank the MPT, MPE, and MPF.
Conflicts of Interest: The authors declare no conflicts of interest.

Life 2023, 13, 1925 12 of 14
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