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. 2023 Dec 8;18(12):e0295167. doi: 10.1371/journal.pone.0295167

RBD-specific antibody response after two doses of different SARS-CoV-2 vaccines during the mass vaccination campaign in Mongolia

Burenjargal Batmunkh 1,‡, Dashpagma Otgonbayar 2,3,‡, Shatar Shaarii 3,#, Nansalmaa Khaidav 3,#, Oyu-Erdene Shagdarsuren 3,#, Gantuya Boldbaatar 4,#, Nandin-Erdene Danzan 4,#, Myagmartseren Dashtseren 4,#, Tsolmon Unurjargal 4,#, Ichinnorov Dashtseren 4,#, Munkhbaatar Dagvasumberel 4,#, Davaalkham Jagdagsuren 2,#, Oyunbileg Bayandorj 2,#, Baasanjargal Biziya 1,#, Seesregdorj Surenjid 5,#, Khongorzul Togoo 1,#, Ariunzaya Bat-Erdene 1,#, Zolmunkh Narmandakh 1,#, Gansukh Choijilsuren 1,#, Ulziisaikhan Batmunkh 1,#, Chimidtseren Soodoi 1,#, Enkh-Amar Boldbaatar 1,#, Ganbaatar Byambatsogt 6,#, Otgonjargal Byambaa 1,#, Zolzaya Deleg 1,#, Gerelmaa Enebish 1,#, Bazardari Chuluunbaatar 7,#, Gereltsetseg Zulmunkh 7,#, Bilegtsaikhan Tsolmon 2,#, Batbaatar Gunchin 1,#, Battogtokh Chimeddorj 1,#, Davaalkham Dambadarjaa 3,#, Tsogtsaikhan Sandag 1,*
Editor: Ashraful Hoque8
PMCID: PMC10707641  PMID: 38064430

Abstract

The SARS-CoV-2 vaccination campaign began in February 2021 and achieved a high rate of 62.7% of the total population fully vaccinated by August 16, 2021, in Mongolia. We aimed to assess the initial protective antibody production after two doses of a variety of types of SARS-CoV-2 vaccines in the Mongolian pre-vaccine antibody-naïve adult population. This prospective study was conducted from March-April to July-August of 2021. All participants received one of the four government-proposed COVID-19 vaccines including Pfizer/BioNTech (BNT162b2), AstraZeneca (ChAdOx1-S), Sinopharm (BBIBP-CorV), and Sputnik V (Gam-COVID-Vac). Before receiving the first shot, anti-SARS-CoV-2 S-RBD human IgG titers were measured in all participants (n = 1833), and titers were measured 21–28 days after the second shot in a subset of participants (n = 831). We found an overall average protective antibody response of 84.8% (705 of 831 vaccinated) in 21–28 days after two doses of the four types of COVID-19 vaccines. Seropositivity and titer of protective antibodies produced after two shots of vaccine were associated with the vaccine types, age, and residence of vaccinees. Seropositivity rate varied significantly between vaccine types, 80.0% (28 of 35) for AstraZeneca ChAdOx1-S; 97.0% (193 of 199) for Pfizer BNT162b2; 80.7% (474 of 587) for Sinopharm BBIBP-CorV, and 100.0% (10 of 10) for Sputnik V Gam-COVID-Vac, respectively. Immunocompromised vaccinees with increased risk for developing severe COVID-19 disease had received the Pfizer vaccine and demonstrated a high rate of seropositivity. A high geometric mean titer (GMT) was found in vaccinees who received BNT162b2, while vaccinees who received ChAdOx1-S, Sputnik V, and BBIBP-CorV showed a lower GMT. In summary, we observed first stages of the immunization campaign against COVID-19 in Mongolia have been completed successfully, with a high immunogenicity level achieved among the population with an increased risk for developing severe illness.

Introduction

Mongolia had no local COVID-19 cases until November 2020, however from November 2020 to March 2021 local cases increased gradually [1,2]. The nationwide vaccination campaign started on 23 February 2021 in Mongolia. Mongolia received the first batch of the inactivated BBIBP-CorV vaccine from Sinopharm, China, and the non-replicating viral vector vaccine Oxford-AstraZeneca, from India and began immunization in high-risk healthcare workers [1,3]. Other priority groups, including the elderly and those with chronic illnesses, were vaccinated following the arrival of further doses. In addition, the mRNA vaccine, Pfizer-BioNTech, and the non-replicating viral vector vaccine Gamaleya’s Sputnik V became available for administration later in the second half of 2021 in Mongolia [1]. The Mongolian campaign for a vaccination with these four types of vaccines was achieved at a high rate of 62.7% of the total population with full vaccination, as reported on August 16, 2021 [4,5].

Globally, the antibody production rate of these vaccines is well-documented [6–22]. However, we found few reports comparing the responses to multiple types of SARS-CoV-2 vaccines in the same vaccination campaign using the same antibody detection system. We explored the Mongolian experiences, with some unique experiences in this field including dispersed and rural populations. Despite successful vaccination campaigns, Mongolia has experienced an upsurge of new cases until February-March 2022, which may be related to the efficacy of the vaccine waning [5,23].

This study aimed to examine the initial protective antibody production after two doses of various types of SARS-CoV-2 vaccines in the Mongolian pre-vaccine antibody-naïve adult population.

Materials and methods

Study population

This prospective cohort study was conducted from April-May to July-August of 2021. All participants had received one of the four government-proposed COVID vaccines: Pfizer/BioNTech (BNT162b2), AstraZeneca (ChAdOx1-S), Sinopharm (BBIBP-CorV), and Sputnik V (Gam-COVID-Vac). Personal information and serum samples of vaccinees were collected in three population groups determined as a priority strategy by the Government of Mongolia.

The first group includes healthcare professionals and government employees (frontline employees) working in frontline places such as hospitals serving out and in-patients with confirmed SARS-CoV-2 infection, family doctors and emergency medical service units, and isolation campuses. Employees of randomly selected facilities in urban (a total of 14 sites including First State Hospital, Central Hospital of the Armed Forces, Mongolia-Japan Hospital of the Mongolian National University of Medical Sciences, and Family Medicine Centers) and rural healthcare sites (general hospitals and primary healthcare centers in 5 selected provinces-aimags) were presented in the group.

The second group includes people with increased risk for severe COVID-19, including immunocompromised patients after immunosuppressive therapy for cancer and systemic or autoimmune diseases (SAD), people living with human immunodeficiency virus infection and acquired immunodeficiency syndrome (PLWHA), pregnant women in the last two trimesters of pregnancy, and elderlies aged above 60 years. Cancer and SAD patients, and PLWHA were classified as the immunocompromised population. SAD patients were selected from patients observed at First State Hospital, cancer patients were selected from patients who are under observation at the National Cancer Center, and PLWHA were selected from patients observed at the National Center for Communicable Diseases. The elderly and pregnant women were selected from the vaccinees of the third group.

The third group represented the 18–59 years old, general adult population and was selected from vaccinees in 18 randomly selected vaccination units in Ulaanbaatar city. The second and third groups included attendants from Ulaanbaatar city only.

Anti-SARS-CoV-2 RBD-IgG seroprevalence

We enrolled a total of 1864 vaccinees for measurement of SARS-CoV-2 receptor binding domain (RBD) immunoglobulin class G (IgG) and M (IgM) antibodies before the first dose of the COVID-19 vaccines as baseline. We then collected data and serum samples on days 21–28 after receiving the second dose of the vaccine from 831 vaccinees only (Fig 1).

Fig 1. Flowchart of postvaccine antibody response study.

Fig 1

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A titer of anti-SARS-CoV-2 S-RBD human IgG (Proteintech®, USA) before the first dose and after the second dose administration of vaccines against COVID-19 was measured using Enzyme-linked Immunosorbent Assay (ELISA) in all participants. Anti-SARS-CoV-2 S-RBD human IgM (Proteintech®, USA) titer was measured at the same schedule and the measurement was used to determine ongoing or previous coronavirus infection. According to the manufacturer’s instruction titer of anti-SARS-CoV-2 RBD-IgG ≥ 6.25 ng/mL and/or titer of anti-SARS-CoV-2 RBD-IgM antibody ≥ 6.25 ng/mL before the first dose administration were considered as previous or ongoing coronaviral infection [24,25]. We considered seroconversion when the ratio of IgG antibody titer measured after the second dose to those measured before vaccination was found equal to or higher than 4.0 and showed a titer value ≥ 6.25 ng/mL.

Ethics statement

Study protocol and consent forms were reviewed and approved by the Ethical Review Committee under the Ministry of Health, under resolution no. 216, 217, and 219 from 6 April 2021.

Statistical analysis

We performed both descriptive and inferential statistics. The distribution of seroprevalence among population subgroups was compared by Pearson’s Chi-square test. The mean of variables, its standard deviation, and 95% confidence intervals were compared using analysis of variance (ANOVA). Protective antibody titer was compared using geometric mean titer (GMT) and geometric standard deviation (GSD). The predictive value of age for seroconversion was analyzed by receiver operating characteristics (ROC) analysis. In the ROC table, the Youden index (J) is calculated first, then the optimal cut-point (OCP) corresponds to the maximum value of the Youden index, sensitivity, and specificity of predictiveness. Logarithmic regression analysis was used for detecting an association between age and antibody titer. Statistical significance was expressed using p-values of < 0.05, < 0.01, < 0.005, and < 0.001.

Results

Study population

Sociodemographic, potential risk for developing severe illness, and vaccine-type information of study participants by two stages of observation are shown in the Table 1.

Table 1. Sociodemographic, severe illness risk, and vaccine-type characteristics of study participants.

Characteristics of participants Before 1st dose
(n = 1864)		 After 2nd dose
(n = 831)
Sex, count (percent)
     Males 692 (37.3) 314 (37.8)
     Females 1164 (62.7) 517 (62.2)
Age (years)
     Mean (M ± SD) 40.9 ± 14.3 41.5 ± 14.0
     Median 38.0 39.0
     CI 95 40.2–41.5 40.6–42.5
     Min.–Max. 18–93 18–93
Age group, count (percent)
     < 20 31 (1.7) 16 (1.9)
     20–29 403 (22.0) 151 (18.2)
     30–39 554 (30.3) 254 (30.6)
     40–49 376 (20.5) 181 (21.8)
     50–59 261 (14.3) 135 (16.2)
     60–69 130 (7.1) 66 (7.9)
     ≥ 70 75 (4.1) 28 (3.4)
Population groups, count (percent)
Urban * 1152 (63.0) 520 (62.6)
Rural (aimags)
     Bayankhongor 119 (17.6)
     Bulgan 128 (18.9) 122 (39.2)
     Darkhan-Uul 70 (10.3) 50 (16.1)
     Dornod 120 (17.7) 97 (31.2)
     Dundgovi 121 (17.8)
     Orkhon 120 (17.7) 42 (13.5)
     Subtotal† 678 (37.0) 311 (37.4)
Frontline employees
     Employees working in “red-label” facilities‡ 559 (60.0) 150 (38.8)
     Employees working in “yellow-label” facilities 373 (40.0) 237 (61.2)
     Subtotal† 932 (50.2) 387 (46.6)
Population with increased risk
     SAD^ 134 (25.8) 95 (42.0)
     Cancer^ 88 (17.0) 20 (8.8)
     PLWHA 68 (13.1) 60 (26.5)
     Elderly 119 (22.9) 48 (21.2)
     Pregnant 110 (21.2) 3 (1.3)
     Subtotal† 519 (28.0) 226 (27.2)
General population $ † 405 (21.8) 218 (26.2)
Vaccine types
     AstraZeneca (ChAdOx1-S) 147 (7.9) 35 (4.2)
     Pfizer/BioNTech (BNT162b2) 403 (21.6) 199 (23.9)
     Sinopharm (BBIBP-CorV) 1240 (66.5) 587 (70.6)
     Sputnik V (Gam-COVID-Vac) 74 (4.0) 10 (1.2)
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*-residents of Ulaanbaatar city and suburban area

†-subgroup percentage was calculated within groups and the group subtotal percentage was calculated from the total number of participants

‡-employees working in direct contact with COVID-19 patients (included medical doctors, nurses, nurse assistants serving COVID-19 patients, radiologists, laboratory technicians collected samples, ambulance drivers and hospital porters, ward serving personnel, health officers from the emergency ward, and epidemiologists)

⁋-employees working without direct contact with patients (included police and security officers, officers of emergency service, personnel of hospital kitchen, inspectors, and administrative and service workers)

^-patients received corticosteroids due to systemic or autoimmune diseases and patients passed chemo- or radiation therapy due to solid cancer (time after last therapy < 6 months)

$-population aged 18–59 years; Abbreviations: M, mean; SD, standard deviation; CI95, confidence interval of 95%; Min.–Max., lowest and highest values; SAD, patients passed immunosuppressive therapy due to systemic or autoimmune diseases; PLWHA, People Living with Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome.

Previous or ongoing infection

In 31 of 1864 vaccinees, we found previous (anti-SARS-CoV-2 RBD IgG ≥ 6.5 ng/mL; n = 15) or ongoing (anti-SARS-CoV-2 RBD IgG and anti-SARS-CoV-2 RBD IgM ≥ 6.5 ng/mL; n = 12) SARS-CoV-2 infection before the first dose and thus excluded from the analysis. The remaining 1883 vaccinees data were used for further analysis.

Seroconversion rate after two doses of vaccine

We found at least a 4-fold increased titer of anti-SARS-CoV-2 RBD-IgG antibody in 705 (84.8%) of 831 vaccinees in 21–28 days (26.2 ± 3.3 days) after administration of the second dose of vaccine. We did not detect an increase of titer more than 4-fold in 97 vaccinees (15.2%) and classified them as non-responders. Seroconversion rates according to population groups and vaccine types are shown in Fig 2.

Fig 2. Post-vaccine anti-SARS-CoV-2 RBD-IgG antibody response rate in various population groups.

Fig 2

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A. Seroconversion rate according to the sex of vaccinees; B. Seroconversion rate according to the age of vaccinees; C and D. Seroconversion rate according to the residence of vaccinees; E. Seroconversion rate according to vaccination priority population (Here, Frontline workers–medical and health professionals and government employees working in the frontline of a fight against infection; Increased risk population–immunocompromised and aged people who may develop severe COVID-19 disease in case of infection; and General population–people aged 18–59 years without increased risk); F. Seroconversion rate according to the professional risk of frontline employees; G. Seroconversion rate according to increased risk population subgroups; and H. Seroconversion rate according to vaccine types. Notes: n, count of vaccinees; %, percentage of vaccinees; p, asymptotic significance (two-sided); Abbreviation: SAD, patients received immunosuppressive therapy due to systemic or autoimmune disorders; PLWHA, people living with HIV and AIDS.

We did not find significant differences in seroconversion rates of population groups stratified by sex, age, permanent residence, and professional risk of medical and healthcare professionals and government employees working in the frontline (Fig 2A–2C and 2F). The seroconversion rate in urban and rural vaccinees was in the approximately same range, however, it was significantly varied according to aimags despite all rural residents being vaccinated with the same type of vaccine—Sinopharm BBIBP-CorV (Fig 2D). Seroconversion rates according to priority population for vaccination and risk for severe diseases varied significantly (Fig 2E and 2G). Sputnik V vaccine receivers have shown an absolute response of 100.0%, actually, we observed very few vaccinees in this group (n = 10). Pfizer BNT162b2 vaccine receivers have shown the high rate (97.0%) of positive response, while the population vaccinated with the Sinopharm BBIBP-CorV and the ChAdOx1-S vaccines demonstrated an approximately same a same rate of seroconversion (80.0% and 80.7%, respectively) (Fig 2H).

Vaccinees of different age groups did not show a significant variation in seroconversion rate (Fig 2B), however, ROC analysis of the age of vaccinees stratified by seroconversion showed an increased probability of people aged ≥ 36 years to not respond to the vaccine exposure (Fig 3A). Furthermore, the age-dependent decline in seroconversion was significant for vaccinees who received the Sinopharm BBIBP vaccine (Fig 3B), but not those who received other types (p > 0.05).

Fig 3. ROC curve of the age of vaccinees stratified by the seroconversion.

Fig 3

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A. ROC curve of the age of all vaccinees; B. ROC curve of age in vaccinees received the Sinopharm BBIBP vaccine. AUC, Area under the curve; OCP, optimal cut-point; p, asymptotic significance.

The titer of protective antibodies in vaccinees with the seroconversion

The mean titer of anti-SARS-CoV-2 RBD-IgG antibodies in vaccinees who showed seroconversion was 0.12 ± 0.15 ng/mL (CI95 0.11–0.13; median 0.1) before the vaccine administration and reached 111.8 ± 116.3 ng/mL (CI95 104.9–118.7; median 81.9) following to second dose. The geometric mean titer (GMT) of anti-SARS-CoV-2 RBD-IgG increased from 0.13 ± 0.09 ng/ml before vaccination to 69.9 ±17.6 ng/ml after two shots of vaccine, respectively. A comparison of GMT value after two doses of the vaccine in various population groups is shown in Table 2.

Table 2. The geometric mean titer of anti-SARS-CoV-2 RBD-IgG antibody after two doses of vaccine against COVID-19 in vaccinees with seroconversion.

Population groups n GMT ± GSD Significance (p)*
Total 705 69.9 ± 17.6
Sex Males 264 65.4 ± 17.0 < 0.05
Females 441 72.8 ± 18.0
Age groups < 20 15 43.6 ± 14.7 < 0.05
20–29 133 64.1 ± 16.5
30–39 222 68.9 ± 16.6
40–49 150 76.1 ± 17.3
50–59 111 74.9 ± 18.2
60–69 56 75.2 ± 22.4
≥ 70 18 60.5 ± 22.6
Residence Urban 435 85.6 ± 18.5 < 0.001
Rural (aimags) 270 50.5 ± 14.3
Bulgan 97 35.0 ± 12.4 < 0.001
Darkhan-Uul 50 68.4 ± 13.2
Dornod 82 49.7 ± 13.8
Orkhon 41 85.3 ± 13.7
Priority groups Frontline workers 346 58.2 ± 15.5 < 0.001
Population with increased risk 209 136.9 ± 16.5
General adult population 150 41.8 ± 14.7
Professional risk of frontline employees Employees of “Red-label” facilities 215 61.4 ± 14.3 > 0.05
Employees of “Yellow-label” facilities 131 56.4 ± 11.4
Population with increased risk of developing severe disease SAD 93 180.7 ± 11.5 < 0.001
Cancer patients 20 219.7 ± 7.9
PLWHA 59 165.6 ± 6.0
Elderly 34 34.5 ± 23.5
Pregnant 3 159.8 ± 8.0
Vaccine types AstraZeneca (ChAdOx1-S) 28 88.2 ± 12.1 < 0.001
Pfizer (BNT162b2) 193 192.5 ± 9.0
Sinopharm (BBIBP-CorV) 474 45.7 ± 15.6
Sputnik V (Gam-COVID-Vac) 10 63.4 ± 21.4
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*- statistical significance calculated using ANOVA. Abbreviations: Ng/mL, nanogram per millimeter; GMT, geometric mean titer; GSD, geometric standard deviation; SAD, patients passed immunosuppressive therapy due to systemic or autoimmune diseases; PLWHA, People Living with Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome.

GMT demonstrated significant variation according to the sex, age, residence of vaccinees, targeted priority population, types of pathology or conditions increasing the risk for severe disease, and vaccine types. However, the sex and professional risk of frontline employees did not had a significant difference in GMT.

We studied the titer of protective antibodies in population groups of vaccinees who received BBIBP-CorV separately and found some significant associations. For instance, female vaccinees immunized with the Pfizer vaccine demonstrated higher levels of protective antibodies compared to males (Fig 4A), and the titer of protective antibodies was found associated with the age of vaccinees who received the Sinopharm vaccine (Fig 4B).

Fig 4. Association of protective antibody titer with sex and age of vaccinees received certain types of vaccines.

Fig 4

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A. ROC curves of anti-SARS-CoV-2 RBD-IgG titer stratified by the sex of vaccinees received the Pfizer vaccine; B. Logarithmic regression between anti-SARS-CoV-2 RBD-IgG titer and age of vaccinees received Sinopharm vaccine. Abbreviations: AUC, Area Under the Curve; OCP, optimal cut-point; p, asymptotic significance; R2, determination coefficient; β, standardized coefficient of regression; p, statistical significance (ANOVA).

Discussion

We found an average protective antibody response of 84.8% (in 705 of 831 vaccinees) in 21–28 days after two doses of the four types of COVID-19 vaccine. In our view, the following factors show an essential impact on postvaccine seroconversion. First, vaccine types likely played a crucial role in the seroprevalence. Seropositivity rate varied significantly by vaccine types showing 80.0% for AstraZeneca ChAdOx1-S; 97.0% for Pfizer BNT162b2; 80.7% for Sinopharm BBIBP-CorV, and 100.0% for Sputnik V Gam-COVID-Vac. Although immunocompromised vaccinees from the population with increased risk for severe COVID-19 disease had received the Pfizer vaccine, 98.5% (192 out of 198) vaccinees in these cohorts demonstrated seropositivity. Seropositivity rates for SARS-CoV-2 (S) IgG after two doses of different types of vaccines are well-described, including AstraZeneca ChAdOx1-S (range 85.7–100.0%) [6,11,14,26,27], Pfizer BNT162b2 (range 93.6–100%) [19–22,28], Sinopharm BBIBP-CorV (range 60.6–99.2%) [6–12,14,15,17,21,27–29], and Sputnik V (range 94.5–100.0%) [27,28,30–32] vaccines.

Second, the age of vaccinees considerably affects seropositivity. We established 36 years as an optimal cut-point for seronegative state prediction. Among similarly designed studies, the majority of studies reported a lower seropositivity rate in elderly vaccines [13,20,22,26,33,34].

Third, the residence of vaccinees might play some role in seroconversion. For instance, in our study, rural residents demonstrated variable seropositivity and mean GMT according to aimags, although they received the same types of vaccines—Sinopharm (BBIBP-CorV).

A high GMT of anti-SARS-CoV-2 (S) IgG (192.5 ± 9.0 ng/mL) have found in vaccinees received Pfizer (BNT162b2) while vaccinees receiving AstraZeneca (ChAdOx1-S) and Sinopharm (BBIBP-CorV) demonstrated the lower GMT (88.2 ± 12.1, 63.4 ± 21 and 45.7 ± 15.6 ng/mL, respectively; p < 0.001). This finding was similar to the results of Sughayer MA (2022), who reported the highest anti-SARS-CoV-2 RBD-IgG response rate and mean titer in vaccinees received Pfizer BNT162b2 followed by vaccinees received AstraZeneca ChAdOx1-S and Sinopharm BBIBP-CorV [16].

We showed two population subgroups among vaccinees who received the BBIBP-CorV vaccine, namely vaccinees aged above 60 years and urban residents, may predict lower titer of postvaccination antibodies. Furthermore, in our study, we observed variable seropositivity and GMT among rural residents, depending on the aimags (provinces), despite receiving the same types of vaccines—Sinopharm (BBIBP-CorV). So far, we cannot give an exclusive explanation of this phenomenon since the sociodemographic pattern of these groups was approximately the same (S1 Table). Association of the seropositivity and titer of protective antibodies after two shot vaccination with sex, age, and residence of vaccinees were reported ambiguous [35,36]. Age was often reported as a predictor of seropositivity in subjects who vaccinated with the BBIBP-CorV vaccine [13,35,37]. We found a 98.2% seropositivity after two shots of the BNT162b vaccine among immunocompromised individuals, including patients who received immunosuppressive therapy and PLWHA. In contrast, seropositivity rates of 77.0–85.2% were reported in cohorts of immunocompromised patients in UK [38], Turkey [34], and USA [39].

Conclusion

In summary, we demonstrate a successful accomplishment of the first stage of the immunization campaign against COVID-19 in Mongolia, with certain high immunogenicity levels found in the population with increased risk for severe disease. Seropositivity and titer of protective antibodies produced following two shots of the SARS-CoV-2 vaccine were associated with the vaccine types, age, and residence of vaccinees.

Study limitation and considerations for further study

Data and serum collection time after two doses of vaccine in this study timely overlayed with the period of strict lockdown measures in the country. Many participants refused further participation in the study because of fear of being infected. For this reason, data and serum samples after complete vaccination were available only yielded in 831 (44.6%) of 1864 eligible vaccinees. However, we suggest our baseline data will be pivotal for a further study concerning the morbidity of vaccinees registered later.

Supporting information

S1 Table. The sociodemographic pattern of frontline employees from different rural sites.

(DOCX)

Click here for additional data file. (14.3KB, docx)

Acknowledgments

We thank the Ministry of Health of Mongolia for its support in conducting the study.

Data Availability

There are ethical restrictions on publicly sharing the minimal data set for this study due to participant privacy concerns. Data are available upon request from the Corresponding Author, and from the Division of Science and Technology, Mongolian National University of Medical Sciences via email (sciencetechnology@mnums.edu.mn), or via phone (+976-7775-7575 (1010)), for researchers who meet the criteria for access to confidential data.

Funding Statement

The authors received no specific funding for this work.

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Decision Letter 0

Paavani Atluri

23 Jun 2023

PONE-D-23-03663RBD-specific antibody response after two doses of different SARS-CoV-2 vaccines during the mass vaccination campaign in MongoliaPLOS ONE

Dear Dr. Tsogtsaikhan Sandag,

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: I find all the parts of the paper correctly written from background to the conclusion and of high quality. Methods are clearly explained. Sample size is proper for this kind of research and enables conclusions to the wider population. Results are clear and correct. Statistical analyses is proper for this kind of research. Discussion is sound and comments various research with comparison to findings of this paper. Limitations are clearly stated. All the data needed to understand the paper are presented in clear and common fashion. English is standard and paper is presented well. I can only extend my congratulations to the authors and my gratitude to the editor for the possibility to review this paper. I have no suggestions to improve this paper.

Reviewer #2: Thank you for inviting me to review this very interesting manuscript, which provides insight into the vaccination roll out in Mongolia. This study shows more granular clinical information than prior studies in this country and focuses specifically on those who are 'naive' to prior infection. Given these two novel features there are some major considerations:

1. Which type of vaccine an individual received was based on which group they were in. High-risk healthcare workers received BBIBP-CorV. Priority groups received vaccination ‘following the arrival of further doses’, presumably BBIBP? (Note in discussion it says these some of this group received Pfizer - Line 189). Pfizer, ChAdOx1, Sputnik became available later when vaccination rollout was expanded to the whole population. Therefore comparison of types of vaccine has major confounders including age (high risk included those over 65 years old) and co-morbidities. These confounders are well described as impacting antibody response, yet the analysis does not account for this when comparing antibody response by vaccine type. It is significantly understated in the authors discussion, which is surprising.

2. The study cohort have been selected on having no prior infection to the first dose. It is unclear how the authors accounted for infection between vaccinations, which again will influence antibody response. If the authors have N-antibody available, they should include this in their analysis. If they don't, this should again be discussed in detail in their discussion and consider how this may impact their findings (e.g., probability of infection in that time window based on transmission risk at the time - note some of this study was conducted during a lockdown).

3. It would be useful to know how exactly participants in the third group were selected (e.g., household based, clinic based...etc). How they were selected, and how it differs to the other groups, may highlight selection bias and would need to be explored in the discussion. I presume selection of group 2 was base done on hospital records? Again, this is not clear.

More specific queries include:

Line 48: Unclear what ‘locally grown cases’ means? Cases that had no clear link to migration?

Table 1: What are ‘red-line’ and ‘yellow-line’ facilities? Can you please provide explanation in caption?

Table 2: Please include use of ANOVA in the statistical analysis part of methods.

Line 210: Can you clarify definition of ‘sociodemographic’ pattern please? It would be interesting to know age distribution, proportion of sex and proportion of co-morbidities between the rural areas and rural vs urban.

I hope my comments has been useful and apologies in advance if I overlooked answers to my queries that are already in the manuscript.

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Reviewer #1: Yes: Vladimir Petrovic

Reviewer #2: Yes: Annalan Mathew Dwight Navaratnam

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PLoS One. 2023 Dec 8;18(12):e0295167. doi: 10.1371/journal.pone.0295167.r002

Author response to Decision Letter 0

13 Jul 2023

Firstly, I would like to inform you that we analyzed all data thoroughly after we submitted the manuscript in early February 2023. And we found 311 participants who were excluded from the analysis due to “not complete” data in primary research units. Many participants were excluded due to insufficient personal information (e.g., unclear ID number, home address, and change in health condition after the first dose). Once we had enough time and no covid restrictions, we connected with participants and clarified their missing personal information. Finally, we added data from 254 participants for the analysis. As a result, some values of our study have to be changed. But these changes were not principal, and the main conclusions remained unchanged.

Answer to Review Comments

Reviewer #1: I find all the parts of the paper correctly written from background to the conclusion and of high quality. Methods are clearly explained. Sample size is proper for this kind of research and enables conclusions to the wider population. Results are clear and correct. Statistical analyses is proper for this kind of research. Discussion is sound and comments various research with comparison to findings of this paper. Limitations are clearly stated. All the data needed to understand the paper are presented in clear and common fashion. English is standard and paper is presented well. I can only extend my congratulations to the authors and my gratitude to the editor for the possibility to review this paper. I have no suggestions to improve this paper.

Answer: Thank you

Reviewer #2: Thank you for inviting me to review this very interesting manuscript, which provides insight into the vaccination roll out in Mongolia. This study shows more granular clinical information than prior studies in this country and focuses specifically on those who are 'naive' to prior infection. Given these two novel features there are some major considerations:

1. Which type of vaccine an individual received was based on which group they were in. High-risk healthcare workers received BBIBP-CorV. Priority groups received vaccination ‘following the arrival of further doses’, presumably BBIBP? (Note in discussion it says these some of this group received Pfizer - Line 189). Pfizer, ChAdOx1, Sputnik became available later when vaccination rollout was expanded to the whole population. Therefore comparison of types of vaccine has major confounders including age (high risk included those over 65 years old) and co-morbidities. These confounders are well described as impacting antibody response, yet the analysis does not account for this when comparing antibody response by vaccine type. It is significantly understated in the authors discussion, which is surprising.

Answer:

Date of arrivals for four types of vaccines:

AstraZeneca - February 23, 2021, and March 12, 2023.

https://www.who.int/mongolia/news/detail/23-02-2021-covid-19-vaccination-rollout-in-mongolia

https://www.unicef.org/mongolia/press-releases/mongolia-welcomes-first-batch-covid-19-vaccines-covax-facility

Sinopharm - February 23, 2021, and April 20, 2021

https://thediplomat.com/2021/05/how-mongolia-made-the-most-of-vaccine-diplomacy

https://asia.nikkei.com/Spotlight/Coronavirus/COVID-vaccines/Mongolia-resumes-vaccinations-as-worst-outbreak-rolls-on

Sputnik V - February 27, 2021, and April 30, 2021

https://news.mn/en/795436/

https://www.capitalsinitiative.org/2021/06/15/covid-19-vaccine-rollout-accelerated-to-all-above-18-years-eligible-in-ulaanbaatar/

Pfizer - June 17, 2021

https://www.unicef.org/mongolia/press-releases/over-84000-pfizer-vaccines-arrive-mongolia-first-batch-25-million-doses#:~:text=Press%20release-,Over%2084%2C000%20Pfizer%20vaccines%20arrive%20in%20Mongolia%2C%20the,batch%20of%202.5%20million%20doses.&text=June%2016%2C%202021%20Ulaanbaatar%20%2D%20Over,batch%20of%202.5%20million%20doses.

As you see, AstraZeneca and Sinopharm vaccines arrived before started mass vaccination, on February 23, 2021. Frontline workers started the vaccination with AstraZeneca, but there were only 14.4 thousand doses of this vaccine. The arrival of the next batch of AstraZeneca was delayed. The Ministry of Health decided to continue the vaccination of frontline employees with the Sinopharm vaccine. So, we have participants who received both vaccines in this group. It is my fault; I did not check the citation source accurately. I corrected the text as follows: “Mongolia received the first batch of the inactivated BBIBP-CorV vaccine from Sinopharm, China, and the non-replicating viral vector vaccines Oxford-AstraZeneca, from India and began immunization in high-risk healthcare workers”

Choice of vaccine type

Citizens of Mongolia had the opportunity to choose the type of vaccine that was available in the immunization unit.

Age and comorbidity impact

All immunocompromised patients or patients who passed immunosuppressive therapy (SAD and Cancer patients) and PLWHA were immunized only with the Pfizer vaccine. 32 out of 48 elderlies received the Sinopharm vaccine.

Additionally, I have performed ROC analysis of age by seroconversion in vaccine-type groups and found a significant impact only in the Sinopharm group. This finding was added to Figure 3 and explained in the text.

2. The study cohort have been selected on having no prior infection to the first dose. It is unclear how the authors accounted for infection between vaccinations, which again will influence antibody response. If the authors have N-antibody available, they should include this in their analysis. If they don't, this should again be discussed in detail in their discussion and consider how this may impact their findings (e.g., probability of infection in that time window based on transmission risk at the time - note some of this study was conducted during a lockdown).

Answer:

I agree with you. We did not provide serological or PCR evidence for infection between shots. The serological investigation was not rational because the Sinopharm vaccine is able to stimulate the production of N-antibodies. We used the following two database to exclude cases of natural infection: 1) we collected information regarding possible natural infections which may occur during the observation by filling out a questionnaire when vaccinees were invited for data and sample collection in days 21 – 28 after second dose. 2) In Mongolia, all new PCR confirmed cases of SARS-CoV-2 infection were registered in the “Gerege” system https://gerege.mn/en/home. This system was connected directly to the database of the Ministry of Health. We have checked all suspicious cases in this database later for exclusion of natural infection from the analysis.

I have added a correction in Figure 1 regarding your comment.

3. It would be useful to know how exactly participants in the third group were selected (e.g., household based, clinic based...etc). How they were selected, and how it differs to the other groups, may highlight selection bias and would need to be explored in the discussion. I presume selection of group 2 was base done on hospital records? Again, this is not clear.

Answer:

Participants in the third group were randomly selected in family doctor’s centers. Vaccine administration units were organized in family doctor centers. Family doctor’s units were randomly selected in two of six urban districts of Ulaanbaatar city. Ulaanbaatar is divided into nine düüregs (usually translated as districts, six districts located in the urban areas, but three districts located in suburban areas), which are further subdivided into khoroos (most often translated as subdistricts). link: https://en.wikipedia.org/wiki/Administrative_divisions_of_Mongolia#:~:text=Ulaanbaatar%20is%20divided%20into%20nine,%2C%20microdistrict%20or%20simply%20district). An explanation according to a selection of participants from group two and three was done in the Methods section.

More specific queries include:

Line 48: Unclear what ‘locally grown cases’ means? Cases that had no clear link to migration?

Answer:

This phrase was cited directly from the reference. I corrected it as “local cases increased gradually”.

Table 1: What are ‘red-line’ and ‘yellow-line’ facilities? Can you please provide explanation in caption?

Answer:

I replaced the word “line” with the word “label”. An explanation of the employees of “red label” and “yellow label” facilities was updated in the caption of the Table 1.

Table 2: Please include use of ANOVA in the statistical analysis part of methods.

Answer:

The use of ANOVA was included in the Statistical Analysis subsection of the Methods section.

Line 210: Can you clarify definition of ‘sociodemographic’ pattern please? It would be interesting to know age distribution, proportion of sex and proportion of co-morbidities between the rural areas and rural vs urban.

Answer:

Here, the term “sociodemographic pattern” was used for frontline employees of different rural sites. This data was shown in newly added S1 Table regarding your comment.

Attachment

Submitted filename: Response to reviwers.docx

Click here for additional data file. (26.2KB, docx)

Decision Letter 1

Ashraful Hoque

10 Nov 2023

PONE-D-23-03663R1RBD-specific antibody response after two doses of different SARS-CoV-2 vaccines during the mass vaccination campaign in MongoliaPLOS ONE

Dear Dr. Sandag,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

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Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

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Reviewer #1: Yes

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: Yes

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Reviewer #1: (No Response)

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I had no comments nor asked for revision. Initial version of the manuscript was already enough to recommend this paper to be accepted. So, i stay with my previous text on the same question.

I find all the parts of the paper correctly written from background to the conclusion and of high quality. Methods are clearly explained. Sample size is proper for this kind of research and enables conclusions to the wider population. Results are clear and correct. Statistical analyses is proper for this kind of research. Discussion is sound and comments various research with comparison to findings of this paper. Limitations are clearly stated. All the data needed to understand the paper are presented in clear and common fashion. English is standard and paper is presented well. I can only extend my congratulations to the authors and my gratitude to the editor for the possibility to review this paper. I have no suggestions to improve this paper.

Answer: Thank you

Reviewer #3: Manuscript shows interesting data related to the COVID-19 immunization in Mongolia, including organization of the vaccination campaign, coverage, seroconversion rates and antibody levels after different types of vaccines and in different groups.

All parts of the manuscript are written in intelligible fashion. Manuscript organization, structure, style and format are in accordance with the submission guidelines.

Introduction provides clear background. Methods, sample size, statistical analyses - all are appropriate and clearly explained. Results are clear. Discussion includes all sound and comments various research with comparison to findings of this paper. Limitations are clearly defined.

In the discussion part, it would be interesting to hear the author's thoughts on the possible reasons for the different seroconversion rates and mean GMT between different aimags, as well as lower titer in urban residents.

The authors provided detailed answers to the reviewers and added all suggested corrections into the appropriate parts of the manuscript.

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Reviewer #1: No

Reviewer #3: No

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Decision Letter 2

Ashraful Hoque

17 Nov 2023

RBD-specific antibody response after two doses of different SARS-CoV-2 vaccines during the mass vaccination campaign in Mongolia

PONE-D-23-03663R2

Dear Dr. Sandag,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Ashraful Hoque

30 Nov 2023

PONE-D-23-03663R2

RBD-specific antibody response after two doses of different SARS-CoV-2 vaccines during the mass vaccination campaign in Mongolia

Dear Dr. Sandag:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Ashraful Hoque

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. The sociodemographic pattern of frontline employees from different rural sites.

    (DOCX)

    Click here for additional data file. (14.3KB, docx)
    Attachment

    Submitted filename: Response to reviwers.docx

    Click here for additional data file. (26.2KB, docx)
    Attachment

    Submitted filename: Response to reviwers.docx

    Click here for additional data file. (26.2KB, docx)

    Data Availability Statement

    There are ethical restrictions on publicly sharing the minimal data set for this study due to participant privacy concerns. Data are available upon request from the Corresponding Author, and from the Division of Science and Technology, Mongolian National University of Medical Sciences via email (sciencetechnology@mnums.edu.mn), or via phone (+976-7775-7575 (1010)), for researchers who meet the criteria for access to confidential data.

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