Evaluation of antibody kinetics and durability in healthy individuals vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China

  1. Hangjie Zhang
  2. Qianhui Hua
  3. Nani Nani Xu
  4. Xinpei Zhang
  5. Bo Chen
  6. Xijun Ma
  7. Jie Hu
  8. Zhongbing Chen
  9. Pengfei Yu
  10. Huijun Lei
  11. Shenyu Wang
  12. Linling Ding
  13. Jian Fu
  14. Yuting Liao
  15. Juan Yang
  16. Jianmin Jiang  Is a corresponding author
  17. Huakun Lv  Is a corresponding author
  1. Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, China
  2. School of Medicine, Ningbo University, China
  3. Xihu District Center for Disease Control and Prevention, China
  4. Shangyu District Center for Disease Control and Prevention, China
  5. Kaihua District Center for Disease Control and Prevention, China
  6. Yuecheng District Center for Disease Control and Prevention, China
  7. Department of Immunization Program, Jiaxing Center for Disease Control and Prevention, China
  8. Longyou District Center for Disease Control and Prevention, China
  9. School of Public Health, Xiamen University, China

Abstract

Background:

Although inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed.

Methods:

We enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests.

Results:

Our results revealed that binding antibody IgM peaked 14–28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The neutralized fraction subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89)–17.8% (16/90).

Conclusions:

Two doses of CoronaVac vaccine resulted in limited protection over a short duration. The inactivated vaccine booster can reverse the decrease of antibody levels to prime strain, but it does not elicit potent neutralization against Omicron; therefore, the optimization of booster procedures is vital.

Funding:

Key Research and Development Program of Zhejiang Province; Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission; Major Program of Zhejiang Municipal Natural Science Foundation; Explorer Program of Zhejiang Municipal Natural Science Foundation.

Editor's evaluation

This study presents important evidence that boosting with the Sinovac Coronavac inactivated vaccine would provide considerable protection from ancestral SARS-CoV-2 in terms of elicited neutralizing antibodies but would offer minimal protection against Omicron subvariants. The evidence supporting the claims of the authors is solid, although using a dilution series instead of one plasma dilution for Omicron neutralization would have strengthened the study. The work will be of very wide interest to the biomedical community and beyond, since it points to the need for a better booster vaccine in China.

https://doi.org/10.7554/eLife.84056.sa0

Introduction

The coronavirus disease 2019 (COVID-19), a global health emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has led to unprecedented global healthcare and economic burdens (Clark et al., 2020). COVID-19 vaccines are indispensable for mitigating this situation and containing the ongoing pandemic, as shown by the decline in new and hospitalized COVID-19 cases since mass vaccination began (Rossman et al., 2021).

Inactivated COVID-19 vaccines, such as CoronaVac and BBIBP-CorV, were proven to be generally safe and effective in adults in several clinical trials (Xia et al., 2022; Xia et al., 2020; Wu et al., 2021) and are widely used in China and abroad. Nevertheless, basic questions remain about the vaccine-induced longevity of immunity in the population and the rate of breakthrough infections (Kim et al., 2021). Several studies have gathered immunogenicity data on antibody kinetics after vaccination and showed that neutralizing titers induced by two doses of inactivated vaccine peaked in month 2 and declined to 33.89% by month 6 (Cheng et al., 2022). However, it is important to provide more data on the enhancement and attenuation of immunological protection after vaccination in real-world studies.

The SARS-CoV-2 variants that have been classified as variants of interest or variants of concern (VOC) by the World Health Organization (WHO) are responsible for multiple waves of infection (Dyson et al., 2021) and the increased concerns about the protection provided by current vaccines (Mlcochova et al., 2021; Altmann et al., 2021). The Omicron (B.1.1.529) variant recently identified in South Africa has spread globally (Karim and Karim, 2021; Viana et al., 2022), raising concerns about the effectiveness of antibody therapies and vaccines to variants with multiple mutations (Flemming, 2022; VanBlargan et al., 2022; Suzuki et al., 2022; Meng et al., 2022). A recent real-world study in Israel suggested that a third dose of BNT162b2 vaccine was highly effective in preventing infection, severe disease, hospitalization, and death (Barda et al., 2021). Booster vaccines reinstate waning immunological memory and expand the breadth of immune responses to SARS-CoV-2 variants (Goldberg et al., 2021; Zhu et al., 2022; Chen et al., 2022; Cao et al., 2021; Planas et al., 2022). Therefore, the provision of booster vaccinations for SARS-CoV-2 is recommended by the WHO and is being implemented for fully vaccinated recipients in China and other countries. However, data are needed on the protective immune responses elicited by the boosters against VOC in mass vaccination campaigns.

We explored the dynamic responses and durations of antibodies against SARS-CoV-2 in individuals within 1 year of being vaccinated with an inactivated COVID-19 vaccine and speculated on the protection provided based on the attenuation of neutralizing antibody levels. Furthermore, we evaluated the presence of neutralizing antibodies against Delta and Omicron in volunteers boosted with a third dose of inactivated vaccine.

Materials and methods

Study design and participants

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The cross-sectional investigation was conducted in five counties of Zhejiang Province, mainland China (Xihu, Yuecheng, Shangyu, Kaihua, and Longyou Districts), after nationwide COVID-19 vaccinations from May to October 2021. Potential participants aged 18–59 years who had no prior vaccinations or were vaccinated with one or two doses of CoronaVac (Sinovac Life Sciences, Beijing, China) were recruited from the community. Individuals with a history of infection with SARS-CoV-2 (based on epidemic surveillance system) or the use of blood products or immunosuppressive drugs were excluded. We randomly enrolled 1067 volunteers, including those on day 0 (V-0, no vaccination), day 14±2 (V1-14d), and day 28±3 (V1-28d) after the first vaccine dose, and day 30±3 (V2-1m), day 90±7 (V2-3m), day 180±14 (V2–6 m), day 270±14 (V2-9m), and day 365±30 (V2-12m) after the second dose and collected their venous blood samples (3–5 ml) to detect serum antibody levels (Figure 1A). This was not a longitudinal survey, as different subjects were enrolled at each point in time. We employed a questionnaire survey at blood drawing visits to gather demographic information.

Schedule of sample collection.

(A) Cross-sectional survey: a total of 1067 participants aged 18–59 were enrolled in five counties in Zhejiang, China. The participants had no previous vaccination or were vaccinated with one or two doses of CoronaVac. Venous blood (3–5 ml) was collected on day 0 (V-0, no vaccination), day 14±2 (V1-14d), and day 28±3 (V1-28d) after the first dose, and day 30±3 (V2-1m), day 90±7 (V2-3m), day 180±14 (V2-6m), day 270±14 (V2-9m), and day 365±30 (V2-12m) after the second dose. (B) Prospective cohort study: 90 healthy adults aged 18–80 years in Jiaxing city were recruited and administered 4 µg/0.5 mL of CoronaVac following a 3-shot vaccine schedule 28 days and 6 months apart. Following that, venous blood was collected from recipients at five timepoints: day 0 (Pre-V, before vaccination), day 30±3 (V2-1m), day 90±7 (V2-3m), and day 180±14 (V2-6m) after the second dose, and day 30±3 (V3-1m) after the third dose.

In the prospective cohort study, we recruited 90 healthy adults aged 18–80 years from Jiaxing city, Zhejiang, in June 2021. The main exclusion criteria included previous or later SARS-CoV-2 infection; allergy to any ingredient included in the vaccine; those who had received any blood products or any research medicines or vaccines in the past month; those who had uncontrolled epilepsy or other serious neurological diseases, acute febrile disease, acute onset of chronic diseases, or uncontrolled severe chronic diseases; and those who were unable to comply with the study schedule. Subjects were administered 4 µg/0.5 mL of CoronaVac following a 3-shot vaccine schedule 28 days and 6 months apart. Following that, venous blood (3–5 ml) was collected from recipients at five time points: day 0 (Pre-V, before vaccination), day 30±3 (V2-1m), day 90±7 (V2-3m), and day 180±14 (V2-6m) after the second dose, and day 30±3 (V3-1m) after the third dose (Figure 1B).

SARS-CoV-2-specific IgG and IgM assay

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The commercial detection kit iFlash-2019-nCoV NAb assay (Shenzhen YHLO Biotech Co. Ltd., Shenzhen, China) was employed to measure the levels of IgG and IgM against SARS-CoV-2 spike glycoprotein (S) and nucleocapsid protein (N) by chemiluminescence immunoassay. Briefly, serum samples were allowed to form a complex with SARS-CoV-2 S- and N-protein antigen-coated paramagnetic microparticles, then an acridinium-ester-labeled ACE2 conjugate was added to competitively combine with the particles, forming another reaction mixture. The analyzer converted relative light units (RLUs) into an antibody titer (AU/mL) through a two-point calibration curve. An inverse relationship existed between the amount of SARS-CoV-2 NAb in the sample and the RLUs detected by the iFlash optical system. According to the manufacturer, titers of ≥10.0 AU/mL and ≥1.0 AU/mL are considered positive (or reactive) for IgG and IgM, respectively. IgG and IgM against SARS-CoV-2 receptor binding domain (RBD) were detected using a commercial ELISA kit (Bioscience Biotech Co. Ltd., Chongqing, China). The positive cutoff values for RBD-specific IgG and IgM antibodies were defined as titers of ≥1.0 AU/mL. All tests were performed according to the manufacturer’s protocols (Chan et al., 2021; Li et al., 2021).

Live virus neutralization antibody assays

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The levels of neutralizing antibodies to live SARS-CoV-2 were assessed by the reduction in the cytopathic effect (CPE) in Vero cells with infectious SARS-CoV-2 strain 19nCoVCDC-Tan-HB01 (HB01) in a BSL-3 laboratory (Zhang et al., 2021). Briefly, serum samples were heat-inactivated for 30 min at 56 °C and successively diluted from 1:4 to the required concentration in a twofold series. An equal volume of challenge solution containing 100 TCID50 virus was added. After neutralization in a 37 °C incubator for 2 h, a 1.5–2.5×105 /ml cell suspension was added to the wells. The CPE (cytopathic effect) on VeroE6 cells was analyzed at 4 days post-infection. NT50 (50% neutralization titer, the reciprocal of the highest dilution protecting 50% of the cells from virus challenge) was used to show the neutralization titers. NT50 above 1:4 was defined as positive.

Pseudovirus-based neutralization test

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Serum samples were also quantified for their content of SARS-CoV-2-neutralizing antibodies to wildtype (Wuhan), Delta (B.1.617.2), and Omicron (B.1.1.529) using the pseudovirus-based virus neutralization test (Nie et al., 2020). Briefly, serum samples and a positive or negative reference sample were each diluted 50 times with phosphate-buffered saline combined with 50 µl of pseudovirus diluent per well in a 96-well plate. The mixed sample/pseudovirus was incubated at 37 °C and 5% CO2 for 1 hr. A 2×105 /ml BHK-21-ACE2 cell suspension was added to each well of the plate containing the sample/pseudovirus mixture, then the plate was incubated in a 37 °C and 5% CO2 cell incubator for 48 hr. Finally, the number of green-fluorescence-protein-positive cells per well was read with a porous plate imager (Tecan, Shanghai, SparkCyto). The results were determined by comparing the neutralized fraction using the following calculation: (1 – (fluorescence value of each well/average virus control value))×100% (Karaba et al., 2022). At least four wells were left blank for calibration to 0% inhibition.

Statistical analysis

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Sex, age, BMI, and other clinical characteristics were collected for each vaccination recipient. We used the medians and interquartile ranges (IQR) for age, and numbers (percentages) for categorical variables. Specific binding antibodies against SARS-CoV-2 (IgG, IgM) and neutralized fraction of SARS-CoV-2-neutralizing antibodies are presented as mean ± standard error (SEM). Neutralizing antibodies are presented as geometric mean titers (GMT), and their 95% confidence interval (CI) was calculated with Student’s t distribution on log-transformed data and then back-transformed. Comparisons of titer-level differences between the two groups were performed using the paired Student’s t-test. One-way analysis of variance (one-way ANOVA) was used to analyze the differences between the mean values at different timepoints. Correlations between NAb titers, neutralized fraction, and IgG/IgM levels were evaluated by Pearson’s correlation coefficient. Statistical tests were two-sided, and we considered p-values of less than 0.05 as statistically significant. All statistical analyses were conducted in SPSS 18.0 (IBM Corporation, Armonk, NY, USA) and GraphPad Prism 9 (San Diego CA, USA).

Results

Study participant characteristics

We conducted a cross-sectional survey and recruited 1067 volunteers who had no vaccination or were vaccinated with one or two doses of CoronaVac in October 2020 or later in this multicenter study. Participants ranged in age from 18 to 59 years, with a median age of 40 years (IQR, [32-48]), and there was a balanced distribution of males (43.3%) and females (56.7%). Samples were collected at eight timepoints, including V-0 (n=91), V1-14d (n=125), and V1-28d (n=91) after vaccination with the first dose and V2-1m (n=100), V2-3m (n=110), V2-6m (n=160), V2-9m (n=190), and V2-12m (n=200) after vaccination with the second dose (Figure 1A). Demographic data for the vaccine recipients are summarized in Table 1.

Table 1
Baseline characteristics and anti-S/N antibody levels in the cross-sectional study.
V-0N=91V1-14dN=125V1-28dN=91V2-1mN=100V2-3mN=110V2-6mN=160V2-9mN=190V2-12mN=200
Median age (IQR), years38(31,47)39(34,47)38(31,47)40(32,50)41(33,55)41(31,48)41(31,48)41(34,49)
Sex
Male3745374954808575
Female548054515680105125
IgM
Concentration (AU/ml)0.4±0.025.1±1.05.1±0.91.4±0.20.4±0.10.3±0.040.3±0.040.2±0.03
Seropositivity (%)3.357.675.833.03.64.44.72.0
IgG
Concentration (AU/ml)0.6±0.13.7±0.564.3±5.879.7±5.729.4±2.410.5±0.98.9±1.06.8±0.9
Seropositivity (%)0.07.297.897.088.232.522.113.5
  1. Data are n (%) or median (IQR), or mean  ± SEM. The seropositivity rate is when positive concentration of anti-S/N antibody is 10.0 AU/mL (IgG) and ≥1.0 AU/mL (IgM) or more.

Table 1—source data 1

Baseline characteristics and anti-S/N antibody levels in the cross-sectional study.

https://cdn.elifesciences.org/articles/84056/elife-84056-table1-data1-v2.xlsx

In the prospective cohort study, we recruited 90 healthy adults who met all inclusion criteria and no exclusion criteria, including 40 (44.4%) males and 50 (56.6%) females with a median age of 64 years (IQR, [39-70]), 33.3% of whom had a BMI of ≥24.0 kg/m2, and 33.3% had ≥1 underlying comorbidity (most commonly hypertension and diabetes) (Table 2). The participants were administered a standard dose of the CoronaVac vaccine on days 0 and 28 and a booster dose after month 7. Blood samples were collected at study visit 0 (Pre-V) before vaccination; visit 1 (V2-1m), visit 2 (V2-3m), and visit 3 (V2-6m) after vaccination with the second dose; and visit 4 (V3-1m) after the third dose (Figure 1B). None of participants had a history of laboratory-confirmed SARS-CoV-2 infection.

Table 2
Baseline characteristics for the prospective cohort.
N=90P (%)
Age group (years)
18–442831.1
45–642123.3
65–804145.6
Sex
Male4044.4
Female5055.6
BMI (kg/m2)
<18.533.3
18.5–23.95763.4
≥243033.3
Chronic conditions
Yes3033.3
No6066.7
Table 2—source data 1

Baseline characteristics for the prospective cohort.

https://cdn.elifesciences.org/articles/84056/elife-84056-table2-data1-v2.xlsx

Dynamics of antibody responses to primary vaccination

To explore the dynamic changes in humoral immune responses to the inactivated COVID-19 vaccine, we first evaluated the recipients’ anti-S/N IgM and IgG development at different timepoints (Figure 2A). The titer of anti-S/N-IgM on day 0 increased to 5.1±1.0 AU/ml on day 28 after the first dose, though the seropositivity rate was 57.6%. The seropositivity rates of anti-S/N-IgM reached a peak of 75.8% (5.1±0.9 AU/ml) approximately 28 days after the first dose, while the seropositivity of anti-S/N-IgG reached 97.0% (79.7±5.7 AU/ml) approximately 28 days after the second dose. The titer of anti-S/N-IgM rapidly declined to 1.4±0.2 AU/ml, which is close to the threshold value, 28 days after the second dose, while anti-S/N-IgG declined to 10.5±0.9 AU/ml during month 6 after the second dose. A small percentage of the population still had anti-S/N IgG antibodies, with seropositivity rates of 22.1% and 13.5%, respectively, during months 9 and 12 after the second dose (Table 1).

Anti-SARS-CoV-2-specific IgG and IgM levels induced by inactivated COVID-19 vaccines.

(A, B) Dynamic changes in anti-S/ N- (A) and anti-RBD- (B) specific IgM/IgG in serum samples from CoronaVac-vaccinated participants at V-0, V1-14d, V1-28d, V2-1m, V2-3m, V2-6m, V2-9m, and V2-12m. (C) Correlation between levels of anti-S/anti-N- and anti-RBD-specific antibodies in IgM (left) or IgG (right) at V2-1m. Dates are presented as mean ± SEM. One-way analysis of variance was used for comparison. Correlations were assessed using Pearson’s correlation coefficient. Two-tailed p values were calculated. ns, not significant, * p<0.05, **p<0.01, ***p<0.001.

Figure 2—source data 1

Anti-SARS-CoV-2-specific IgG and IgM levels induced by inactivated COVID-19 vaccines.

https://cdn.elifesciences.org/articles/84056/elife-84056-fig2-data1-v2.xlsx

S protein RBD binding to the angiotensin converting enzyme 2 (ACE2) receptor is a critical initial step in the entry of SARS-CoV-2 into target cells (Zuo et al., 2022). We detected the anti-RBD IgM and IgG levels in the serum samples at several timepoints after the second dose (Figure 2B). The results were similar to those for anti-S/N antibodies, showing peak levels of anti-RBD-IgM (1.8±0.4 AU/ml) and anti-RBD-IgG (18.0±1.6 AU/ml) 1 month after the second dose, after which, the levels of both gradually waned. Furthermore, analysis showed a good correlation between IgM or IgG and anti-S/N and anti-RBD antibodies (R2=0.7364, p<0.001; R2=0.7170, p<0.001, Figure 2C).

Participants were tested with a live virus-based and pseudovirus-based neutralization assay. As depicted in Figure 3A, samples were negative for NAbs at the pre-vaccine baseline, and 87.0% of recipients had a NAb titer greater than 1:4 after the administration of the second dose, along with a GMT of 20.2 (95% CI: 16.3–24.9). Despite the decline observed in month 1, the values did not differ significantly between month 1 and month 3 (p=0.052). However, 12 months after immunization, 35.5% of the population were NAb-positive, with a GMT of 4.1 (95% CI: 3.7–4.5). Additionally, the neutralized fraction for the pseudovirus was significantly elevated (76.2%±1.6, p<0.001) at 1 month after the second dose and decreased slightly thereafter (Figure 3B). Correlation analysis showed poor correlation between NAb titers and anti-S/N IgM (R2=0.014, p=0.243), NAb titers and anti-RBD IgM (R2=0.010, p=0.322), NAb titers and anti-S/N IgG (R2=0.087, p=0.003), neutralized fraction and anti-S/N IgM (R2=0.084, p=0.003), neutralized fraction and anti-RBD IgM (R2=0.048, p=0.028); whereas moderate correlations between NAb titers and anti-RBD IgG (R2=0.121, p<0.001), NAb titer and neutralized fraction (R2=0.135, p<0.001), neutralized fraction and anti-S/N IgG (R2=0.539, p<0.001), neutralized fraction and anti-RBD IgG (R2=0.471, p<0.001).

Neutralizing antibodies induced by inactivated COVID-19 vaccines.

(A, B) Dynamic changes in GMT of NAb titer (A) and neutralized fraction (B) in serum samples from CoronaVac-vaccinated participants at V-0, V2-1m, V2-3m, V2-6m, V2-9m, and V2-12m. (C) Correlation among levels of anti-SARS-CoV-2-IgM and IgG, GMT of NAb titer, and neutralized fraction at V2-1m. One-way analysis of variance was used for comparison. Correlations were assessed using Pearson’s correlation coefficient. Two-tailed p values were calculated. ns, not significant, * p<0.05, **p<0.01, ***p<0.001.

Figure 3—source data 1

Neutralizing antibodies induced by inactivated COVID-19 vaccines.

https://cdn.elifesciences.org/articles/84056/elife-84056-fig3-data1-v2.xlsx

Antibody responses before and after booster immunization

With the dampening of antibody responses to the CoronaVac vaccine, we gave the cohort of 90 individuals booster immunizations up to 6 months after the second dose, and the antibody-titer-level distributions are shown in the violin plot in Figure 4. At month 1 after the second dose, the seropositivity of anti-S/N and anti-RBD IgGs were 96.7% and 100.0% and reached peak levels of 67.4±5.0 AU/ml and 9.4±0.8 AU/ml, respectively. After which point, they slowly diminished over time to 9.4±1.6 AU/ml and 2.8±0.2 AU/ml, respectively, in month 6. Injection of the booster dose stimulated these levels back to 131.3±8.6 AU/ml and 21.7±1.8 AU/ml at month 1 post-booster, 14.0- and 7.8-fold increases from the lowest point, respectively (Figure 4A).

Comparisons of anti-SARS-CoV-2-specific IgG and IgM levels and neutralizing activity before and after booster immunization.

(A, B) Dynamic changes in anti-S/N IgM and IgG (A), GMT of NAb titer, and neutralized fraction (B) in serum samples from CoronaVac-vaccinated participants at V-0, V2-1m, V2-3m, V2-6m, and V3-1m. One-way analysis of variance was used for comparison. Two-tailed P values were calculated. ns, not significant, * p< 0.05, **p < 0.01, ***p < 0.001.

Figure 4—source data 1

Comparisons of anti-SARS-CoV-2-specific IgG and IgM levels and neutralizing activity before and after booster immunization.

https://cdn.elifesciences.org/articles/84056/elife-84056-fig4-data1-v2.xlsx

After the primary two doses and the third booster dose, a similar increasing trend was observed in the two neutralization test results (Figure 4B). The GMT of the NAb titer peaked at 29.4 (95% CI: 23.5–24.2) and dropped to 6.6 (95% CI: 5.4–8.0) at month 6, which was a 4.5-fold attenuation of the peak value, with the total seropositivity dropping from 98.9% to 57.8%. After the booster dose, the GMT increased to 168.2 (95% CI: 139.7–202.6), that is, 25.5-fold higher, at month 6, which was 5.7-fold higher than the first peak. The result showed that the neutralized fraction for the pseudovirus peaked at 72.7% ± 1.6% before gradually decreasing to 21.4% ± 1.7% in month 6 but increased to 84.3% ± 1.7% after the booster.

The levels of antibodies grouped by age (i.e. 18–44 y.o., 45–64 y.o., and≥65y.o.), sex, BMI, and chronic conditions at each monitoring point are presented in Table 3. The Nab titer showed a statistically significant difference among age groups during months 1–6 after the primary vaccination, but there was no significant difference (p=0.369) after the booster dose. Females exhibited a higher NAb titer than males [199.3 (95% CI: 159.2–249.5) vs 136.1 (95% CI: 99.9–185.4), p=0.039] after the booster vaccination. However, there were no statistically significant differences in antibody titer levels between the different BMI or chronic conditions groups.

Table 3
The influence of age to GMT and Seropositivity.
Time pointStatisticTotal18–44 years45–64 years≥65 yearsp
Pre-VGMT2.12.22.12.10.908
95% CI2.0–2.21.9–2.41.9–2.42.0–2.3
Seropositivity (%)3.33.64.82.4
V2-1mGMT29.433.236.824.30.019
95% CI23.5–24.225.3–43.424.3–55.720.0–29.5
Seropositivity (%)98.910095.2100
V2-3mGMT15.522.916.011.5<0.01
95% CI13.3–18.017.0–30.912.5–20.59.4–14.2
Seropositivity (%)95.510095.292.7
V2-6mGMT6.610.27.94.4<0.01
95% CI5.4–8.07.0–14.75.1–12.33.5–5.7
Seropositivity (%)57.882.166.735.6
V3-1mGMT168.2217.2152.3148.70.369
95% CI139.7–202.6165.7–287.797.3–238.5110.7–199.7
Seropositivity (%)100.0100100100
  1. The seropositivity rate is when positive NT50 is above 1:4.

  2. GMT, geometric mean titers.

Antibody responses to Delta and Omicron variants

Mutations in the RBD may lead to a reduction in the antibody neutralization susceptibility of VOC (Liu et al., 2021). We furthermore measured the levels of neutralizing antibodies against the Delta (B.1.617.2) and Omicron (B.1.1.529) variants from serum samples in month 1 after the primary and booster immunizations (Figure 5). Of note, in individuals vaccinated with two doses of the inactivated vaccine, the neutralized fraction for the pseudovirus against the Delta variant and, in particular, the Omicron variant were much lower compared with that against the Wuhan strain (28.4% vs 72.4%, 0.5% vs 72.4%, p≤0.001). However, the booster vaccination gave rise to a slight increase in neutralizing activity against the variants. The neutralized fraction subsequently rose to 36.0% for Delta (p=0.03) and 4.3% (p=0.004) for Omicron after booster dose of inactivated vaccine. The response rate (neutralized fraction >0%) for Omicron rose from 7.9% (7/89) in the primary two doses to 17.8% (16/90) after booster dose. Therefore, our results showed that the booster of Coronavac did not elicit potent neutralization against Omicron BA.1, although booster dose slightly increased antibody responses.

Antibody responses to Delta and Omicron variants.

Neutralized fraction of Wuhan strain, Delta (B.1.617.2), and Omicron (B.1.1.529) variants for CoronaVac primary- and booster-vaccinated participants, as evaluated by pseudovirus-based neutralization test. The paired Student’s t-test and one-way analysis of variance were used for comparison. Two-tailed p values were calculated. * p<0.05, **p<0.01, ***p<0.001.

Figure 5—source data 1

Antibody responses to Delta and Omicron variants.

https://cdn.elifesciences.org/articles/84056/elife-84056-fig5-data1-v2.xlsx

Discussion

Inactivated vaccines have been widely used worldwide, mainly to reduce the COVID-19 severity and hospitalization rate and number of related deaths (Jara et al., 2021; Medeiros-Ribeiro et al., 2021). However, there has been no correlation between immunization and protection or duration of protection demonstrated for inactivated COVID-19 vaccines. Our study of post-vaccination antibody kinetics showed that IgM levels peaked 14–28 days after one dose of CoronaVac, after which point, they declined rapidly. Two doses of the completely inactivated vaccine induced high levels of IgG and neutralizing antibodies, which peaked approximately 1 month after vaccination and declined slightly over time. The vaccine-induced immunity had notably waned to lower levels 6 months later and became undetectable in the majority of individuals 12 months later.

Previous studies have shown that antibody responses usually decline over time after an initial COVID-19 vaccination. Following vaccination with the Pfizer BNT162b2 vaccine, humoral responses were substantially decreased after 6 months among healthcare workers in Israel of 65 years of age or older, especially men (Levin et al., 2021). In addition, a significant trend of declining S-antibody levels was observed following AstraZeneca ChAdOx1 and BNT162b2 administration, with levels reducing by about 5-fold and 2-fold 21–41 days and 70 days or more after the second dose, respectively (Shrotri et al., 2021). It was reported that the immunity provided by inactivated COVID-19 vaccines, such as CoronaVac and Sinopharm/BBIBP, endured for 6 months, with a NAb GMT of 6.8 (95%CI: 5.2–8.8) and 2.31 (95%CI: 2.1–2.6) in month 6 after the two doses and seropositivity of 35% and 61%, respectively (Cheng et al., 2022; Zeng et al., 2022). In our study, the seropositivity and GMT of CoronaVac remained at 57.8% and 6.6 (95% CI: 5.4–8.0), respectively, for 6 months after the primary vaccination, which is comparable to prior reported data on inactivated vaccines (Cheng et al., 2022), although the immunogenicity was lower than that of other types of COVID-19 vaccines. However, the neutralization antibody response levels of different vaccines are difficult to directly compare because of a lack of standardized laboratory methods for SARS-CoV-2 neutralization and differences in experimental conditions (Chen et al., 2021).

We also assessed the dynamics of antibody levels in a small prospective longitudinal cohort 6 months following two vaccination doses and found they were consistent with the above findings. Importantly, a booster injection around 6 months after the primary vaccination activated the anamnestic immunity and raised immune components (such as NAbs) to higher levels. Additionally, several factors, such as age group, sex, obesity, and chronic conditions affecting neutralizing antibody levels, were analyzed. We found that initial and booster-vaccine-elicited neutralizing antibody titers was weaker in older than younger adults, similar to the findings described in many other reports (Meng et al., 2021; Wu et al., 2021; Liao et al., 2022). Even so, Li, et al. showed that among Delta cases, the risk of ≥60 year age group developing pneumonia was 66% lower in the full vaccination age groups compared with no vaccination. And ≥60 year Delta cases the inactivated vaccine booster dose had 86% lower risk of developing pneumonia similar to 18–59 year cases (Li et al., 2022). There is evidence of vaccination-induced protection against severe COVID-19 in people with excess weight or obesity of a similar magnitude to that in people of a healthy weight (Piernas et al., 2022), and we found the COVID-19 neutralizing antibody titer was not associated with bodyweight. The comorbidities had no significant effect on NAb levels in our study, which agrees with another other study that demonstrated that inactivated COVID-19 vaccines had good immunogenicity and safety in older patients with hypertension and/or diabetes mellitus (Zhang et al., 2022). NAbs levels following the CoronaVac booster vaccine was found to have an association with sex, though the BNT162b2 mRNA vaccine was reported to induce higher antibody levels in women than men (Lustig et al., 2021).

The live SARS-CoV2 neutralizing antibody test has been used as a gold standard for evaluating vaccine immunogenicity in clinical trials and has shown correlations with protection from COVID-19 for real-world vaccinations (Gilbert et al., 2022; Khoury et al., 2021). In our study, we compared different methods of detecting the vaccine immunogenicity of serum samples with binding antibodies (IgM/IgG) and live and pseudovirus-based virus neutralizing antibodies. We found the correlations between both anti S/N and RBD IgM and IgG to be very strong. Moreover, the titers of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG or NAbs to pseudovirus; however, NAbs to live SARS-CoV-2 did not correlate well with anti-SARS-CoV-2 IgM levels. This might be attributable to the rapid attenuation of IgM at the incipient stage and its further decrease over time and the contribution of IgG to increases in neutralizing antibody and IgM. Therefore, anti-SARS-CoV-2- IgG and pseudovirus-based neutralizing antibody detection methods can be applied to partly substitute for serological tests of live virus-neutralizing tests.

The Delta variant has eight mutations of the S protein, two of which are within the RBD, while there are 30 spike mutations in Omicron variant BA.1 (Kumar et al., 2022; Zhao et al., 2022). Our results revealed the capability of the SARS-CoV-2 Delta and Omicron variants escaped the antibodies induced by the inactivated vaccine after both primary and booster doses, especially for Omicron with a steep reduction in neutralization. Planas et al. demonstrated that Omicron was able to evade the recognition of most therapeutic monoclonal antibodies completely or partially. Sera from recipients of the Pfizer or AstraZeneca vaccine five months after complete vaccination or COVID-19-convalescent patients collected 6 or 12  months after symptoms, showed low or no neutralizing activity against Omicron (Planas et al., 2022). Although Omicron had a high immune escape rate after inactivated vaccine administration and led to breakthrough infection with severe and fatal cases, a study of the University of Hong Kong revealed that three-dose inactivated vaccine could provide 98.1% protection of severe symptoms and death induced by Omicron in elderly people (>60 years old), and that of the BioNTech vaccine was 98.3% (Zhou et al., 2023; Li et al., 2022).

However, there were some limitations to this investigation. First, the sample size in this study was based on practical considerations rather than statistical power calculations, and the distribution of age and sex were not very well balanced in the study. Second, vaccine efficacy was not calculated, as we did not compare the NAb titers generated by vaccination with those of convalescent COVID-19 patients or a serum standard panel in parallel. Third, we assessed only serum antibody responses, and further evaluations focusing on memory and cellular immunity are needed. Forth, we detected the neutralization activity to Delta and Omicron with pseudovirus-based neutralizing test, only calculated the fraction neutralized at 1:50 plasma dilution (%), not the NT50.

In conclusion, our study suggests that vaccination against SARS-CoV-2 with two doses of CoronaVac can trigger humoral responses in the majority of vaccination recipients aged 18–59 years. Although binding and neutralizing antibodies were still detectable at 12 months post-vaccine, serum antibody levels tended to decrease over time, and Delta and Omicron variants may be able to more efficiently evade the antibodies induced by the inactivated vaccine with time. Despite the booster dose of inactivated vaccine can reverse the decrease of antibody levels to prime strain and heighten the cross immune response to Delta, it does not elicit potent neutralization against Omicron, which is circulating now. So, the optimization of the booster procedure such as heterologous boost immunization using viral-vector-, nucleic-acid-, and protein-based vaccines is necessary.

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files; source data files have been provided on Dryad: https://doi.org/10.5061/dryad.ghx3ffbsw.

The following data sets were generated
    1. Zhang H
    2. Hua Q
    3. NN Xu
    4. Zhang X
    5. Chen B
    6. Ma X
    7. Hu J
    8. Chen Z
    9. Yu P
    10. Lei H
    11. Wang S
    12. Ding L
    13. Fu J
    14. Liao Y
    15. Yang J
    16. Jiang J
    17. Lv H
    (2023) Dryad Digital Repository
    Data for: Evaluation of antibody kinetics and durability in health individuals vaccinated with inactivated COVID-19 vaccine (CoronaVac): a cross-sectional and cohort study in Zhejiang, China.
    https://doi.org/10.5061/dryad.ghx3ffbsw

References

Decision letter

  1. Alex Sigal
    Reviewing Editor; Africa Health Research Institute, South Africa
  2. Neil M Ferguson
    Senior Editor; Imperial College London, United Kingdom
  3. Alex Sigal
    Reviewer; Africa Health Research Institute, South Africa

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, including Alex Sigal as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Neil Ferguson as the Senior Editor.

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

Given the current shift in COVID-19 policy in China from Zero-Covid to minimal restrictions, a major infection wave is taking place. This paper shows that boosting with the Sinovac Coronavac inactivated vaccine would provide considerable protection from the ancestral virus and the no longer circulating Δ variant in terms of elicited neutralizing antibodies. But it would offer minimal protection against Omicron subvariants.

This data (Figure 5) points to the need for a better booster vaccine in China. After careful consideration, the Reviewers agreed that given the time-sensitive nature of the data, the paper can be re-submitted without further experimental work. The authors should ensure that the following points are addressed:

(1) The bottom line, that Coronavac does not elicit potent neutralization against Omicron, should be unequivocally stated.

(2) There are multiple issues with the presentation of the work as outlined by both Reviewers which should be fixed in the revised manuscript. As an example, the meaning of "neutralization inhibition rate" in Figure 5 is critical to understand the figure but is hard to decipher without carefully reading the Materials and methods. The relevant information (e.g. that testing was done at a 1:50 plasma dilution) should be accessible in the figure (e.g., change the axis label to something like "fraction neutralized at 1:50 plasma dilution"). A more standard ID50 would be better if the authors have the serial dilution data.

Reviewer #1 (Recommendations for the authors):

While the paper is an important one, the major weakness is the way the pseudovirus neutralization assays were done. In addition, whether any of the participants were previously infected is unclear.

(1) The pseudovirus neutralization assay is done only at the 1:50 concentration. This weakens the result and presents them in a way that is non-standard to the field. At least for the booster results, a standard dilution series should be performed and a dose-response curve fitted to obtain the ID50. The limit of detection should also be included, and be clearly presented for all figures.

(2) It would be very useful to know what proportion of study participants were previously infected and if there are differences between the previously infected and uninfected individuals. This is clearly complicated by the fact that the vaccine is inactivated virus and therefore discrimination by the presence of anti-nucleocapsid antibodies will not work. However, any clinical record of infection could be used. If none, this should be stated.

(3) Given the data, it is unclear how the authors can conclude on line 260 that: "protective capability of a primary vaccination series is enhanced following booster doses and optimization of the booster procedure" unless they are not talking about their study. The boost doesn't work as far as eliciting neutralizing antibodies against Omicron, which is what is circulating now, and this should be stated outright.

Reviewer #2 (Recommendations for the authors):

Line 115: 'critical' value. Did the authors mean threshold here?

Lines 135-139 are unclear in terms of the exact correlations being tested for.

Line 160 – may be better to use the term 'primary' course of vaccination.

Line 177: I would not use the word unprecedented. Rather could say they have been used widely.

Line 210-212: this does not make sense.

The references omit some of the key papers in the field. Where possible the authors should cite primary sources eg for the emergence of omicron Viana et al., Nature. For comparative biology of spike between omicron and δ, there are a number of possibilities including https://doi.org/10.1038/s41586-022-04462-1, https://www.tandfonline.com/doi/full/10.1080/22221751.2021.2023329, https://doi.org/10.1038/s41586-022-04474-x, and others. Some of the papers also report an increased breadth of neutralisation against omicron with booster doses that should be included in citations and compared to results observed in this study with boosting. https://doi.org/10.1038/s41586-021-04389-z.

In addition, the authors discuss the impact of age on response to vaccines but have not adequately cited papers on vaccine efficacy or in vitro neutralsiation / T cell responses in the elderly. This is clearly a key point for the Chinese population and needs further discussion, especially in light of recent developments in covid control policies.

The rationale for using an assay that detects N and S antibodies together without distinguishing them is unclear and should be addressed. In my view, this is a weakness.

Figure 4 should show data for Delta and Omicron. The data appear to be for WT only.

Table 1: Please define how the positive rate was determined.

Table 3: The 'positive rate' should be defined. Is it a GMT of >20 for example?

Table S2: please define P1 and P2 in the table legend. There should be 95% CI or sd around the inhibition rate %.

Table S3: The 'positive rate' should be defined.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China" for further consideration by eLife. Your revised article has been evaluated by Neil Ferguson (Senior Editor) and a Reviewing Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

The authors partially completed the referee corrections, and this paper does not require an additional round of review. However, the presentation of the work should be corrected before publication.

(1) The most significant result of the study – that the inactivated vaccine booster does not elicit potent neutralizing antibodies against Omicron, should be stated in the abstract.

(2) Title: "Evaluation of antibody kinetics and durability in health subjects…" should be changed to "Evaluation of antibody kinetics and durability in healthy…". Also, the term "subjects" is outdated, and the authors should consider using "individuals" or "participants".

(3) Figure 2: that cross-sectional and not cohort (if that is the case) study participants were analyzed should be stated in the legend. If the participants at each time point are not the same, there should be no connecting lines between points (e.g., a bar graph should be used).

(4) Figure 3A-B: labels on graph missing "2" (e.g., V-1m instead of V2-1m).

https://doi.org/10.7554/eLife.84056.sa1

Author response

Essential revisions:

(1) The bottom line, that Coronavac does not elicit potent neutralization against Omicron, should be unequivocally stated.

Thanks for your great suggestion. We have mortified the description in line 44-45, 347-350. Based on our data, we found Coronavac does not elicit potent neutralization against Omicron after the third dose as the editor' and reviewers' comments. Other studies draw similar conclusions. Li, et al. showed the neutralizing antibody GMTs against the Delta variant at day 14 after the homologous booster was 8.2 (95% CI=6.6, 10.1) with 56% seroconversion (Li, et al. 2022). Fanglei Zuo, et al. showed the 90% neutralization titer (NT90) value against Β, Delta and Omicron VOC was 5, 5 and 5 respectively after homologous booster with inactivated vaccine (Zuo, et al. 2022). However, we considered the method only used the fraction neutralized at 1:50 plasma dilution (%) with pseudovirus-based neutralizing test was less powerful, so we did not emphasize this result unequivocally.

(2) There are multiple issues with the presentation of the work as outlined by both Reviewers which should be fixed in the revised manuscript. As an example, the meaning of "neutralization inhibition rate" in Figure 5 is critical to understand the figure but is hard to decipher without carefully reading the Materials and methods. The relevant information (e.g. that testing was done at a 1:50 plasma dilution) should be accessible in the figure (e.g., change the axis label to something like "fraction neutralized at 1:50 plasma dilution"). A more standard ID50 would be better if the authors have the serial dilution data.

Thanks for your great suggestion on improving the accessibility of our manuscript. We have corrected the y-axis label in figures and figure legends. The multiple issues by both Reviewers we have fixed in the revised manuscript and answered the comments point by point. Due to the few reagents of pseudovirus of Delta and Omicron, we could not detect all samples with the serial dilution. We tried to detect two serum samples by serial dilution showed in Table S2 as a limited reference, but it cannot work because of the different calculated method and observed outcome. Karaba, et al. detected with the similar method (pseudoneutralization/ACE2 inhibition measurement) showed that a cutoff of 20% ACE2 inhibition is associated with measurable live virus–neutralizing antibody, including versus VOCs (Karaba, et al).

Reference

1. Li J, Hou L, Guo X, Jin P, Wu S, Zhu J, et al. Heterologous AD5-nCOV plus CoronaVac versus homologous CoronaVac vaccination: a randomized phase 4 trial. Nat Med. 2022;28(2):401-9.

2. Zuo F, Abolhassani H, Du L, Piralla A, Bertoglio F, de Campos-Mata L, et al. Heterologous immunization with inactivated vaccine followed by mRNA-booster elicits strong immunity against SARS-CoV-2 Omicron variant. Nat Commun. 2022;13(1):2670.

3. Karaba AH, Zhu X, Liang T, Wang KH, Rittenhouse AG, Akinde O, et al. A third dose of SARS-CoV-2 vaccine increases neutralizing antibodies against variants of concern in solid organ transplant recipients. Am J Transplant. 2022;22(4):1253-60.

Reviewer #1 (Recommendations for the authors):

While the paper is an important one, the major weakness is the way the pseudovirus neutralization assays were done. In addition, whether any of the participants were previously infected is unclear.

(1) The pseudovirus neutralization assay is done only at the 1:50 concentration. This weakens the result and presents them in a way that is non-standard to the field. At least for the booster results, a standard dilution series should be performed and a dose-response curve fitted to obtain the ID50. The limit of detection should also be included, and be clearly presented for all figures.

Thanks for your great suggestion. We agree it is a weaken for our study only to calculate the fraction neutralized at 1:50 plasma dilution (%) with pseudovirus-based neutralizing test, not the NT50. We have discussed this limitation in the discussion. We designed the study early in 2021, when there were not many SARS-CoV-2 mutant strains. The primary objective was to evaluate the antibody kinetics and durability to WT after vaccinated with inactivated COVID-19 vaccine. Then with the emergence of Δ and Omicron, we added the detections with limited reagents. The limit of detection we have added in all figures with your professional suggestions.

(2) It would be very useful to know what proportion of study participants were previously infected and if there are differences between the previously infected and uninfected individuals. This is clearly complicated by the fact that the vaccine is inactivated virus and therefore discrimination by the presence of anti-nucleocapsid antibodies will not work. However, any clinical record of infection could be used. If none, this should be stated.

Thanks for your great suggestion. It is very interesting to compare the antibody levels induced by inactivated SARS-CoV-2 in previously infected and uninfected individuals. The participants we recruited were not previous or later SARS-CoV-2 infected. Because our study was conducted from May to December 2021, when China had taken the strict measures to prevent and control the epidemic. Our organization (Zhejiang CDC) had the recorded information of individuals if they had been infected SARS-CoV-2. Meanwhile, the study regions had no large outbreaks and epidemics during that period. We have mortified the descriptions in the methods and results (line 116 and 117).

(3) Given the data, it is unclear how the authors can conclude on line 260 that: "protective capability of a primary vaccination series is enhanced following booster doses and optimization of the booster procedure" unless they are not talking about their study. The boost doesn't work as far as eliciting neutralizing antibodies against Omicron, which is what is circulating now, and this should be stated outright.

Thanks for your great suggestion. The description was not accurate and we have mortified in line 347-350:

“Despite the booster dose of inactivated vaccine can reverse the decrease of antibody levels to prime strain and heighten the cross immune response to Delta, it does not elicit potent neutralization against Omicron, which is circulating now. So, the optimization of the booster procedure such as heterologous boost immunization using viral-vector-, nucleic-acid-, and protein-based vaccines is necessary.”

Reviewer #2 (Recommendations for the authors):

Line 115: 'critical' value. Did the authors mean threshold here?

Yes. Thanks for your great suggestion on improving the accessibility of our manuscript, we have corrected this word.

Lines 135-139 are unclear in terms of the exact correlations being tested for.

Thanks for your great suggestion, we have corrected the description in line 156-167:

“Correlation analysis showed poor correlation between NAb titers and anti-S/N IgM (R2 = 0.014, P = 0.243), NAb titers and anti-RBD IgM (R2 = 0.010, P = 0.322), NAb titers and anti-S/N IgG (R2 = 0.087, P = 0.003), neutralized fraction and anti-S/N IgM (R2 = 0.084, P = 0.003), neutralized fraction and anti-RBD IgM (R2 = 0.048, P = 0.028); whereas moderate correlations between NAb titers and anti-RBD IgG (R2 = 0.121, P < 0.001), NAb titer and neutralized fraction (R2 = 0.135, P < 0.001), neutralized fraction and anti-S/N IgG (R2 = 0.539, P < 0.001), neutralized fraction and anti-RBD IgG (R2 = 0.471, P < 0.001).”

Line 160 – may be better to use the term 'primary' course of vaccination.

Thanks for your great suggestion, we have corrected the descriptions in the full text.

Line 177: I would not use the word unprecedented. Rather could say they have been used widely.

Thanks for your great suggestion, we have corrected the descriptions.

Line 210-212: this does not make sense.

Thanks for your great suggestion, the sentences we described not clearly and have modified in line 250-252:

“We found that initial and booster-vaccine-elicited neutralizing antibody titers was weaker in older than younger adults, similar to the findings described in many other reports.”.

The references omit some of the key papers in the field. Where possible the authors should cite primary sources eg for the emergence of omicron Viana et al., Nature. For comparative biology of spike between omicron and δ, there are a number of possibilities including https://doi.org/10.1038/s41586-022-04462-1, https://www.tandfonline.com/doi/full/10.1080/22221751.2021.2023329, https://doi.org/10.1038/s41586-022-04474-x, and others. Some of the papers also report an increased breadth of neutralisation against omicron with booster doses that should be included in citations and compared to results observed in this study with boosting. https://doi.org/10.1038/s41586-021-04389-z.

Thanks for your great suggestion, we have modified the citations and added discussions about escapes against omicron in line 308-334.

In addition, the authors discuss the impact of age on response to vaccines but have not adequately cited papers on vaccine efficacy or in vitro neutralsiation / T cell responses in the elderly. This is clearly a key point for the Chinese population and needs further discussion, especially in light of recent developments in covid control policies.

Thanks for your great suggestion, we have added the discussions about the vaccine efficacy and vitro neutralization activity in the elderly in line 270-275.

The rationale for using an assay that detects N and S antibodies together without distinguishing them is unclear and should be addressed. In my view, this is a weakness.

We agree that the design is not perfect. There were not many commercial detection kits to choose that time. We additionally considered the inactivated vaccine had full virions, the detection of N and S antibodies together was in place of total viral antibodies, and we also detected the RBD antibodies.

Figure 4 should show data for Δ and Omicron. The data appear to be for WT only.

For Δ and Omicron, we only detected the samples of 28 days after the second and third dose (V2-1m and V3-1m). Due to the weaker neutralized fraction to Delta and Omicron, we did note detected samples of other groups. The results showed in Figure 5.

Table 1: Please define how the positive rate was determined.

According to the manufacturer of kits, the concentration anti-S/N antibodies≥10.0 AU/mL (IgG) and ≥1.0 AU/mL (IgM) are considered positive (or reactive); for anti-RBD antibodies, the positive was defined as concentration≥1.0 AU/mL. The positive rate was percent of numbers of positive samples/ total detected samples. We have added the description in the table legends. Thanks for your great suggestion.

Table 3: The 'positive rate' should be defined. Is it a GMT of >20 for example?

The seropositivity rate is when positive titer of NT50 is above 1:4 and descripted in the methods. Thanks for your great suggestion, we have added the description in the table legends.

Table S2: please define P1 and P2 in the table legend. There should be 95% CI or sd around the inhibition rate %.

Thanks for your great suggestion. We have added the description in the table S2 legends. P1 and P2 means serum sample of person1 and person2. The samples were conducted with the serial dilution from 1:100 and tested with pseudovirus-based neutralization. We only detected with 1 complex well that 95% CI or sd around the inhibition rate % were valueless.

Table S3: The 'positive rate' should be defined.

We have added the description in the table S3 legends. Thank you very much for your valuable revision suggestions.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

The authors partially completed the referee corrections, and this paper does not require an additional round of review. However, the presentation of the work should be corrected before publication.

(1) The most significant result of the study – that the inactivated vaccine booster does not elicit potent neutralizing antibodies against Omicron, should be stated in the abstract.

Thanks for your great suggestion. We have mortified the description in line 44-45, 347-350.

(2) Title: "Evaluation of antibody kinetics and durability in health subjects…" should be changed to "Evaluation of antibody kinetics and durability in healthy…". Also, the term "subjects" is outdated, and the authors should consider using "individuals" or "participants".

Thanks for your great suggestion. We have corrected the title to “Evaluation of antibody kinetics and durability in health individuals vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China

(3) Figure 2: that cross-sectional and not cohort (if that is the case) study participants were analyzed should be stated in the legend. If the participants at each time point are not the same, there should be no connecting lines between points (e.g., a bar graph should be used).

Thanks for your great suggestion on improving the accessibility of our manuscript. We have corrected in the Figure 2.

(4) Figure 3A-B: labels on graph missing "2" (e.g., V-1m instead of V2-1m).

Thanks for your great suggestion. It was my mistake and we have corrected in the Figure 3A-B.

https://doi.org/10.7554/eLife.84056.sa2

Article and author information

Author details

  1. Hangjie Zhang

    Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Software, Formal analysis, Writing - original draft
    Contributed equally with
    Qianhui Hua
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7334-2536
  2. Qianhui Hua

    School of Medicine, Ningbo University, Ningbo, China
    Contribution
    Formal analysis
    Contributed equally with
    Hangjie Zhang
    Competing interests
    No competing interests declared
  3. Nani Nani Xu

    Xihu District Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  4. Xinpei Zhang

    Shangyu District Center for Disease Control and Prevention, Shaoxing, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  5. Bo Chen

    Kaihua District Center for Disease Control and Prevention, Quzhou, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  6. Xijun Ma

    Yuecheng District Center for Disease Control and Prevention, Shaoxing, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  7. Jie Hu

    Department of Immunization Program, Jiaxing Center for Disease Control and Prevention, Jiaxing, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  8. Zhongbing Chen

    Longyou District Center for Disease Control and Prevention, Quzhou, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  9. Pengfei Yu

    Department of Immunization Program, Jiaxing Center for Disease Control and Prevention, Jiaxing, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  10. Huijun Lei

    Longyou District Center for Disease Control and Prevention, Quzhou, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  11. Shenyu Wang

    Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Resources
    Competing interests
    No competing interests declared
  12. Linling Ding

    Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Data curation, Formal analysis, Project administration
    Competing interests
    No competing interests declared
  13. Jian Fu

    Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Data curation, Project administration
    Competing interests
    No competing interests declared
  14. Yuting Liao

    School of Public Health, Xiamen University, Xiamen, China
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared
  15. Juan Yang

    School of Public Health, Xiamen University, Xiamen, China
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
  16. Jianmin Jiang

    Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Funding acquisition, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    jmjiang@cdc.zj.cn
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3563-4006
  17. Huakun Lv

    Department of Immunization Program, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
    Contribution
    Funding acquisition, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    hklv@cdc.zj.cn
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3420-6942

Funding

Key Research and Development Program of Zhejiang Province (2021C03200)

  • Hangjie Zhang
  • Nani Nani Xu
  • Bo Chen
  • Yuting Liao
  • Juan Yang
  • Jianmin Jiang
  • Huakun Lv

Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission (WKJ-ZJ-2221)

  • Jianmin Jiang
  • Huakun Lv

Major program of Zhejiang Municipal Natural Science Foundation (LD22H190001)

  • Hangjie Zhang

Explorer Program of Zhejiang Municipal Natural Science Foundation (LQ23H00001)

  • Hangjie Zhang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank the staff from the local CDCs and the local designated hospitals for their help with the field survey. We also sincerely thank professor Xiaofeng Qin in Suzhou Institute of Systematic Medicine for assisting us to detect the pseudovirus-based neutralization antibody. This work was supported by the Key Research and Development Program of Zhejiang Province (2021C03200); the Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission (WKJ-ZJ-2221); the Major Program of Zhejiang Municipal Natural Science Foundation (LD22H190001); the Explorer Program of Zhejiang Municipal Natural Science Foundation (LQ23H100001).

Ethics

We state that we conformed with the Helsinki Declaration of 1975 (as revised in 2008) concerning Human and Animal Rights, and that we followed out the policy concerning Informed Consent as shown on Springer.com. The study protocol and informed consent form were approved by the Medical Ethics Committee of The Zhejiang Center for Disease Control and Prevention (2021-044-01). Written informed consent was obtained from all study participants.

Senior Editor

  1. Neil M Ferguson, Imperial College London, United Kingdom

Reviewing Editor

  1. Alex Sigal, Africa Health Research Institute, South Africa

Reviewer

  1. Alex Sigal, Africa Health Research Institute, South Africa

Version history

  1. Received: October 9, 2022
  2. Preprint posted: November 4, 2022 (view preprint)
  3. Accepted: February 20, 2023
  4. Accepted Manuscript published: March 16, 2023 (version 1)
  5. Version of Record published: April 17, 2023 (version 2)

Copyright

© 2023, Zhang, Hua et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Hangjie Zhang
  2. Qianhui Hua
  3. Nani Nani Xu
  4. Xinpei Zhang
  5. Bo Chen
  6. Xijun Ma
  7. Jie Hu
  8. Zhongbing Chen
  9. Pengfei Yu
  10. Huijun Lei
  11. Shenyu Wang
  12. Linling Ding
  13. Jian Fu
  14. Yuting Liao
  15. Juan Yang
  16. Jianmin Jiang
  17. Huakun Lv
(2023)
Evaluation of antibody kinetics and durability in healthy individuals vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China
eLife 12:e84056.
https://doi.org/10.7554/eLife.84056

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https://doi.org/10.7554/eLife.84056

Further reading

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    The aim of our study was to test the hypothesis that the community contact tracing strategy of testing contacts in households immediately instead of at the end of quarantine had an impact on the transmission of SARS-CoV-2 in schools in Reggio Emilia Province.

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    We analysed surveillance data on notification of COVID-19 cases in schools between 1 September 2020 and 4 April 2021. We have applied a mediation analysis that allows for interaction between the intervention (before/after period) and the mediator.

    Results:

    Median tracing delay decreased from 7 to 3.1 days and the percentage of the known infection source increased from 34–54.8% (incident rate ratio-IRR 1.61 1.40–1.86). Implementation of prompt contact tracing was associated with a 10% decrease in the number of secondary cases (excess relative risk –0.1 95% CI –0.35–0.15). Knowing the source of infection of the index case led to a decrease in secondary transmission (IRR 0.75 95% CI 0.63–0.91) while the decrease in tracing delay was associated with decreased risk of secondary cases (1/IRR 0.97 95% CI 0.94–1.01 per one day of delay). The direct effect of the intervention accounted for the 29% decrease in the number of secondary cases (excess relative risk –0.29 95%–0.61 to 0.03).

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    Prompt contact testing in the community reduces the time of contact tracing and increases the ability to identify the source of infection in school outbreaks. Although there are strong reasons for thinking it is a causal link, observed differences can be also due to differences in the force of infection and to other control measures put in place.

    Funding:

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