COVID-19 cross-sectional study in Maricá, Brazil: The impact of vaccination coverage on viral incidence.

Population surveillance in COVID-19 Pandemic is crucial to follow up the pace of disease and its related immunological status. Here we present a cross-sectional study done in Maricá, a seaside town close to the city of Rio de Janeiro, Brazil. Three rounds of study sampling, enrolling a total of 1134 subjects, were performed during May to August 2021. Here we show that the number of individuals carrying detectable IgG antibodies and the neutralizing antibody (NAb) levels were greater in vaccinated groups compared to unvaccinated ones, highlighting the importance of vaccination to attain noticeable levels of populational immunity against SARS-CoV-2. Moreover, we found a decreased incidence of COVID-19 throughout the study, clearly correlated with the level of vaccinated individuals as well as the proportion of individuals with detectable levels of IgG anti-SARS-CoV-2 and NAb. The observed drop occurred even during the introduction of the Delta variant in Maricá, what suggests that the vaccination slowed down the widespread transmission of this variant. Overall, our data clearly support the use of vaccines to drop the incidence associated to SARS-CoV-2.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic reached the Latin America later than other continents [1, 2]. The first case recorded in Brazil dates back to February 25th, 2020 [3]. In October 2021, Brazil accounted for the most cases and deaths in Latin America (>21 million cases and >600.000 deaths) [4]. Rio de Janeiro State concentrates 1.31 million cases and 67,000 deaths by the beginning of 41st epidemiological week [5]. Case incidence experienced a substantial decrease after large scale vaccination campaigns [5-7]. In fact, COVID-19 vaccination campaign in Rio de Janeiro State reached 80% of target population with at least one dose and 60% of fully vaccinated individuals by October 14th, 2021 [5]. Until June 2021, Rio de Janeiro has experienced the circulation of three major variants in different time frames [8]. By the beginning of October 2020 there was the introduction of P2 (Zeta) variant of investigation (VOI), that was replaced by the beginning of 2021 by P1 (Gamma) variant of concern (VOC), which prevailed until June 2021 when Delta VOC arrived and dominated until beginning of 2022 [8].

The introduction of COVID vaccines in early 2021 has impacted the incidence of COVID-19 as well as the hospitalization and death associated with SARS-CoV-2 infections in different cohort studies [9-11]. Concurrently, The National Plan of COVID-19 Immunization in Brazil employed four vaccines on its strategy [6, 12]. The Brazilian campaigns first begun with the utilization of CoronaVac in January 2021, followed by AstraZeneca in February 2021 [6, 12]. On April 2021 Pfizer was included and for the last, Janssen was incorporated to the campaign strategies in June 2021 [6, 12].

Population-based data on COVID-19 are essential for guiding policies and evaluating public health interventions made in different cities [13-16]. However, there are few such studies, particularly from low or middle-income countries [15, 17]. Then, our aim is to investigate SARS-CoV-2 antibody (anti-SCOV2) prevalence and RT-PCR status in Maricá, a seaside town close to the city of Rio de Janeiro, Brazil. Maricá is located 60Km from the city of Rio de Janeiro and has a total population of 161,000 habitants. Since the beginning of COVID-19 pandemic, Maricá accounted for 18,657 cases and 584 deaths (mortality rate of 2.782/100,000 inhabitants) [7]. In this study, we disclose the results of three repeated cross-sectional COVID-19 seroprevalence and incidence surveillances from May to August 2021. For each round, samples from 384 individuals were randomly selected. Nasopharyngeal swabs and blood sera were collected to run RT-PCR targeting SARS-CoV-2 N gene and COVID-19 serology measurements such as neutralizing antibodies titles, respectively.

Material and methods

Sampling strategy

From May, 24th to August, 5th a multi-stage probabilistic sampling was adopted, with 39 census tracts selected with probability proportionate to size in each sentinel cross-sectional study, and ten households at random in each tract. In order to select each census tracts maps and household listings made available by the Brazilian Institute of Geography and Statistics was utilized [18]. One individual was randomly selected from a listing of all household members. Subjects below 18 years old and those with mental disability or special needs were excluded. If the randomly selected person refused to provide sample or could not be found, the interviewers moved on to the next household on the right.

A questionnaire was applied to capture socio demographic and clinical data from all enrolled individuals. In addition, nasopharyngeal swab samples and 10mL of whole blood were collected by venipuncture to perform RT-PCR (swabs) and ELISA and serum neutralization antibodies titration (blood serum). Interviewers were equiped with all personel protective equipment required (aprons, gloves, surgical face masks, shoes and hair covers), discarded as hospital waste after each interview.

Data and specimen collection

A smartphone application for data collection was used by interviewers for listing and selecting household members, and also to record answers. Participants answered short questionnaires on sociodemographic information (sex, age, education, and occupation) and compliance with physical distancing measures. Participants (and family) previous exposition to COVID-19 was also evaluated in the questionnaire. All selected participants were asked to sign an informed consent and a blood specimen was drawn for serological tests to estimate patients´ immunological status as well as a nasopharyngeal swab for RT-PCR COVID-19 molecular test to estimate the incidence of COVID-19 in each sampling cycle. See study raw data in S1 Data.

Serological SARS-CoV-2 ELISA tests

To measure anti-SCOV2 RBD antibody levels, a chemiluminescent based immunoassay (CLIA) was performed with ACCESS SARS-CoV-2 IgM QC and ACCESS SARS-CoV-2 IgG II QC kits (Beckman Coulter, USA) in accordance with manufacturer instructions. Results were generated based on the ratio between the luminescence of tested specimen and the negative control. All results above 1.0 were considered positive in this assay.

To evaluate the title of neutralizing antibody in each sera specimens, Lumit SARS-CoV-2 Spike RBD:ACE2 immunoassay (Promega, Madison, WI, USA) was performed. Previously published protocol was followed and the result was calculated by the percentage of inhibition of RBD:ACE2 interaction by each serum analyzed. Inhibition above 70% was considered positive in terms the presence of neutralizing antibodies [19].

Viral RNA extraction and RT-PCR test

Nasopharyngeal swab samples were pooled together–four samples per pooling [20]. Nucleic acid extraction was performed a in automated Maxwell® RSC platform (Promega, USA). Extract pools was shortly storage at 4°C before RT-PCR analysis.

SARS-CoV-2 RNA detection was made following the CDC protocol for SARS-CoV-2 RT-PCR diagnosis (2019-nCoV CDC kit) [21] with CFX96 BioRad instrument. Pooled samples with detected Ct values in N1 and/or N2 were segregated and reanalyzed separately. Segregated nasopharyngeal swab samples were considered positive when Ct values for N1 and N2 were ≤ 38.

VOC assessments were made on SARS-CoV-2 RT-PCR positive samples by a 4Plex SARS-CoV-2 for VOC screening kit (Bio-Manguinhos, Brazil). The assay was based in a fourplex format. TaqMan probes for SARS-CoV-2 virus were used for detection a target region in the N gene, and screening samples with suggestive profiles for the different VOCs. Suggestive VOC profiles were given by combining results obtained of the deletions (Del) S106, G107 and F108, in the ORF1a gene (NSP6) and Del. H69 and V70 in the Spike gene from the samples tested. Samples were considered positive when Ct values for SC2-N, Wt Del NSP6 and Wt Del 69, 70 were lower than 40.

Ethics committee approval

Ethics approval was obtained from the UNIRIO Ethics Committee (CAAE 38341120.0.0000.5258), with written informed consent from all participants. Positive cases were reported to the municipal COVID-19 surveillance systems after participants agreed to the disclosure in the consent form.

Data analysis

All data included in the patient´s questionnaire was saved in a database to perform the analysis. Sociodemographic data and its association with SARS-CoV-2 infections was done with Chi-square tests with Yates correction. Serological and NAb production groups correlations were done with a Mann-Whitney unpaired test. All graphics and statistical analysis were based on GraphPad Prism 9.0.0. software (GraphPad Software, LLC). P-values lower than 0.05 were considered significant. Vaccination effectiveness was calculated based on the ration between the incidence of SARS-CoV-2 infection (by RT-PCR status), in vaccinated compared to unvaccinated subjects.

Results

During the three rounds of this study, a total of 1,134 subjects were interviewed. Table 1 resume overall collected sociodemographic data. Female participants were the majority during all three rounds (n = 679; 60%) as well as participants with age below 60 years old (yo) (n = 430; 38%). Thirteen percent of all participants showed previous COVID-19 diagnosis and almost one fourth of the interviewed participants reported disease in cohabiting relatives. This number increased to 40% when RT-PCR positive individuals were segregated; this correlation was statistically significant (χ2 = 5.1; p = 0.02354).

Table 1

Overview of sociodemographic and epidemiological data in all three studies.

Characteristics	Participants
	Round 1		Round 2		Round 3		Overall
	(n = 363)		(n = 384)		(n = 387)		(n = 1134)
	% (no.)	Median (Range)	% (no.)	Median (Range)	% (no.)	Median (Range)	% (no.)	Median (Range)
Gender
Female	59 (215)		63 (244)		57 (220)		60 (679)
Male	41 (148)		37 (140)		43 (167)		40 (455)
Age groups
All participants	-	54 (19–91)	-	56 (18–91)	-	54 (18–87)	-	54 (18–91)
< 60 years old	63 (230)	42 (19–59)	60 (230)	46 (18–59)	63 (244)	43 (18–59)	62 (704)	43 (18–59)
≥ 60 years old	37 (133)	68 (60–91)	40 (154)	66 (60–91)	37 (143)	68 (60–87)	38 (430)	68 (60–91)
Previous COVID-19 diagnosis reported
Participant	13 (47)		13 (49)		13 (50)		13 (146)
Familya	31 (112)		29 (112)		18 (68)		26 (292)
Comorbidities reported
Hypertension	41 (149)		41 (157)		35 (136)		39 (442)
Diabetes	14 (51)		18 (68)		11 (41)		14 (160)
Asthma/Bronchitis	8 (28)		6,5 (25)		(19)		6 (72)

aCOVID-19 cases reported in relatives living in the same house.

The most prevalent comorbidity were hypertension, followed by diabetes, and then respiratory syndromes. Other sociodemographical characteristics such as educational level, hygiene and social distance compliance are detailed in S1 Table.

When all data regarding non-pharmacological measurements was analyzed, no differences between RT-PCR or anti-SCOV2 positive individuals and SARS-CoV-2 unexposed subjects (RT-PCR negative and anti-SCOV2 antibodies seronegative) were observed (S1 Table). Regarding the educational level, we found that RT-PCR positive results were higher in lower educational background. Moreover, we did not find positive cases in participants with superior educational levels (S1 Table).

Among RT-PCR positive individuals, main symptoms were cough and “body ache” (S1 Table). For seropositive individuals for COVID-19, main symptoms could not be distinguished from the general population and are related as running nose, cough, and headache.

The overall rate of positive SARS-CoV-2 RT-PCR (RT-PCR+) results was 1.76% (Fig 1A). We observed a progressive reduction of 58% in RT-PCR+ cases from the first to the third round of the study. The global Ct median of SARS-CoV-2 N1 target was 27.32 (range 16.61–37.04) and became stable across all three study rounds (Fig 1B). Our VOC screening analysis showed that in the first round 100% (n = 6) of RT-PCR+ of the samples had the deletion on H69 and V70 on Spike gene, an indicative of Gamma VOC profile. In the second round, six out of seven samples (85%,) had the same Gamma profile, with the remaining one presenting no deletions on ORF1a and Spike genes and being classified as “others”. In the last round of the study, from three samples analyzed we found one with Gamma profile, one classified as “others” and one that showed deletions on (Del) S106, G107 and F108, in the ORF1a gene, and H69 and V70 on Spike gene, suggesting a Delta VOC SNP signature.

Fig 1

Incidence of Covid-19 in the study.

A) Percentage of SARS-CoV-2 RT-PCR positive participants in all and each round of the study. B) N1 target Ct average of participants SARS-Cov-2 RT-PCR positive in all and each round of the study.

RT-PCR+ participants were predominantly female and below 60yo (Table 2). Seventy percent had comorbidities; hypertension was present in half of the participants followed by diabetes and respiratory syndromes. Regarding vaccination status, fifty five percent of RT-PCR+ participants received at least one vaccine jab and 40% were fully immunized. Approximately 75% (n = 8) of vaccinated RT-PCR+ participants received at least one jab of CoronaVac. The remaining three individuals infected were immunized with AstraZeneca. Most of RT-PCR+ participants reported recent symptoms related to COVID-19 (n = 13; 65%) and the remaining (n = 7; 33%) did not report any kind of symptoms. Fifty four percent (n = 7) of the symptomatic RT-PCR+ participants were vaccinated. Among them, five participants (71%) were fully immunized with CoronaVac and the remaining received two doses of AstraZeneca vaccine. No significant difference on N1 target Ct values (P = 0.94) was observed between infected vaccinated (M = 27.6) and unvaccinated (M = 27.0) individuals.

Table 2

Overview of all epidemiological and clinical data from RT-PCR positives individuals.

Characteristics	Participants
	Round 1		Round 2		Round 3		Overall
	% (no.)	Median (Range)	% (no.)	Median (Range)	% (no.)	Median (Range)	% (no.)	Median (Range)
	100 (n = 9)		100 (n = 7)		100 (n = 4)		100 (n = 20)
Gender
Female	56 (5)		57 (4)		75 (3)		60 (12)
Male	44 (4)		43 (3)		25 (1)		40 (8)
Age groups
All participants	-	43 (27–70)	-	55 (36–71)	-	64 (34–76)	-	50 (27–76)
< 60 years old	67 (6)	35 (27–45)	57 (4)	40 (36–55)	25 (1)	34 (34)	55 (11)	37 (27–55)
≥ 60 years old	33 (3)	68 (67–70)	43 (3)	65 (63–71)	7 5 (3)	68 (60–76)	45 (9)	68 (60–76)
Symptoms related to COVID-19
Symptomatic	67 (6)		71 (5)		50 (2)		65 (13)
Asymptomatic	33 (3)		29 (2)		50 (2)		35 (7)
Previous COVID-19 diagnosis
Participant	11 (1)		29 (2)		25 (1)		20 (4)
Familya	33 (3)		71 (5)		25 (1)		45 (9)
Comorbidities
Hypertension	44 (4)		43 (3)		75 (3)		50 (10)
Diabetes	22 (2)		0 (0)		0 (0)		10 (2)
Asthma/Bronchitis	22 (2)		0 (0)		0 (0)		10 (2)
Immunization status
Unvaccinated	67 (6)	-	43 (3)	-	0 (0)	-	45 (9)	-
Partially immunizedb	0 (0)	0 (0)	29 (2)	34 (27–40)	25 (1)	3 (3)	15 (3)	27 (3–40)
Fully immunizedc	33 (3)	22 (21–44)d	29 (2)	58 (41–74)	75 (3)	79 (21–86)	40 (8)	43 (21–86
	100 (n = 3)		100 (n = 4)		100 (n = 4)		100 (n = 11)
Vaccine type
AstraZeneca	0 (0)		50 (2)		25 (1)		27 (3)
CoronaVac	100 (3)		50 (2)		75 (3)		73 (8)

aCOVID-19 cases reported in relatives living in the same house.

bIndividuals that received at least one vaccine dose.

cIndividuals immunized with all doses preconized in the vaccine instruction insert.

dDays after last jab.

We observed an increase of 76% (χ2 = 98.9; p<0.00001) in vaccinated participants across all three study rounds (Table 3). At the end of the third round, the global vaccination rate was 65% for participants receiving at least one vaccine jab and there no significant changes were found for fully immunized subjects. Over the three rounds, CoronaVac and AstraZeneca standard the most frequent vaccines administered.

Table 3

Overview of vaccination profile of all participants in the three rounds of the study.

Characteristics	Participants
	Round 1	Round 2	Round 3	Overall
	% (no.)	% (no.)	% (no.)	% (no.)
	100 (n = 363)	100 (n = 384)	100 (n = 387)	100 (n = 1134)
Vaccination status
Unvaccinated	54 (196)	32 (124)	19 (74)	35 (394)
Vaccinateda	46 (167)	68 (260)	81 (313) d	65 (740)
	100 (n = 167)	100 (n = 260)	100 (n = 313)	100 (n = 740)
Immunization status
Partially immunizeda	50 (84)	63 (164)	53 (165)	56 (413)
Fully immunizedb	50 (83)	34 (96)	47 (148)	44 (327)
Vaccine type
CoronaVac	55 (92)	38 (100)	36 (114)	41 (306)
AstraZeneca	42 (71)	53 (139)	48 (149)	49 (359)
Pfizer	2 (3)	8 (21)	14 (44)	9 (68)
Janssen	0 (0)	0 (0)	2 (6)	1 (6)
Mixedc	1 (1)	0 (0)	0 (0)	<1 (1)
	100 (n = 83)	100 (n = 96)	100 (n = 148)	100 (n = 327)
Fully immunization by vaccine type
CoronaVac	90 (75)	94 (90)	62 (91)	78 (256)
AstraZeneca	9 (7)	6 (6)	34 (51)	20 (64)
Pfizer	0 (0)	0 (0)	0 (0)	0 (0)
Janssen	0 (0)	0 (0)	4 (6)	2 (6)
Mixed	1 (1)	0 (0)	0 (0)	<1 (1)

aIndividuals that received at least one vaccine dose.

bIndividuals immunized with all doses preconized in the vaccine instruction insert.

cFirst dose CoronaVac and second dose AstraZeneca.

d p<0.00001

The increase of vaccination rate impacted the anti-SCOV2 IgG (anti-SCOV2 IgG) serum levels on participants evaluated by CLIA assay. We observed a sustained increase of anti-SCOV2 IgG positive results through the three rounds (37%, 47% and 52%) with a overall rate of anti-SCOV2 IgG positive individuals of 48%. Fig 2 shows the anti-SCOV2 IgG profile in vaccinated and unvaccinated groups. Of note, both groups presented a rise in the number of anti-SCOV2 IgG positive individuals (Fig 2A). However, the percentage of anti-SCOV2 IgG positive individuals was around three times higher in the vaccinated group on average. On the third round, the anti-SCOV2 IgG positive rate decreased in vaccinated individuals with age above 60yo (Fig 2C). Furthermore, anti-SCOV2 IgG positive rate in the third round increased to 47% on unvaccinated subjects (Fig 2A) and to 53% among unvaccinated subjects below 60yo (Fig 2B) when compared to the second round. This increase in the amount of unvaccinated IgG positive individuals in the 3rd round was statistically significant (χ2 = 7.68; p = 0. 05584). When unvaccinated subjects carrying anti-SCOV IgG antibodies in the third round were analyzed, 78% of them reported no COVID-19 symptoms in the last 30 days prior to interview, suggesting asymptomatic infections in this group. This number contrasts with the RT-PCR+ counterpart where most of the infections were symptomatic.

Fig 2

Percentage of anti-SCOV2 immunoglobulin positivity in each study cycle.

A, B and C) Anti-SCOV2 Immunoglobulin profile of unvaccinated participants. A) All vaccinated participants. B) <60 years old group. C) ≥60 years old group. White bars represent the 1st cycle, grey bars the 2nd cycle and black bars the 3rd cycle.

In general, the median title of anti-SCOV2 IgG in fully immunized individuals was higher than in unvaccinated individuals (Fig 3). In our study, 90% of vaccinated individuals received CoronaVac or AstraZeneca vaccines. Both vaccines produced significant levels of anti-SCOV2 IgG (p<0.0001) in fully immunized individuals when compared to unvaccinated ones, independent of age (Fig 3A–3C). Of note, there was no significant difference between one dose CoronaVac population (IgG level OD/Cut-off M = 0.2) and unvaccinated individuals. The median levels of anti-SCOV2 IgG in unvaccinated subjects was drastically lower (M = 0,08) when compared to fully vaccinated ones (CoronaVac: M = 1,17 and AstraZeneca: M = 4,19). Even when analyzed by age, CoronaVac (<60yo M = 0.97; ≥60yo M = 1.19) and AstraZeneca (<60yo M = 3.27; ≥60yo M = 4.62) fully immunized groups exhibited higher median levels compared to unvaccinated population (<60yo M = 0.08; ≥60yo M = 0.3). Based on IgG levels, AstraZeneca was significantly more effective than CoronaVac in the fully immunized population (p = 0.0001) or in individuals below (p = 0.0136) and above (p = 0.0001) 60yo. This fact could be explained by the time after full immunization of individuals and their age as differences were observed between CoronaVac (M = 10 weeks, M = 70yo) and AstraZeneca (M = 4 weeks, M = 60yo) (see Fig 4 for details). Overall, vaccinee age impacted IgG levels measured by CLIA assays. Individuals older than 60yo showed lower IgG levels compared to younger age groups (<60yo).

Fig 3

Comparisons among unvaccinated and fully immunized groups according to their anti-SCOV2 IgG and NAb levels.

A, B and C) Anti-SCOV2 IgG serum levels according to age (overall, <60 and ≥60 years old, respectively). D, E and F) NAb serum levels of overall, <60 and ≥60 years old groups, respectively. Red line represents the cut offs (≥1.0 and ≥70%). Blue lines stands for the median of each group. Red dots represent SARS-CoV-2 RT-PCR positive individuals in each group. * p value <0.05; **** p value <0.0001.

Fig 4

Fully vaccinated groups distribution.

A) Distribution of CoronaVac and AstraZeneca fully vaccinated groups according to time after the end of immunization scheme. B) Age distribution of CoronaVac and AstraZeneca fully vaccinated groups.

When RT-PCR positive results were analyzed in vaccinated and unvaccinated groups, a clear difference in IgG levels was observed. Most of RT-PCR+ samples had lower IgG titles (n = 14) (Fig 3, red dots).

We further investigated neutralizing antibodies (NAb) in a selected group of IgG positive individuals with the Lumit assay (Fig 3D–3F). We found that 79% of IgG+ participants vaccinated with AstraZeneca developed NAb in a relevant title (>70%). On the other hand, CoronaVac induced NAb in 24% of total IgG+ individuals. In contrast, only 10% of unvaccinated IgG+ participants had NAb and this was significantly lower compared to CoronaVac fully vaccinated group (χ2 = 6.9, p = 0.008403). There was a clear association between the level of anti-SCOV2 IgG measured by CLIA and the percentage of individuals carrying positive levels of NAb in our study. When anti-SCOV2 antibody levels were breakdown into three OD/Cut-off windows (1 to 5; 5 to 10; and beyond 10) we found 41, 77, and 96% of individuals showing detectable levels of NAb, respectively. Interestingly, we found that the majority of RT-PCR+ individuals presented high levels of NAb (n = 7) with only three showing low NAb levels (<70% of RDB:ACE2 inhibition) regardless the vaccination status.

A correlation between NAb production and anti-SCOV2 IgG levels in AstraZeneca fully immunized subjects (Fig 3D–3F) could also be found. Nearly 100% of individuals of this group showed significantly higher IgG levels when compared to IgG+ unvaccinated population, regardless age (global, <60 and >60yo; p = 0.0001). In comparison to CoronaVac, AstraZeneca elicited more NAb production in individuals above 60yo (p = 0.0001) as well as in overall fully immunized ones (p = 0.0001). We did not see any statistical difference in NAb levels between fully immunized CoronaVac and unvaccinated IgG+ individuals. Although there was a small number of individuals vaccinated with Pfizer and Janssen vaccines, their effectiveness in terms of production of anti-SCOV2 IgG and NAb was also analyzed. Janssen (n = 6) fully immunized individuals had the highest anti-SCOV2 IgG levels (M = 13.36) when compared to the AstraZeneca fully immunized group (M = 4,19). Although we did not find Pfizer fully immunized individuals in our study, participants who received one jab of Pfizer (n = 68) produced strong levels of anti-SCOV2 IgG (M = 8.02) and NAb (M = 99%). We did not observe RT-PCR+ subjects vaccinated with Pfizer or Janssen. However, the high IgG titles of Pfizer and Janssen vaccinees could reflect their recent immunization (<2 months). CoronaVac fully immunized individuals had an average time after the second dose of 10 weeks (range 2–24), whereas for AstraZeneca fully immunized individuals this was 4 weeks (range 2–17) (Fig 4A). CoronaVac fully immunized individuals had an average age of 70yo, whereas AstraZeneca fully immunized individuals had an average age of 60yo (Fig 4B). Participants vaccinated with Pfizer and Janssen had their immunizations recently given–Pfizer 1st dose 3 weeks (range 0–10); Janssen 3 weeks (range 2–4). Moreover, those participants were younger (M = 47yo) than individuals fully immunized with CoronaVac and AstraZeneca vaccines.

Besides our limited RT-PCR+ samples, we could find a level of protection against SARS-CoV-2 infection between vaccinated and unvaccinated population in our study (34%). However, if we stratify individuals fully vaccinated according to vaccine kind, CoronaVac vaccinated subjects presented no level of protection contrasting to the AstraZeneca fully immunized ones. Moreover, when incidence data and immunization rate were combined for each round of the study, an inverse correlation is found (Fig 5). As immunization rates increase, the number of individuals showing detectable levels of IgG anti-SARS COV2 as well as detectable NAb over the cycles increases at the same pace. Contrasting to that, COVID-19 incidence measured by RT-PCR dropped drastically (Fig 5). In addition, if the proportion of VOCs presented in each cycle are compared with COVID-19 incidence, a drop in incidence is noticed regardless to a shift of VOCs proportion (Fig 5). At the beginning of our study Gamma variant was the most frequent (90%) and was substituted by Delta variant in the last study round.

Fig 5

Impact of immunization on COVID-19 incidence on the studied population.

On the left Y axis: red line shows de COVID-19 incidence on the studied population over the three round. On the right Y axis: 1) black line represents the percentage of vaccinated participants through the three rounds; 2) blue line shows the percentage of SCOV2 IgG+ individuals (IgG OD/CO >1.0); 3) dotted blue line points the percentage of SCOV2 IgG+ individuals carrying detectable levels of NAb. Black, grey, and white bars represent the frequency of Delta (Δ), Gamma (γ) and other VOCs, respectively, in the city of Maricá when all three rounds were performed.

Discussion

Population-based data on COVID-19 are essential for guiding policies and evaluating public health interventions made during pandemics [13-16]. So far, there are few such studies, particularly from lower or middle-income countries [15, 17]. Our study captures epidemiological data from individuals randomly selected in three districts of Maricá, Brazil. We selected 39 urban census tracts with probability proportional to size sampling in three sentinel round, collecting data and clinical specimens of 384 individuals in each round. The data presented here corroborate previous knowledge that the presence of infected individuals in the same house is a major risk for SARS-CoV-2 infection worldwide [17, 22–26]. In fact, we observed a prevalence of RT-PCR+ participants and the presence of a household with COVID in our study. After sociodemographical analysis, we could find an association between educational level and SARS-CoV-2 RT-PCR positivity. It is well known that COVID-19 has a higher incidences among individuals with lower levels of education [15, 17, 22–24, 27–30]. Although we could not point statistically differences, we also found a high number of RT-PCR+ individuals having running nose, cough, and headache. As seen by others, it was difficult to establish a specific group of symptoms related to SARS-CoV-2 infection [31].

The global rate of RT-PCR+ individuals in the study was 1.76%. We observed a progressive reduction on RT-PCR+ cases throughout the study rounds. Fifty five percent of RT-PCR+ participants received at least one vaccine jab and 40% were fully immunized with CoronaVac or AstraZeneca vaccines. Most of RT-PCR+ participants reported recent symptoms related to COVID-19. Approximately half of the RT-PCR+ symptomatic participants were vaccinated, and we found no significant differences in N1 Ct values between vaccinated and unvaccinated individuals. This indicates that the vaccine itself might not impact viral load during acute infections. This could be due to the kind of VOC in those infected individuals [32, 33].

The global vaccination rate observed in our study was 65% in participants receiving at least one vaccine jab, and CoronaVac and AstraZeneca were the most frequent vaccines used. We observed a sustained increase in anti-SCOV2 IgG positive participants over the three rounds of the study. The overall anti-SCOV2 IgG positive individuals rate was 48%. In comparison to unvaccinated participants, the anti-SCOV2 IgG positivity in vaccinated individuals was nearly three times higher. However, we observed a significant increase in the amount of unvaccinated IgG positive individuals in the 3rd round, which matched with the increase of Delta variant in Rio de Janeiro State and Maricá [8]. Most of them reported no COVID-19 symptoms in the last 30 days prior to interview, suggesting an asymptomatic infection in this group. This number contrasts with the RT-PCR+ data, where more symptomatic infections were observed. This fact could be due to the introduction of Delta variant, known to be more transmissible and previously related to asymptomatic infections when compared to Gamma [28, 30–32, 34, 35].

The most frequent vaccines received by our population were CoronaVac and AstraZeneca. Both vaccines produced significant levels of anti-SCOV2 IgG in fully immunized individuals when compared to unvaccinated ones. Based on IgG levels, AstraZeneca was significantly more effective than CoronaVac in fully immunized individuals. This could be explained by the immunization strategy adopted in Brazil [12], since the COVID-19 National Immunization Program started with CoronaVac immunization in elderlies with AstraZeneca and other vaccines (Pfizer and Janssen) coming right after that in adult immunization. In fact, in this study, participants vaccinated with AstraZeneca were younger and had less time after full immunization when compared with CoronaVac vaccinees. Another observation was that vaccinee age impacted the level of IgG. Vaccinated individuals older than 60yo had lower IgG levels when compared to a younger group. As previously demonstrated by several studies, this could represent the basis by which a 3rd dose was rapidly recommended in elderly across many countries [36-38].

Our study showed a clear association between anti-SCOV2 IgG levels and the percentage of individuals with detectable levels of NAb. CoronaVac and AstraZeneca produced significant levels of NAb in anti-SCOV2 IgG positive vaccinated individuals. Again, AstraZeneca was significantly more effective in NAb production than CoronaVac considering the fully immunized population. This could be explained by participants age and/or the long time after the second CoronaVac dose [38, 39]. Interestingly, most of the individuals that showed RT-PCR+ in the vaccinated group had a strong neutralization title indicating a fast NAb production after SARS-CoV-2 infection [40]. Only a few percentages of unvaccinated anti-SCOV2 IgG positive participants had NAb. Some of them with high anti-SCOV2 IgG and Nab levels, that could indicate infection close to each study round [41, 42].

In contrast to several studies [43-45], we could see a small level of protection against SARS-CoV-2 infection in vaccinated population in our study, besides our limited sample size (34%). The same level of protection was seen in AstraZeneca fully vaccinated individuals. In contrast, we could not find any level of protection in CoronaVac fully immunized subjects. However, it was possible to see an inverse correlation between incidence data and immunization rate. As the number of individuals showing detectable levels of IgG anti-SARS COV2 and NAb increased, incidence of RT-PCR+ dropped drastically.

Nonetheless, COVID-19 incidence drop should not only be interpreted in the light of vaccination status. Community transmission rates in a specific period and mitigation measurements must be considered. We found no statistical correlations on our non-pharmacological measures and social distance compliance analysis. It will be necessary, in future studies, to increase the number of and/or the time among rounds to cover different periods of community transmission.

In addition, Maricá epidemiological data such as severe case hospitalization as well as mortality has dropped 3 times in the same period, corroborating our study findings [7]. Of note, we observed a shift of VOCs across the three cycles of our study. Indeed, there was a shift of VOCs in the Rio de Janeiro State [8]. At the beginning of our study Gamma variant was the most frequent (90%) in the population whereas Delta variant appeared only in six percent of the cases. At the end of study Delta variant was found in 90% of individuals studied in a SARS-CoV-2 VOC sampling done in Rio de Janeiro State [8]. Then, we can argue that this drop in incidence at the same time of Delta VOC introduction could be due to a high vaccination rate.

Conclusion

Our findings show that the number of individuals carrying detectable anti-SCOV2 IgG and NAb levels was bigger in vaccinated compared to unvaccinated groups, proving the importance of the vaccination to attain noticeable levels of herd immunity against SARSCoV-2. We found a decreased incidence of COVID-19 throughout the study, and this was correlated with vaccination status, IgG levels and NAb titles across study rounds. Our data clearly support the use of vaccines to drop the incidence of SARS-CoV-2 infection and the consequent reduction in morbidity and mortality associated with COVID-19. We also found a drop in the anti-SCOV2 IgG levels as well as Nab titers in individuals vaccinated with CoronaVac at more than 10 weeks. We could not see these drops in the AstraZeneca, Pfizer and Janssen vaccines, probably to a short period of time after immunization until sampling. This kind of sampling methodology is an inexpensive way to monitor the spread of COVID-19 in a population and to evaluate the impact of vaccination in low-income countries.

Detailed sociodemographic, non-pharmacological measures and clinical data from participants.

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22 Mar 2022

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Reviewer #1: The manuscript “COVID-19 population-based survey in Maricá, Brazil: the impact of vaccination in viral incidence” submitted to PlosOne Journal presented data about the decrease in the incidence of COVID-19 according to the level of vaccination in a Brazilian city, investigating data of three repeated cross-sectional from 1134 subjects in a population-based epidemiological study from May to August 2021.

It is an interesting study. However, I would like to discuss some aspects with the authors to improve the manuscript before publication. I recommend the authors revise the results description and indications of the figures and tables in the text. Also, a revision of the conclusion. In summary, the study can be published after minor revision. Questions, comments, and suggestions are listed below:

Major comments:

#1 Introduction: Since it is currently well known that vaccination prevents COVID-19 infection, I recommend including the reasons to explore this issue in this article. Some points:

For example, in comparison or sequence with other studies, what novelty this relevant study may corroborate? Is it because of the Brazilian context during the period? Is it because of the specific behavior of the population in this local? Was it not expected that the vaccine promotes an increase of neutralizing antibody levels, or during this period, this was unknown information? The type of vaccine applied vs. variant prevalence can be included as a novel aspect for readers?

To summarize, it is not clear the novelty end contribution of the study for readers in the introduction section. The authors presented clearly the study objective in the introduction: “our aim is to investigate SARS-CoV-2 antibody (anti-SCOV2) prevalence by city and RT-PCR results in a repeated cross-sectional study in a municipality”. However, the lack of information in the field that can be answered with the study is not completely clear in the introduction. For example, there are some comparisons made about vaccine type in the study. After reading the introduction section, this type of comparison is not expected for readers.

#2 Methods: The authors informed: “Subjects below 18 years old were excluded, and if the selected individual did not provide a sample, another household member was randomly selected.” During the period, teenagers had access to vaccination in this place? If they don’t, I suggest including this information as a reason not to include < 18 yo subjects. If they had access to the vaccine, please inform readers why not include them. All other information was adequately presented in methods such as ethical approval, population-based sampling procedures (areas and subjects), sample collection and analytical procedures (RT-PCR, serological tests…),

#3 Figure 1B showed an increase in the N1 target CT during the 2° transversal data collection cycle and a decrease in the next cycle. Is there some special meaning about this result according to the variant/period to be interpreted and discussed in the manuscript?

#4 The description of the results presented in figure 2 needs a revision. There is some repetition of information. Also, the text informed (line 292): “On the third cycle the anti-SCOV2 IgG positive rate decreased in vaccinated individuals with age above 60yo (Fig 2C)”. However, the decreasing is showed in the figure of unvaccinated individuals in the figure. (is it possible that groups were presented in the figure changed?). Also, the legend of figure 2 includes figures 2D, 2E, and 2F. However, these figures were not presented. In another hand, the results about the prevalence of NAB+ in unvaccinated vs. vaccinated subjects showed in the figure 2 were not described in the text.

#5 The discussion is adequately centered on the effect of vaccines on the reduction of COVID-19 impact. Also, there is a discussion about the type of vaccine. Because of these, I recommend above to include this expectation in the introduction for readers. Also, since the vaccine is not only the way to avoid the incidence of COVID-19, I recommend authors include a short paragraph in the discussion about the local recommendations and adherence of subjects in the period of the study in terms of social distancing and use of masks, for example. This is necessary to better understand of the context and also may help to improve the support of the conclusion: “The effect of vaccines”.

#6 Conclusion: I recommend deleting the text between lines 531-535, it is a description of the study again. Also, authors concluded an additional point not expected: “We also found a drop in the anti-SCOV2 IgG levels as well as NAb in individuals vaccinated CoronaVac more than 10 weeks supporting the use of an additional vaccine dose to boost the immune response in these individuals.” However, the study showed that Coronavac presented lower levels of protection in comparison with AstraZeneca and argued that these findings were due to the time after completing the vaccination scheme. For supporting this conclusion adequately, It was necessary to include results about the analysis of protection levels vs. time after vaccination in both vaccine regimens. However, the authors agree that this is not possible since “We could not see these drops in the AstraZeneca, Pfizer and Janssen vaccines due to a short period of time after immunization before our sampling”. Thus, since the decrease in the protection was not adequately presented in the study, this conclusion may not be adequate. I would like to hear the authors about it.

Minor points:

#7 Authors described the result of 26% of family history of COVID-19 as follows: “almost one-third of the 211 interviewed participants reported disease in relatives cohabiting the household.”. I suggest that the authors change this text for approximately one-fourth, not one-third.

#8 After the description of the results on lines 223-229, please indicate for readers to find these results in table S1;

#9 Is the text described in lines 348-351 about the results presented in figure 3? The comparison about IGG levels using only COVID positive subjects could be presented with more details, in the text of including a graph in figure 3.

Reviewer #2: The study evaluates the seropositive gains CPVO-19 according with vaccinal status, over time in Marica-RJ.

1. I suggest that the authors followed the STROBE statement Statement—Checklist of items that should be included in reports of cross-sectional studies.

2. The title must contain the study design.

3. The title specifies that the study evaluates the impact of the vaccination in viral incidence, but in the abstract the objectives was to evaluate the immunological status (antibodies against SARS-COV2), not the viral incidence (see title, pg 57 and pg 105-107). Please adapt the title.

4. The conclusion of the abstract refers to drop in mortality, that was not supported in the data presented. There is no mortality data in the study.

5. In the methods section, the sampling process description should include the period of recruitment and also explain how the study size was arrived at. The eligibility criteria and exclusion must be described. How the study handled with illiterate participants or individual with special needs?

6. The main outcomes need to be clearly defined, as well as exposures, predictors, potential confounders, and effect modifiers.

7. The data analysis must contain the test used do calculate effectiveness and also include how the immunological variables were handled. Additionally, must contain the software used for data analysis.

8. Regarding the results, please confirm that the number of participants with previous COVID was the same (13) in all three cycles – Table 1.

9. Please include a measure of difference in the S1 table and Table 1 or add the measurements to the text. The paragraph 223-229 stated that there are differences between groups, but there is no statistical test associated to that.

10. In line 275 the authors stated that there is an increase in % of participants, but there is no statistical test associated. Please include a statistical test in Table 3.

11. The Figure 2 need a legend for the abbreviations - NAb+.

12. Please correct the figure 3 and add p-value for the differences between groups or add a legend to state what the number 1 1 1 1 means.

13. Please specify which figure/table the results from lines 348-351 refers to sentence 360-362. As well as for the correlation states in lines 371-372.

14. In Figure 5 is very confuse. The Y axis goes from 0-3 and the secondary axes from 0-100% without axis specification.

15. Inline 401, is not clear with outcome the effectiveness analysis refers to. Please clarify and add the statistical test.

16. The authors make different statements regarding the association of risk factors and the PCR positivity. These affirmation needs to be based on multivariate analysis to avoid confounding bias. Please add a multivariate analysis to evaluate the risk factors (Pgs 438-448) or modify the paragraph.

17. The authors should include a paragraph with the weaknesses of the study.

18. The incidence of COVID-19 could be not only because of vaccination status but also due to the probability of infection in a specific period of time, that depend also from community transmission rates and mitigation measurements. Please discuss this.

19. The manuscript needs a grammar English review.

**********

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Reviewer #1: Yes: Thiago Gomes Heck

Reviewer #2: No

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23 Apr 2022

To PlosOne

REF: Rebuttal Letter Manuscript PONE-D-22-03333.

Rio de Janeiro, 3/30/2022

Dear Editor

Thank you for the excellent review done in our manuscript entitled “COVID-19 population-based survey in Maricá, Brazil: the impact of vaccination in viral incidence.” I am sure that reviewers´ comments will make the article clearer and more interesting for readers.

Please find bellow our response to reviewers queries.

Reviewer #1:

Major comments:

#1 Introduction: Since it is currently well known that vaccination prevents COVID-19 infection, I recommend including the reasons to explore this issue in this article. Some points:

For example, in comparison or sequence with other studies, what novelty this relevant study may corroborate? Is it because of the Brazilian context during the period? Is it because of the specific behavior of the population in this local? Was it not expected that the vaccine promotes an increase of neutralizing antibody levels, or during this period, this was unknown information? The type of vaccine applied vs. variant prevalence can be included as a novel aspect for readers?

To summarize, it is not clear the novelty end contribution of the study for readers in the introduction section. The authors presented clearly the study objective in the introduction: “our aim is to investigate SARS-CoV-2 antibody (anti-SCOV2) prevalence by city and RT-PCR results in a repeated cross-sectional study in a municipality”. However, the lack of information in the field that can be answered with the study is not completely clear in the introduction. For example, there are some comparisons made about vaccine type in the study. After reading the introduction section, this type of comparison is not expected for readers.

We concur with reviewer comment and we have included a new text and three new references (9-11) to discuss the impact of vaccination in viral incidence.

#2 Methods: The authors informed: “Subjects below 18 years old were excluded, and if the selected individual did not provide a sample, another household member was randomly selected.” During the period, teenagers had access to vaccination in this place? If they don’t, I suggest including this information as a reason not to include < 18 yo subjects. If they had access to the vaccine, please inform readers why not include them. All other information was adequately presented in methods such as ethical approval, population-based sampling procedures (areas and subjects), sample collection and analytical procedures (RT-PCR, serological tests…),

The reason we included only adults (>18 years old by Brazilian laws) is that collecting samples from childrens (<18 years old) needs the approval/consent of the kid guardian and it would complicate our study. In addition, our IRB has very restricted rules to include children in epi studies.

#3 Figure 1B showed an increase in the N1 target CT during the 2° transversal data collection cycle and a decrease in the next cycle. Is there some special meaning about this result according to the variant/period to be interpreted and discussed in the manuscript?

We agree and we have included a new paragraph discussing this issue in the discussion section.

#4 The description of the results presented in figure 2 needs a revision. There is some repetition of information. Also, the text informed (line 292): “On the third cycle the anti-SCOV2 IgG positive rate decreased in vaccinated individuals with age above 60yo (Fig 2C)”. However, the decreasing is showed in the figure of unvaccinated individuals in the figure. (is it possible that groups were presented in the figure changed?). Also, the legend of figure 2 includes figures 2D, 2E, and 2F. However, these figures were not presented. In another hand, the results about the prevalence of NAB+ in unvaccinated vs. vaccinated subjects showed in the figure 2 were not described in the text.

This was corrected in the new version of the manuscript (see corrected copy in annex).

#5 The discussion is adequately centered on the effect of vaccines on the reduction of COVID-19 impact. Also, there is a discussion about the type of vaccine. Because of these, I recommend above to include this expectation in the introduction for readers. Also, since the vaccine is not only the way to avoid the incidence of COVID-19, I recommend authors include a short paragraph in the discussion about the local recommendations and adherence of subjects in the period of the study in terms of social distancing and use of masks, for example. This is necessary to better understand of the context and also may help to improve the support of the conclusion: “The effect of vaccines”.

Thanks for this remind and we have included a new paragraph to discuss this point in Conclusion section.

#6 Conclusion: I recommend deleting the text between lines 531-535, it is a description of the study again. Also, authors concluded an additional point not expected: “We also found a drop in the anti-SCOV2 IgG levels as well as NAb in individuals vaccinated CoronaVac more than 10 weeks supporting the use of an additional vaccine dose to boost the immune response in these individuals.” However, the study showed that Coronavac presented lower levels of protection in comparison with AstraZeneca and argued that these findings were due to the time after completing the vaccination scheme. For supporting this conclusion adequately, It was necessary to include results about the analysis of protection levels vs. time after vaccination in both vaccine regimens. However, the authors agree that this is not possible since “We could not see these drops in the AstraZeneca, Pfizer and Janssen vaccines due to a short period of time after immunization before our sampling”. Thus, since the decrease in the protection was not adequately presented in the study, this conclusion may not be adequate. I would like to hear the authors about it.

We agree and we modified this paragraph in the Discussion section removing this comparison.

Minor points:

#7 Authors described the result of 26% of family history of COVID-19 as follows: “almost one-third of the 211 interviewed participants reported disease in relatives cohabiting the household.”. I suggest that the authors change this text for approximately one-fourth, not one-third.

Thanks for your suggestion, the change was done.

#8 After the description of the results on lines 223-229, please indicate for readers to find these results in table S1;

We included the table S1 indication in the text.

#9 Is the text described in lines 348-351 about the results presented in figure 3? The comparison about IGG levels using only COVID positive subjects could be presented with more details, in the text of including a graph in figure 3.

You are correct, the paragraph describes results presented in figure 3. We included the indication in the text and pointed those red dots in the figures 3 represent COVID positive subjects.

Reviewer #2: The study evaluates the seropositive gains CPVO-19 according with vaccinal status, over time in Marica-RJ.

1. I suggest that the authors followed the STROBE statement Statement—Checklist of items that should be included in reports of cross-sectional studies.

We appreciate all the suggestions, and we checked the items in the STROBE statement and placed inside the manuscript.

2. The title must contain the study design.

The study design was included in the title.

3. The title specifies that the study evaluates the impact of the vaccination in viral incidence, but in the abstract the objectives was to evaluate the immunological status (antibodies against SARS-COV2), not the viral incidence (see title, pg 57 and pg 105-107). Please adapt the title.

We agree with your point. Title was adapted.

4. The conclusion of the abstract refers to drop in mortality, that was not supported in the data presented. There is no mortality data in the study.

We agree with your point. The results presented on this study do not support the drop of mortality. That affirmation was excluded in the text.

5. In the methods section, the sampling process description should include the period of recruitment and also explain how the study size was arrived at. The eligibility criteria and exclusion must be described. How the study handled with illiterate participants or individual with special needs?

The period was included in the sampling strategy. The exclusion criteria were improved. For illiterate participants, we included a detail in data specimen collection, the questionnaire was applied by interviewers using an application. We did not use printed questionnaire in the study.

6. The main outcomes need to be clearly defined, as well as exposures, predictors, potential confounders, and effect modifiers.

We have included a new paragraph in Discussion section to place some of the cofounders and modified effects of our study.

7. The data analysis must contain the test used do calculate effectiveness and also include how the immunological variables were handled. Additionally, must contain the software used for data analysis.

Effectiveness calculations were explained at lines 207-210. We mentioned the software at line 206.

8. Regarding the results, please confirm that the number of participants with previous COVID was the same (13) in all three cycles – Table 1.

The percentage of participants with previous COVID was the same in all three cycles, but the number differed in each cycle. The number of participants with previous COVID are in parenthesis. We had to change the table layout to fit the page. A landscape layout is the best choice to present this table.

9. Please include a measure of difference in the S1 table and Table 1 or add the measurements to the text. The paragraph 223-229 stated that there are differences between groups, but there is no statistical test associated to that.

In this paragraph our intention was only to describe the different numbers of individuals with specific characteristics not a formal statical analysis. To make our text more clear we placed S1 Table reference at the end of this paragraph. Then the readers can find these number direct in Table S1.

10. In line 275 the authors stated that there is an increase in % of participants, but there is no statistical test associated. Please include a statistical test in Table 3.

The statistical analysis was included.

11. The Figure 2 need a legend for the abbreviations - NAb+.

The data about neutralizing antibodies were not supposed to be present in figure 2. Those data were excluded.

12. Please correct the figure 3 and add p-value for the differences between groups or add a legend to state what the number 1 1 1 1 means.

Sorry for that. The figured lost its configuration on the exportation process. The figure was fixed.

13. Please specify which figure/table the results from lines 348-351 refers to sentence 360-362. As well as for the correlation states in lines 371-372.

The lines 348-351 refer to figure 3. The indication was added in the text. The sentences 360-362 we meant association. We excluded the term correlation.

14. In Figure 5 is very confuse. The Y axis goes from 0-3 and the secondary axes from 0-100% without axis specification.

We also had a loss of configuration in this figure, it was fixed. But the axis meaning are detailed in the legends. Both show percentage values. We chose different scales for aesthetics proposal to try to demonstrate the drop on incidence (left Y axis) while increment of vaccination and Ig (right Y axis)

15. Inline 401, is not clear with outcome the effectiveness analysis refers to. Please clarify and add the statistical test.

The effectiveness refers to all vaccines combined in participants who received at least one shot.

16. The authors make different statements regarding the association of risk factors and the PCR positivity. These affirmation needs to be based on multivariate analysis to avoid confounding bias. Please add a multivariate analysis to evaluate the risk factors (Pgs 438-448) or modify the paragraph.

We agreed and changed the paragraph.

17. The authors should include a paragraph with the weaknesses of the study.

See comment 18.

18. The incidence of COVID-19 could be not only because of vaccination status but also due to the probability of infection in a specific period of time, that depend also from community transmission rates and mitigation measurements. Please discuss this.

These points really be considered. We discussed those together with weakness of the study.

19. The manuscript needs a grammar English review.

We have asked a native English speaker to review our manuscript and all corrections are in the new version.

We have also corrected some authors name which were with some type error. The references were renumbered to accommodate 3 new references included in the new version. We have also remove one of the authors which were duplicated in the authorship section.

Thank you for your attention and I hope our modifications satisfy the reviewers.

Sincerely Yours

Amilcar Tanuri

UFRJ

Submitted filename: A Tanuri PlosOne Rebbutal Letter.docx

Click here for additional data file.

1 May 2022