{"paper_id":"321c2afa-8a0c-41f6-909a-e775212516b8","body_text":"The Impact of Omicron Infection on Antibody Response and Attenuation: A Six-Month Follow-Up Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Omicron Infection on Antibody Response and Attenuation: A Six-Month Follow-Up Study Yanfei Wu, Shaohua Guo, Suyi Zhang, Weibing Wang, Pengfei Deng, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6653332/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Nov, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted 13 You are reading this latest preprint version Abstract Background Antibody patterns to ssevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are the subject of current study, and the variations in antibodies to Omicron are yet unknown. The study investigated the six-month longitudinal dynamics and influencing factors of antibodies, including IgG, IgM, and neutralizing antibodies (NAbs), in healthcare workers (HCWs) following Omicron infection. Methods HCWs were recruited in Shanghai through multistage sampling, tested positive for SARS-CoV-2, and were followed up six times with blood sampling and questionnaires. The primary endpoints were the titers of the specific NAb against Omicron and the cut off index (COI) of IgG/IgM against Omicron. Antibody decay models were developed based on individual data of participants with single Omicron infection, and statistical analyses were conducted to explore influencing factors using Mann-Whitney U and Kruskal-Wallis tests. Results A total of 710 HCWs were enrolled, with IgG and NAb remaining high for five months but declining significantly in the sixth, but IgM declining rapidly throughout. After the single infection, IgG exhibited a mean short-term increase of 70.07 COI and a long-term elevation of 33.63 COI, with a gradual decline at a rate of − 0.0024 COI per day. IgM demonstrated a transient elevation, with a short-term boost of 23.66 COI and a modest long-term increase of 0.63, followed by a more rapid decay at − 0.0664 COI per day. NAb similarly rose significantly post-infection, with a short-term increase of 295.28 and a sustained long-term elevation of 292.07, declining at a rate of − 0.0021 COI per day. Reinfection occurred in 36.76% of HCWs, boosting antibody levels. Timing between infection and vaccination significantly influenced IgG/IgM waning but not NAbs. No associations were found between antibody decay and demographic or clinical factors. Conclusion While Omicron infection induces robust short-term antibody responses, immunity wanes significantly within six months, and reinfection temporarily boosts antibody levels. The findings highlight the limited durability of natural and hybrid immunity and underscore the need for timely booster vaccinations to sustain protection, particularly in high-risk groups like HCWs. Omicron neutralizing antibodies IgG IgM antibody waning reinfection healthcare workers vaccination timing Figures Figure 1 Figure 2 Figure 3 1 INTRODUCTION The Corona virus disease 2019 (COVID-19) pandemic has evolved with the emergence of multiple variants, among which Omicron has demonstrated the highest transmissibility and immune evasion properties, leading to an unprecedented surge in COVID-19 cases worldwide[ 1 ]. The variant possessed a large number of mutations in the spike protein, reducing the effectiveness of neutralizing antibodies and increasing the likelihood of breakthrough infections[ 2 , 3 ]. While Omicron infections are generally associated with reduced severity compared to previous variants[ 4 ], their high reinfection rates and rapid antibody waning raise concerns about long-term immunity. Consequently, understanding the immune response dynamics following Omicron infection is critical for refining vaccination strategies and mitigating future outbreaks, particularly for healthcare workers (HCWs) who are at high risk of repeated exposure. According to research, IgM, IgG and NAbs against SARS-CoV-2 peaked within one month after COVID-19 symptoms, declined rapidly within 6 months and then maintained a stable state[ 5 – 8 ]. Current research focuses on the antibody trends of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the changes in antibodies to Omicron are still unclear. Therefore, the purpose of this study is to track the dynamics of IgM, IgG, and NAbs in the serum of Omicron-infected HCWs for evaluating the durability of vaccine protection and formulating individualized vaccination strategies. Additionally, an antibody change model will be established to assess the dynamic trend of antibody change following infection to further investigate the parameters of short-term and long-term enhancement and attenuation in antibody levels. Simultaneously, an exploratory investigation was carried out to see how demographic characteristics and vaccination affected the levels of antibodies following infection. 2 METHODS 2.1 Study design and Participants HCWs infected with Omicron between December 19 and 25, 2022, volunteered to participate in the six-month follow-up study, from 64 district-affiliated medical and health institutions (district Centers for Disease Control and Preventions, community health care centers, secondary and tertiary medical institutions) in Pudong New Area, Shanghai. HCWs were enrolled if they tested positive for nucleic acid or SARS-CoV-2 antigen, or they showed early signs of COVID-19, and had no intention of leaving Shanghai within six months. HCWs consent was obtained via 5 mL non-anticoagulated serum tubes containing a venous blood sample. Additionally, online questionnaires ( Supplement file 1 and 2 ) developed for the study on the participants' work, general health, and history of SARS-CoV-2 infection were completed, as was their status of the COVID-19 vaccine, and continuation of COVID-19 symptoms. HCWs were followed up a total of 6 times, with Survey 1 (baseline) from January 31 to February 6, 2023 and follow-up surveys conducted one month (7 days as the time window) after each participant. Every follow-up session requires HCWs to provide blood and complete questionnaires. Blood samples were collected in the study in accordance with the Declaration of Helsinki. The study has been approved by the Medical Ethics Committee of Shanghai Pudong New Area for Disease Control and Prevention. And written informed consent ( Supplement file 3 ) was given by each participating HCW prior to the commencement of the study. The randomization used in the study was multi-stage random sampling. In accordance with the degree of the medical structure in which they were employed, HCWs who contracted COVID-19 between December 19 and December 25, 2022, were split into two tiers (secondary and third-level medical institutions, and community health care centers). Then, based on the likelihood of coming into contact with COVID-19 patients, each institution is divided into low-risk areas (almost no contact with patients: administration, security, etc.), medium-risk areas (no direct contact, but they are exposed to biological samples obtained from patients every day, such as laboratory testing personnel, non-communicable disease related-clinics), and high-risk areas (direct contact with patients or suspected patients: infectious disease-related clinics, wards, etc.). 10 HCWs were randomly selected from each area of 17 secondary and tertiary medical institutions, resulting in a total of 510 HCWs. 3–4 were randomly selected from each area of 47 communities, and a total of about 470 HCWs were selected. The sample size was estimated by using the sample calculation formula comparing the sample rate with the population rate. According to a recent Shanghai COVID-19 case survey that tracked 9,000, the infection rate of HCWs was about 81.6%[ 9 ]. The sample size of the study was 637 with a 10% two-way significance level, 90% power, and an allowable error of 5%. The final sample size was 950, raised by approximately 30% considering the loss of follow-up and the challenges associated with blood collection. 2.2 Experiment IgG, IgM and NAbs to SARS-CoV-2 were quantitatively detected using the magnetic particle chemiluminescence technique. The detection reagents included IgG/IgM Antibody Reagent Test Kits for the Novel Coronavirus 2019-nCoV (BiOSCiENCE, Chongqing, China), and Neutralizing Antibody Reagent Test Kits for the Novel Coronavirus 2019-nCoV (BiOSCiENCE, Tianjin, China). The endpoints were the titers of the specific NAb against Omicron in units of antibody units (AU)/ml, and cut off index (COI) of IgG/IgM against Omicron. The secondary immunogenicity endpoint was the positivity rates of IgG, IgM and NAbs. NAb titers with a concentration of ≥ 2.0 AU/ml were considered positive and vice versa, whereas COI values of ≥ 1.0 were considered positive for IgG/IgM. 2.3 Statistical analysis We used an exponential decay model to simulate the decline in antibody titers. Assuming that an individual contracted Omicron just once, antibody levels would rise rapidly in the early period following infection and then gradually decline to a rather steady level. Short-term immunity was the phase in which antibody levels increased quickly, while long-term immunity was the phase that followed stability. For example, studies have shown that following natural influenza infection, antibody responses are rapidly induced, peaking within approximately 15 days, and then gradually decline, leaving a longer-term response that remains stable for up to one year[ 10 – 13 ]. And researches indicated that Iantibodies reached their peak levels within one month following the infection with SARS-CoV-2, subsequently declining rapidly over the next six months before stabilizing[ 8 ]. Based on the assumption, the following model was constructed[ 13 – 15 ]. The antibody level of an individual was represented by λ(t), which indicated the antibody level t days following the peak. µ 1 and µ 2 represented the antibody levels of long-term immunity and short-term immunity, respectively. The antibody level peaked and then fell exponentially, with the rate of decrease determined by the parameter ω . The parameters µ 1 , µ 2 , and ω were evaluated in the study using data from a single infection as well as data collected prior to a repeat infection, yielding estimated values and 95% confidence interval (CI). Titers of the specific NAb and COIs of IgG and IgM against Omicron were expressed as medians (quartile or interquartile ranges) and subjected to rank sum test analysis,if required, by Dunn's multiple comparison test. Since the data were not normally distributed, the the Mann-Whitney U test for binary variables or the Kruskal-Wallis test for multi-categorical variables were used to assess the association of age, sex, BMI, history of underlying diseases, history of immunosuppressive medication use, previous infection, and the interval between the date of infection and the last day of vaccination on antibody waning (defined as relative decline; [X(final antibody COI or titer) − X(baseline COI or titer)]/X(baseline COI or titer)×100). With 5% as the default significance threshold, all statistical tests were two-way. Unless specified differently in the analytic description, all CIs were presented as 95%. GraphPad Prism 9.0, SAS 9.4, and R 4.3.3 were used for statistical analysis. 3 RESULTS 3.1 Demographic characteristics A total of 1186 HCWs were recruited and screened for eligibility (Fig. 1 ). 207 HCWs were excluded, including 162 individuals who met the exclusion criteria, 10 individuals who uncollected blood, and 35 individuals who withdrew consent. 710 HCWs were ultimately included in the study after 238 were lost to follow-up after six follow-up visits, 15 revoked their informed permission, and 16 uncollected blood. The 710 HCWs who participated in the study had a median age of 38 (IQR: 33–45 years), 165 males and 545 females, with a male to female ratio of 0.30:1. And the mean body-mass index (BMI) of HCWs was 23.34 kg/m 2 (IQR: 20.81–24.91 kg/m 2 ). Among 710 HCWs, 693 (97.61%) have been infected with Omicron in the past, and 622 (87.61%) had underlying medical conditions (chronic lung illness, diabetes, renal disease, liver disease, malignancies, etc.). Out of the total research participants, only 12 (1.69%) had a history of prolonged use of immunosuppressive medications. And the interval between the date of infection and the last day of vaccination was less than 14 days for 313 (44.08%), more than 180 days for 371 (52.25%), 14 to 180 days for 15 (2.11%), and not vaccinated for 11 (1.55%). Besides, 261 (36.76%) individuals contracted Omicron again within the 6-month follow-up period, including 134 (18.87%) at Survey 5 and 127 (17.89%) at Survey 6. 3.2 Model of antibody degradation The 449 HCWs with only a single Omicron infection were found to maintain a high COI for IgG with no statistical difference in the first five months and a significant decrease in the sixth month compared to the first follow-up after six months (Fig. 2 (A) ). And there were the high rates of IgG positivity within the six-month follow-up (all higher than 98%). The COIs in IgM remained low throughout the six-month follow-up with low positivity rates (less than 20%) (Fig. 2 (B) ). And COIs on the second month were slightly lower than the first month with a statistically significant difference. Otherwise, over the six-month observation period of NAb, titer values decreased month by month and were all statistically different, while maintaining high levels of antibodies and high levels of positivity (all more than 98%) (Fig. 2 (C) ). The data used to build the antibody attenuation model were the individual data from a single infection within the 6-month follow-up period. The model estimated short-term and long-term immunity after an individual was infected with Omicron (Table 1 and Supplement Table 1 , Supplement Fig. 1 ). The single infection with Omicron increased the COI of IgG by an average of 70.07 (42.03, 104.86) in the short term and 33.63 (0, 61.89) in the long term, decreasing at the rate of -0.0024 (-0.0045, -0.0013) COI per day. The COI of IgM generated a short-lived boost of an average of 23.66 (4.84, 62.78) and a long-term boost of 0.63 (0.45, 0.80), with the decline rate of -0.0664 (-0.0964, -0.0338) after the single infection. And the short-term and long-term increase in the titers of NAb were 295.28 (242.78, 347.53) and 292.07 (242.09, 342.17), respectively, and the decline rate was−0.0021 (−0.0039,−0.0005). Table 1 Parameter estimates for models fitted to IgG, IgM and NAb against Omicron Parameters IgG IgM NAb Long-term immunity (µ 1 ) 33.63 (0, 61.89) 0.63 (0.45, 0.80) 292.07 (242.09, 342.17) Short-term immunity (µ 2 ) 70.07 (42.03, 104.86) 23.66 (4.84, 62.78) 295.28 (242.78, 347.53) Waning (ω) -0.0024 (-0.0045, -0.0013) -0.0663 (-0.0963, -0.0327) -0.0021 (-0.0039, -0.0005) Median estimates are shown, with 95% credible intervals (95%CI) in parentheses. The analysis was based on the participants who were singly infected with Omicron within the 6-month follow-up period. NAb = neutralizing antibodies. 3.3 Single infection vs. Recurrent infection Within the 6-month follow-up period, 449 out of 710 HCWs contracted Omicron just once, and 134 (18.87%) and 127 (17.89%) contracted again in Surveys 5 and 6, respectively. The antibody titres were for single infection and recurrent infection after one month in Fig. 3 . Compared with one month after the single infection, the titers of NAb and the COIs of IgG and IgM against Omicron increased significantly one month after reinfection (Fig. 2 ), showing 93.98 (71.87, 109.53) vs. 114.54 (93.36, 134.97) in IgG, 0.28 (0.16, 0.75) vs. 0.37 (0.22, 0.68) in IgM, and 440.31 (222.94, 1967.04) vs. 481.70 (182.45, 954.11) in NAb. 3.4 Variables influencing the waning of antibodies Mann-Whitney U-test and Kruskal-Wallis test were used to analyze the factors affecting the waning rate of IgG, IgM and NAb after the single infection with Omicron (Table 2 ). The results showed that the interval between the date of infection and the last day of vaccination affected the decay of IgG ( P < 0.00) and IgM ( P < 0.00), but not the decay of NAb ( P = 0.58 ). A two-by-two comparison between the groups in IgG and IgM showed that the < 14 group had a slower relative decline than the ≥ 180 group, both differences statistically significant. And age, sex, BMI, past infection, underlying diseases, and the long-term use of immunosuppressive drugs had no statistical difference in the relative decline of antibodies. Table 2 The influence factors of the waning of IgG, IgM and NAb after infection with Omicron IgG waning IgM waning NAb waning N M (IQR) P value M (IQR) P value M (IQR) P value Age, year 0.52 0.51 0.92 < 40 227 -18.78 (50.02) -6.25 (165.20) -71.84 (34.59) ≥ 40 222 -23.75 (54.2) -6.25 (159.19) -75.53 (31.87) Sex 0.14 0.06 0.76 female 334 -24.91 (51.00) 5.20 (169.82) -72.51 (33.62) male 115 -16.98 (52.85) -23.68 (107.16) -71.00 (29.21) BMI*, kg/m 2 0.16 0.15 0.51 < 18.5 24 -28.04 (41.47) -23.97 (100.85) -61.12 (37.72) 18.6~ ☨ 261 -26.15 (51.33) 0.00 (178.82) -73.56 (32.39) 24~ 119 -16.88 (53.08) 11.11 (143.81) -72.19 (31.23) ≥ 28 45 -10.96 (57.09) -29.41 (127.46) -71.61 (31.77) Past infection 0.26 0.58 0.61 Yes 438 -12.56 (25.67) -6.25 (167.24) -71.68 (27.37) No 11 -23.31 (52.85) -0.00 (134.89) -72.13 (33.11) Underlying diseases 0.70 0.1 0.17 Yes 63 -17.59 (53.58) -7.75 (165.34) -68.70 (36.45) No 386 -23.46 (52.46) 21.74 (161.25) -72.34 (32.36) Long-term use of immunosuppressive drugs 0.26 0.9 0.86 Yes 441 -15.79 (22.41) -3.45 (168.82) -71.48 (16.53) No 8 -23.44 (52.91) -16.00 (32.46) -72.10 (33.47) The interval between the date of infection and the last day of vaccination, days < 0.00 < 0.00 0.58 Not vaccinated 4 -27.24 (72.81) 100.00 (433.43) -38.16 (116.64) < 14 ☨ 210 -14.67 (51.79) -23.28 (113.08) -71.48 (34.14) 14~ 10 -39.98 (41.53) 26.28 (163.62) -77.48 (29.33) ≥ 180 225 -29.94 (47.88) 23.91 (166.29) -73.18 (31.88) Data are shown number of participants and median (interquartile range). The analysis was based on the participants who were singly infected with Omicron within the 6-month follow-up period. *BMI was stratified according to the guidelines for prevention and control of overweight and obesity in Chinese adults. ☨The grouping was set as the reference for the variable. NAb = neutralizing antibodies, N = the number of participants, BMI = body-mass index. 4 DISCUSSION The purpose of the six-month follow-up research systematically evaluated the kinetics of antibody responses among HCWs following Omicron infection over a six-month period. The findings compared immune responses in individuals with single versus recurrent infections and analyzed key factors influencing antibody waning. These findings provide valuable insights into the durability of post-infection immunity and offer important implications for public health vaccination strategies. Firstly, the study showed that IgG and neutralizing antibodies (NAb) were maintained at high levels after Omicron infection. Specifically, IgG levels remained stable for the first five months, with a significant decline observed at the sixth month, while NAb levels gradually declined month by month throughout the six-month follow-up but remained highly positive (above 98%). These results are consistent with prior studies indicating that SARS-CoV−2 infection induces long-lasting humoral immunity, particularly for IgG and NAb[ 16 , 17 ]. In contrast, IgM levels remained low and rapidly declined, suggesting that IgM serves more as a marker of recent infection rather than long-term immunity[ 18 ]. Using a mathematical model, the study quantified the short-term and long-term immune responses following a single Omicron infection, showing that IgG and IgM levels increased significantly post-infection but declined at varying rates. IgG increased by an average of 70.07 COI in the short term and 33.63 COI in the long term, declining at−0.0024 COI per day. IgM exhibited a short-lived boost of 23.66 COI and a minor long-term increase of 0.63 COI, with a more pronounced decline rate of−0.0664 COI per day. Similarly, NAb levels increased significantly post-infection, with a short-term rise of 295.28 and a long-term increase of 292.07, declining at−0.0021 COI per day. The study was consistent with the immune response rules of human beings’ bodies: after being infected with a virus, antibodies first increase and then decrease, IgM rapidly drops to a lower level in a short period of time, and IgG and NAb can exist at a high level for a longer period of time. And the difference showed in the study reflects the immunological profile of the different types of antibodies, with IgG and NAb being more persistent as important components of adaptive immunity and having a key defensive role in viral re-exposure[ 19 ]. Reinfection further enhanced antibody titers, with IgG increasing from 93.98 to 114.54 COI, IgM from 0.28 to 0.37 COI, and NAb from 440.31 to 481.70. The phenomenon is consistent with the concept of immunological memory, where memory B cells facilitate rapid antibody production upon reinfection[ 20 , 21 ]. And research by Zhao et al. found that Omicron reinfection provided only a temporary immune boost but did not prevent subsequent decline[ 22 ]. The waning pattern of antibodies post-reinfection should be explored further to determine optimal vaccination schedules. The further statistical analysis revealed that the interval between infection and the last vaccination significantly influenced the decay of IgG and IgM, with individuals infected within 14 days of vaccination experiencing a slower decline compared to those infected 180 days post-vaccination. This finding aligns with previous reports suggesting that recent vaccination can enhance B cell activation and help sustain antibody levels[ 21 ]. However, our study found that while reinfection boosts NAb levels, their decay remains consistent, regardless of vaccination timing. The finding aligns with research demonstrated that reinfection at various intervals (2, 4, 6, and 12 months) post-primary infection significantly elevated plasma NAb titers, but the longevity of these antibodies was comparable across different timing groups. This suggests that while reinfection serves as a booster to the immune system, the timing of vaccination relative to infection does not markedly alter the rate at which NAb levels decline over time[ 23 ]. Interestingly, the study did not find significant associations between antibody decay and demographic or clinical factors such as age, sex, BMI, past infection, underlying diseases, or immunosuppressive drug use. This contrasts with a study by Selvavinayagam et al., which reported that individuals over 60 years of age with underlying comorbid conditions had faster antibody decline[ 24 ]. The discrepancy may be due to differences in study populations, as our cohort consisted solely of HCWs with relatively homogeneous health profiles. Despite the valuable insights provided by our study, several limitations should be acknowledged. First, our study was conducted within a specific cohort of HCWs, which may limit the generalizability of the findings to the broader population, particularly individuals with different occupational exposures and risk factors. Second, the follow-up period was limited to six months, and longer-term immunity patterns remain unknown. Further studies with extended follow-up durations are necessary to evaluate the persistence of antibody responses over a longer timeframe. Third, while we focused on humoral immunity by measuring antibody titers, cellular immune responses were not assessed. T-cell immunity plays a crucial role in long-term protection against SARS-CoV−2, and future research should incorporate both humoral and cellular immunity assessments to provide a more comprehensive understanding of immune durability. Lastly, potential confounding factors such as prior asymptomatic infections or differences in vaccine-induced immunity were not fully accounted for, which may have influenced the observed antibody dynamics. Overall, the present study emphasized the short-term solidity and long-term attenuation trend of humoral immunity after natural infection, while revealing the important role of vaccination timing in delaying antibody attenuation. Although the majority of individuals still maintained high levels of IgG and NAb within six months, reinfection still occurred in a significant proportion of individuals, suggesting that it is difficult to effectively block virus transmission by relying only on herd immunity established by natural infection, and that vaccine booster shots are still necessary for controlling the outbreak. In addition, the quantified antibody elevation and attenuation parameters in the model can provide a reference basis for evaluating the durability of vaccine protection and formulating individualized vaccination strategies. Future studies could further explore the contribution of T-cell immunity, cross-immunity persistence among different variants, and the relationship between antibody function (e.g., neutralization ability) and protection efficacy. Meanwhile, combined with big data tracking studies, it is expected to establish more accurate prediction models to realize early identification and intervention of COVID−19 reinfection risk. 5 CONCLUSIONS This study highlights the dynamic nature of antibody responses to Omicron infection and reinfection. While reinfection provides a temporary boost, antibody waning remains a concern, particularly in the absence of timely booster doses. Public health strategies should focus on optimizing vaccination schedules to sustain immunity among HCWs and other vulnerable populations. Future research should explore cellular immunity contributions and the impact of hybrid immunity from vaccination and natural infection to provide a more comprehensive understanding of long-term protection against COVID−19. Abbreviations SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; NAbs: Neutralizing antibodies; HCWs: Healthcare workers; COI: Cut off index; COVID-19: Corona virus disease 2019; CI: Confidence interval; BMI: Body-mass index Declarations Acknowledgments This work was supported by Key Disciplines of Shanghai Three-year Action Plan to Strengthen the Construction of Public Health System (2023–2025) [Number GWVI-11.1-02 Infectious Diseases], Shanghai Pudong New Area Science and Technology Development Fund Project [Number PKJ2023-Y70] and the Key Discipline Program of Pudong New Area Health System [Number: PWZxk2022-25]. The above projects were awarded to Lipeng Hao, Laibao Yang and Yi Fei respectively. Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. This study was performed after Ethics committee of Shanghai Pudong New Area Center for Disease Control and Prevention approval was obtained. And each HCWs participated in the study provided the written informed consent ( Supplement file 3 ) before the start of the study. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding This work was supported by Key Disciplines of Shanghai Three-year Action Plan to Strengthen the Construction of Public Health System (2023–2025) [Number GWVI-11.1-02 Infectious Diseases], Shanghai Pudong New Area Science and Technology Development Fund Project [Number PKJ2023-Y70] and the Key Discipline Program of Pudong New Area Health System [Number: PWZxk2022-25]. Contributions Laibao Yang was the principal investigator of this study and designed the study protocol. 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Wang Z, Muecksch F, Schaefer-Babajew D, Finkin S, Viant C, Gaebler C, Hoffmann HH, Barnes CO, Cipolla M, Ramos V et al : Naturally enhanced neutralizing breadth against SARS-CoV-2 one year after infection . Nature 2021, 595 (7867):426-431. Goel RR, Painter MM, Apostolidis SA, Mathew D, Meng W, Rosenfeld AM, Lundgreen KA, Reynaldi A, Khoury DS, Pattekar A et al : mRNA vaccines induce durable immune memory to SARS-CoV-2 and variants of concern . Science 2021, 374 (6572):abm0829. Zhao XJ, Liu XL, Gu HJ, Liu T, Li DY, Zhang S, Wu J, Du KG, Tian S, Chen JJ et al : SARS-CoV-2 reinfection broadens the antibody responses and promotes the phenotypic differentiation of virus-specific memory T cells in adolescents . J Med Virol 2024, 96 (8):e29873. Srivastava K, Carreño JM, Gleason C, Monahan B, Singh G, Abbad A, Tcheou J, Raskin A, Kleiner G, van Bakel H et al : SARS-CoV-2-infection- and vaccine-induced antibody responses are long lasting with an initial waning phase followed by a stabilization phase . Immunity 2024, 57 (3):587-599.e584. Selvavinayagam ST, Yong YK, Tan HY, Zhang Y, Subramanian G, Rajeshkumar M, Vasudevan K, Jayapal P, Narayanasamy K, Ramesh D et al : Factors Associated With the Decay of Anti-SARS-CoV-2 S1 IgG Antibodies Among Recipients of an Adenoviral Vector-Based AZD1222 and a Whole-Virion Inactivated BBV152 Vaccine . Front Med (Lausanne) 2022, 9 :887974. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Published Journal Publication published 17 Nov, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 04 Aug, 2025 Reviews received at journal 02 Aug, 2025 Reviews received at journal 01 Aug, 2025 Reviews received at journal 26 Jul, 2025 Reviewers agreed at journal 26 Jul, 2025 Reviewers agreed at journal 26 Jul, 2025 Reviewers agreed at journal 25 Jul, 2025 Reviewers agreed at journal 24 Jul, 2025 Reviewers invited by journal 09 Jul, 2025 Editor assigned by journal 18 Jun, 2025 Editor invited by journal 02 Jun, 2025 Submission checks completed at journal 30 May, 2025 First submitted to journal 30 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6653332\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":483793943,\"identity\":\"f6a346a0-a0cd-4cee-8c8a-66ba7c717a81\",\"order_by\":0,\"name\":\"Yanfei Wu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yanfei\",\"middleName\":\"\",\"lastName\":\"Wu\",\"suffix\":\"\"},{\"id\":483793944,\"identity\":\"f18d87c6-e45f-4e56-ac25-71e015ae0833\",\"order_by\":1,\"name\":\"Shaohua Guo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shaohua\",\"middleName\":\"\",\"lastName\":\"Guo\",\"suffix\":\"\"},{\"id\":483793945,\"identity\":\"b539dc15-ebc5-4104-814a-b2d5cf150857\",\"order_by\":2,\"name\":\"Suyi Zhang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Suyi\",\"middleName\":\"\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":483793946,\"identity\":\"b5d12de3-f13d-4b85-abe8-983914f9c745\",\"order_by\":3,\"name\":\"Weibing Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Key Laboratory of Public Health Safety of Ministry of Education, Fudan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Weibing\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":483793947,\"identity\":\"60ccb71c-0ad1-41b2-8eb9-06926578c0dc\",\"order_by\":4,\"name\":\"Pengfei Deng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Pengfei\",\"middleName\":\"\",\"lastName\":\"Deng\",\"suffix\":\"\"},{\"id\":483793948,\"identity\":\"18a2902e-81da-4417-9380-197f923192d9\",\"order_by\":5,\"name\":\"Bing Zhao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Bing\",\"middleName\":\"\",\"lastName\":\"Zhao\",\"suffix\":\"\"},{\"id\":483793949,\"identity\":\"4c862475-1d58-4b0d-973f-9a369958876b\",\"order_by\":6,\"name\":\"Shaotan Xiao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shaotan\",\"middleName\":\"\",\"lastName\":\"Xiao\",\"suffix\":\"\"},{\"id\":483793950,\"identity\":\"0e0ce577-50e9-4fe1-ac24-9cbe68408c8f\",\"order_by\":7,\"name\":\"Xiao Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xiao\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":483793951,\"identity\":\"19a12773-ec16-4ca6-95a8-f3df5be3e298\",\"order_by\":8,\"name\":\"Laibao Yang\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIie3PsUrEMBzH8ZRAXVKzJlTUR0g5OCsc+ioJwk2lyy0OIqmF3ubcTr6CkzimHHhLtWvklrrdcEO6OIlYHQVzNzrkS6bw+wx/AFyu/1oHCAfAy7r+Y4IwljsQ/kNgHlVyekBLtRP5fntFGMjFhEluX7Pl82LNr+IUz7OCVo8tYkB5pk8spEmnMX8iM9LUedw3K3QCJaTVg4WoZMy4T4TUInst/RU6lcqHgY20m4F8EnGnhQyR/4KY4luITkadKIi41+ImDAq1nVC9GQNxS2bRcEtUNheIlnVuvWW/TUbGvF+nh8v5W2cuz84xzmvTW8ixAj759efJv/dDRxJAY124XC6X6wsFUF6yAC+2ogAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Shanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute)\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Laibao\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-05-13 08:38:25\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6653332/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6653332/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12879-025-11845-y\",\"type\":\"published\",\"date\":\"2025-11-17T15:59:09+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":86759429,\"identity\":\"2411d571-cc62-46d3-a617-02c570ae5e84\",\"added_by\":\"auto\",\"created_at\":\"2025-07-15 10:02:40\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":257176,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eSurvey profile\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSurvey 1 (baseline) was conducted January 31 to February 6, 2023. Survey 2 -6 were conducted one month after each participant.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6653332/v1/d6f8be08d899d319f82ddef7.png\"},{\"id\":86757984,\"identity\":\"c03948e9-729c-4ad9-ab68-b4763bbd8503\",\"added_by\":\"auto\",\"created_at\":\"2025-07-15 09:46:40\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1363432,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe changes of antibodies in IgG, IgM and NAb against Omicron within 6-month follow-up period\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe analysis was based on the participants who were singly infected with Omicron within the 6-month follow-up period. Data are shown median (quartile) and percentages of participants. Survey 1 was used as the control group for multiple comparisons of antibody titers, and only the \\u003cem\\u003eP\\u003c/em\\u003e value summary with statistically significant differences was shown in the figure. ****\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;0.0001, COI = cut off index, NAb = neutralizing antibodies.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6653332/v1/2fc4922b2dc944fc256679de.png\"},{\"id\":86759016,\"identity\":\"f5305dee-a2b6-4c16-abd2-656cb0d1ec59\",\"added_by\":\"auto\",\"created_at\":\"2025-07-15 09:54:40\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":291638,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe changes of antibodies in IgG, IgM and NAb after single and repeat Omicron infection\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data were for single infection and repeat infection after one month. Data are shown median (quartile) and percentages of participants. ****\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;0.0001，*\\u003cem\\u003eP\\u003c/em\\u003e\\u0026lt;0.05. COI = cut off index, NAb = neutralizing antibodies.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6653332/v1/c24db0c4393213d161016cad.png\"},{\"id\":96650249,\"identity\":\"653180db-f9d8-42fb-bdc5-517373361dc5\",\"added_by\":\"auto\",\"created_at\":\"2025-11-24 16:10:23\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":3549021,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6653332/v1/7230b0ee-ed69-4830-884d-9ec223ba93da.pdf\"},{\"id\":86757985,\"identity\":\"96a58a8a-de49-4108-af47-8dbc9eb7b19e\",\"added_by\":\"auto\",\"created_at\":\"2025-07-15 09:46:40\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":586640,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Supplementarymaterial.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6653332/v1/9a8cab4eddee7dbdefd1a481.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"The Impact of Omicron Infection on Antibody Response and Attenuation: A Six-Month Follow-Up Study\",\"fulltext\":[{\"header\":\"1 INTRODUCTION\",\"content\":\"\\u003cp\\u003eThe Corona virus disease 2019 (COVID-19) pandemic has evolved with the emergence of multiple variants, among which Omicron has demonstrated the highest transmissibility and immune evasion properties, leading to an unprecedented surge in COVID-19 cases worldwide[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. The variant possessed a large number of mutations in the spike protein, reducing the effectiveness of neutralizing antibodies and increasing the likelihood of breakthrough infections[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. While Omicron infections are generally associated with reduced severity compared to previous variants[\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e], their high reinfection rates and rapid antibody waning raise concerns about long-term immunity. Consequently, understanding the immune response dynamics following Omicron infection is critical for refining vaccination strategies and mitigating future outbreaks, particularly for healthcare workers (HCWs) who are at high risk of repeated exposure.\\u003c/p\\u003e\\u003cp\\u003eAccording to research, IgM, IgG and NAbs against SARS-CoV-2 peaked within one month after COVID-19 symptoms, declined rapidly within 6 months and then maintained a stable state[\\u003cspan additionalcitationids=\\\"CR6 CR7\\\" citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Current research focuses on the antibody trends of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the changes in antibodies to Omicron are still unclear. Therefore, the purpose of this study is to track the dynamics of IgM, IgG, and NAbs in the serum of Omicron-infected HCWs for evaluating the durability of vaccine protection and formulating individualized vaccination strategies. Additionally, an antibody change model will be established to assess the dynamic trend of antibody change following infection to further investigate the parameters of short-term and long-term enhancement and attenuation in antibody levels. Simultaneously, an exploratory investigation was carried out to see how demographic characteristics and vaccination affected the levels of antibodies following infection.\\u003c/p\\u003e\"},{\"header\":\"2 METHODS\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.1 Study design and Participants\\u003c/h2\\u003e\\n \\u003cp\\u003eHCWs infected with Omicron between December 19 and 25, 2022, volunteered to participate in the six-month follow-up study, from 64 district-affiliated medical and health institutions (district Centers for Disease Control and Preventions, community health care centers, secondary and tertiary medical institutions) in Pudong New Area, Shanghai. HCWs were enrolled if they tested positive for nucleic acid or SARS-CoV-2 antigen, or they showed early signs of COVID-19, and had no intention of leaving Shanghai within six months. HCWs consent was obtained via 5 mL non-anticoagulated serum tubes containing a venous blood sample. Additionally, online questionnaires (\\u003cstrong\\u003eSupplement file 1 and 2\\u003c/strong\\u003e) developed for the study on the participants\\u0026apos; work, general health, and history of SARS-CoV-2 infection were completed, as was their status of the COVID-19 vaccine, and continuation of COVID-19 symptoms. HCWs were followed up a total of 6 times, with Survey 1 (baseline) from January 31 to February 6, 2023 and follow-up surveys conducted one month (7 days as the time window) after each participant. Every follow-up session requires HCWs to provide blood and complete questionnaires. Blood samples were collected in the study in accordance with the Declaration of Helsinki. The study has been approved by the Medical Ethics Committee of Shanghai Pudong New Area for Disease Control and Prevention. And written informed consent (\\u003cstrong\\u003eSupplement file 3\\u003c/strong\\u003e) was given by each participating HCW prior to the commencement of the study.\\u003c/p\\u003e\\n \\u003cp\\u003eThe randomization used in the study was multi-stage random sampling. In accordance with the degree of the medical structure in which they were employed, HCWs who contracted COVID-19 between December 19 and December 25, 2022, were split into two tiers (secondary and third-level medical institutions, and community health care centers). Then, based on the likelihood of coming into contact with COVID-19 patients, each institution is divided into low-risk areas (almost no contact with patients: administration, security, etc.), medium-risk areas (no direct contact, but they are exposed to biological samples obtained from patients every day, such as laboratory testing personnel, non-communicable disease related-clinics), and high-risk areas (direct contact with patients or suspected patients: infectious disease-related clinics, wards, etc.). 10 HCWs were randomly selected from each area of 17 secondary and tertiary medical institutions, resulting in a total of 510 HCWs. 3\\u0026ndash;4 were randomly selected from each area of 47 communities, and a total of about 470 HCWs were selected.\\u003c/p\\u003e\\n \\u003cp\\u003eThe sample size was estimated by using the sample calculation formula comparing the sample rate with the population rate. According to a recent Shanghai COVID-19 case survey that tracked 9,000, the infection rate of HCWs was about 81.6%[\\u003cspan class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. The sample size of the study was 637 with a 10% two-way significance level, 90% power, and an allowable error of 5%. The final sample size was 950, raised by approximately 30% considering the loss of follow-up and the challenges associated with blood collection.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.2 Experiment\\u003c/h2\\u003e\\n \\u003cp\\u003eIgG, IgM and NAbs to SARS-CoV-2 were quantitatively detected using the magnetic particle chemiluminescence technique. The detection reagents included IgG/IgM Antibody Reagent Test Kits for the Novel Coronavirus 2019-nCoV (BiOSCiENCE, Chongqing, China), and Neutralizing Antibody Reagent Test Kits for the Novel Coronavirus 2019-nCoV (BiOSCiENCE, Tianjin, China).\\u003c/p\\u003e\\n \\u003cp\\u003eThe endpoints were the titers of the specific NAb against Omicron in units of antibody units (AU)/ml, and cut off index (COI) of IgG/IgM against Omicron. The secondary immunogenicity endpoint was the positivity rates of IgG, IgM and NAbs. NAb titers with a concentration of \\u0026ge;\\u0026thinsp;2.0 AU/ml were considered positive and vice versa, whereas COI values of \\u0026ge;\\u0026thinsp;1.0 were considered positive for IgG/IgM.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.3 Statistical analysis\\u003c/h2\\u003e\\n \\u003cp\\u003eWe used an exponential decay model to simulate the decline in antibody titers. Assuming that an individual contracted Omicron just once, antibody levels would rise rapidly in the early period following infection and then gradually decline to a rather steady level. Short-term immunity was the phase in which antibody levels increased quickly, while long-term immunity was the phase that followed stability. For example, studies have shown that following natural influenza infection, antibody responses are rapidly induced, peaking within approximately 15 days, and then gradually decline, leaving a longer-term response that remains stable for up to one year[\\u003cspan class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. And researches indicated that Iantibodies reached their peak levels within one month following the infection with SARS-CoV-2, subsequently declining rapidly over the next six months before stabilizing[\\u003cspan class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Based on the assumption, the following model was constructed[\\u003cspan class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e].\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\" width=\\\"344\\\" height=\\\"56\\\"\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003eThe antibody level of an individual was represented by \\u0026lambda;(t), which indicated the antibody level \\u003cem\\u003et\\u003c/em\\u003e days following the peak. \\u003cem\\u003e\\u0026micro;\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e and \\u003cem\\u003e\\u0026micro;\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sub\\u003e represented the antibody levels of long-term immunity and short-term immunity, respectively. The antibody level peaked and then fell exponentially, with the rate of decrease determined by the parameter \\u003cem\\u003e\\u0026omega;\\u003c/em\\u003e. The parameters \\u003cem\\u003e\\u0026micro;\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e, \\u003cem\\u003e\\u0026micro;\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sub\\u003e, and \\u003cem\\u003e\\u0026omega;\\u003c/em\\u003e were evaluated in the study using data from a single infection as well as data collected prior to a repeat infection, yielding estimated values and 95% confidence interval (CI).\\u003c/p\\u003e\\n \\u003cp\\u003eTiters of the specific NAb and COIs of IgG and IgM against Omicron were expressed as medians (quartile or interquartile ranges) and subjected to rank sum test analysis,if required, by Dunn\\u0026apos;s multiple comparison test. Since the data were not normally distributed, the the Mann-Whitney U test for binary variables or the Kruskal-Wallis test for multi-categorical variables were used to assess the association of age, sex, BMI, history of underlying diseases, history of immunosuppressive medication use, previous infection, and the interval between the date of infection and the last day of vaccination on antibody waning (defined as relative decline; [X(final antibody COI or titer)\\u0026thinsp;\\u0026minus;\\u0026thinsp;X(baseline COI or titer)]/X(baseline COI or titer)\\u0026times;100). With 5% as the default significance threshold, all statistical tests were two-way. Unless specified differently in the analytic description, all CIs were presented as 95%.\\u003c/p\\u003e\\n \\u003cp\\u003eGraphPad Prism 9.0, SAS 9.4, and R 4.3.3 were used for statistical analysis.\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"3 RESULTS\",\"content\":\"\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.1 Demographic characteristics\\u003c/h2\\u003e\\u003cp\\u003eA total of 1186 HCWs were recruited and screened for eligibility (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). 207 HCWs were excluded, including 162 individuals who met the exclusion criteria, 10 individuals who uncollected blood, and 35 individuals who withdrew consent. 710 HCWs were ultimately included in the study after 238 were lost to follow-up after six follow-up visits, 15 revoked their informed permission, and 16 uncollected blood.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe 710 HCWs who participated in the study had a median age of 38 (IQR: 33\\u0026ndash;45 years), 165 males and 545 females, with a male to female ratio of 0.30:1. And the mean body-mass index (BMI) of HCWs was 23.34 kg/m\\u003csup\\u003e2\\u003c/sup\\u003e (IQR: 20.81\\u0026ndash;24.91 kg/m\\u003csup\\u003e2\\u003c/sup\\u003e). Among 710 HCWs, 693 (97.61%) have been infected with Omicron in the past, and 622 (87.61%) had underlying medical conditions (chronic lung illness, diabetes, renal disease, liver disease, malignancies, etc.). Out of the total research participants, only 12 (1.69%) had a history of prolonged use of immunosuppressive medications. And the interval between the date of infection and the last day of vaccination was less than 14 days for 313 (44.08%), more than 180 days for 371 (52.25%), 14 to 180 days for 15 (2.11%), and not vaccinated for 11 (1.55%). Besides, 261 (36.76%) individuals contracted Omicron again within the 6-month follow-up period, including 134 (18.87%) at Survey 5 and 127 (17.89%) at Survey 6.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.2 Model of antibody degradation\\u003c/h2\\u003e\\u003cp\\u003eThe 449 HCWs with only a single Omicron infection were found to maintain a high COI for IgG with no statistical difference in the first five months and a significant decrease in the sixth month compared to the first follow-up after six months (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e \\u003cb\\u003e(A)\\u003c/b\\u003e). And there were the high rates of IgG positivity within the six-month follow-up (all higher than 98%). The COIs in IgM remained low throughout the six-month follow-up with low positivity rates (less than 20%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e \\u003cb\\u003e(B)\\u003c/b\\u003e). And COIs on the second month were slightly lower than the first month with a statistically significant difference. Otherwise, over the six-month observation period of NAb, titer values decreased month by month and were all statistically different, while maintaining high levels of antibodies and high levels of positivity (all more than 98%) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e \\u003cb\\u003e(C)\\u003c/b\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe data used to build the antibody attenuation model were the individual data from a single infection within the 6-month follow-up period. The model estimated short-term and long-term immunity after an individual was infected with Omicron (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e \\u003cb\\u003eand Supplement\\u003c/b\\u003e Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cb\\u003eSupplement\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The single infection with Omicron increased the COI of IgG by an average of 70.07 (42.03, 104.86) in the short term and 33.63 (0, 61.89) in the long term, decreasing at the rate of -0.0024 (-0.0045, -0.0013) COI per day. The COI of IgM generated a short-lived boost of an average of 23.66 (4.84, 62.78) and a long-term boost of 0.63 (0.45, 0.80), with the decline rate of -0.0664 (-0.0964, -0.0338) after the single infection. And the short-term and long-term increase in the titers of NAb were 295.28 (242.78, 347.53) and 292.07 (242.09, 342.17), respectively, and the decline rate was\\u0026minus;0.0021 (\\u0026minus;0.0039,\\u0026minus;0.0005).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eParameter estimates for models fitted to IgG, IgM and NAb against Omicron\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eParameters\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eIgG\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eIgM\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eNAb\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLong-term immunity (\\u0026micro;\\u003csub\\u003e1\\u003c/sub\\u003e)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e33.63 (0, 61.89)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.63 (0.45, 0.80)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e292.07 (242.09, 342.17)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eShort-term immunity (\\u0026micro;\\u003csub\\u003e2\\u003c/sub\\u003e)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e70.07 (42.03, 104.86)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e23.66 (4.84, 62.78)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e295.28 (242.78, 347.53)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eWaning (ω)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e-0.0024 (-0.0045, -0.0013)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.0663 (-0.0963, -0.0327)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e-0.0021 (-0.0039, -0.0005)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eMedian estimates are shown, with 95% credible intervals (95%CI) in parentheses. The analysis was based on the participants who were singly infected with Omicron within the 6-month follow-up period. NAb\\u0026thinsp;=\\u0026thinsp;neutralizing antibodies.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.3 Single infection vs. Recurrent infection\\u003c/h2\\u003e\\u003cp\\u003eWithin the 6-month follow-up period, 449 out of 710 HCWs contracted Omicron just once, and 134 (18.87%) and 127 (17.89%) contracted again in Surveys 5 and 6, respectively. The antibody titres were for single infection and recurrent infection after one month in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e. Compared with one month after the single infection, the titers of NAb and the COIs of IgG and IgM against Omicron increased significantly one month after reinfection (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e), showing 93.98 (71.87, 109.53) vs. 114.54 (93.36, 134.97) in IgG, 0.28 (0.16, 0.75) vs. 0.37 (0.22, 0.68) in IgM, and 440.31 (222.94, 1967.04) vs. 481.70 (182.45, 954.11) in NAb.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.4 Variables influencing the waning of antibodies\\u003c/h2\\u003e\\u003cp\\u003eMann-Whitney U-test and Kruskal-Wallis test were used to analyze the factors affecting the waning rate of IgG, IgM and NAb after the single infection with Omicron (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). The results showed that the interval between the date of infection and the last day of vaccination affected the decay of IgG (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.00) and IgM (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.00), but not the decay of NAb (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.58 ). A two-by-two comparison between the groups in IgG and IgM showed that the \\u0026lt;\\u0026thinsp;14 group had a slower relative decline than the \\u0026ge;\\u0026thinsp;180 group, both differences statistically significant. And age, sex, BMI, past infection, underlying diseases, and the long-term use of immunosuppressive drugs had no statistical difference in the relative decline of antibodies.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eThe influence factors of the waning of IgG, IgM and NAb after infection with Omicron\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"8\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e\\u003cp\\u003eIgG waning\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e\\u003cp\\u003eIgM waning\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e\\u003cp\\u003eNAb waning\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eN\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eM (IQR)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e value\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eM (IQR)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e value\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003eM (IQR)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e value\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAge, year\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.52\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.51\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.92\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e227\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-18.78 (50.02)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-6.25 (165.20)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-71.84 (34.59)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026ge;\\u0026thinsp;40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e222\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-23.75 (54.2)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-6.25 (159.19)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-75.53 (31.87)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSex\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.14\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.06\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.76\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003efemale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e334\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-24.91 (51.00)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e5.20 (169.82)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-72.51 (33.62)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003emale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e115\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-16.98 (52.85)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-23.68 (107.16)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-71.00 (29.21)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003eBMI*, kg/m\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.16\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.51\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;18.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e24\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-28.04 (41.47)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-23.97 (100.85)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-61.12 (37.72)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e18.6~\\u003csup\\u003e☨\\u003c/sup\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e261\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-26.15 (51.33)\\u003c/p\\u003e \\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00 (178.82)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-73.56 (32.39)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e24~\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e119\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-16.88 (53.08)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e11.11 (143.81)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-72.19 (31.23)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026ge;\\u0026thinsp;28\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-10.96 (57.09)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-29.41 (127.46)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-71.61 (31.77)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePast infection\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.26\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.58\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.61\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eYes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e438\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-12.56 (25.67)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-6.25 (167.24)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-71.68 (27.37)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNo\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e11\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-23.31 (52.85)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-0.00 (134.89)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-72.13 (33.11)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c3\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003eUnderlying diseases\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.70\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eYes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e63\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-17.59 (53.58)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-7.75 (165.34)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-68.70 (36.45)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNo\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e386\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-23.46 (52.46)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e21.74 (161.25)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-72.34 (32.36)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c3\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003eLong-term use of immunosuppressive drugs\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.26\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.86\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eYes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e441\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-15.79 (22.41)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-3.45 (168.82)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-71.48 (16.53)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNo\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-23.44 (52.91)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-16.00 (32.46)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-72.10 (33.47)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c3\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003eThe interval between the date of infection and the last day of vaccination, days\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.00\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.00\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.58\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNot vaccinated\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-27.24 (72.81)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e100.00 (433.43)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-38.16 (116.64)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;14\\u003csup\\u003e☨\\u003c/sup\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e210\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-14.67 (51.79)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e-23.28 (113.08)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-71.48 (34.14)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e14~\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e10\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-39.98 (41.53)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e26.28 (163.62)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-77.48 (29.33)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026ge;\\u0026thinsp;180\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e225\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-29.94 (47.88)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e23.91 (166.29)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e-73.18 (31.88)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eData are shown number of participants and median (interquartile range). The analysis was based on the participants who were singly infected with Omicron within the 6-month follow-up period. *BMI was stratified according to the guidelines for prevention and control of overweight and obesity in Chinese adults. ☨The grouping was set as the reference for the variable.\\u003c/p\\u003e\\u003cp\\u003eNAb\\u0026thinsp;=\\u0026thinsp;neutralizing antibodies, N\\u0026thinsp;=\\u0026thinsp;the number of participants, BMI\\u0026thinsp;=\\u0026thinsp;body-mass index.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"4 DISCUSSION\",\"content\":\"\\u003cp\\u003eThe purpose of the six-month follow-up research systematically evaluated the kinetics of antibody responses among HCWs following Omicron infection over a six-month period. The findings compared immune responses in individuals with single versus recurrent infections and analyzed key factors influencing antibody waning. These findings provide valuable insights into the durability of post-infection immunity and offer important implications for public health vaccination strategies.\\u003c/p\\u003e\\u003cp\\u003eFirstly, the study showed that IgG and neutralizing antibodies (NAb) were maintained at high levels after Omicron infection. Specifically, IgG levels remained stable for the first five months, with a significant decline observed at the sixth month, while NAb levels gradually declined month by month throughout the six-month follow-up but remained highly positive (above 98%). These results are consistent with prior studies indicating that SARS-CoV\\u0026minus;2 infection induces long-lasting humoral immunity, particularly for IgG and NAb[\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. In contrast, IgM levels remained low and rapidly declined, suggesting that IgM serves more as a marker of recent infection rather than long-term immunity[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eUsing a mathematical model, the study quantified the short-term and long-term immune responses following a single Omicron infection, showing that IgG and IgM levels increased significantly post-infection but declined at varying rates. IgG increased by an average of 70.07 COI in the short term and 33.63 COI in the long term, declining at\\u0026minus;0.0024 COI per day. IgM exhibited a short-lived boost of 23.66 COI and a minor long-term increase of 0.63 COI, with a more pronounced decline rate of\\u0026minus;0.0664 COI per day. Similarly, NAb levels increased significantly post-infection, with a short-term rise of 295.28 and a long-term increase of 292.07, declining at\\u0026minus;0.0021 COI per day. The study was consistent with the immune response rules of human beings\\u0026rsquo; bodies: after being infected with a virus, antibodies first increase and then decrease, IgM rapidly drops to a lower level in a short period of time, and IgG and NAb can exist at a high level for a longer period of time. And the difference showed in the study reflects the immunological profile of the different types of antibodies, with IgG and NAb being more persistent as important components of adaptive immunity and having a key defensive role in viral re-exposure[\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e\\u003cp\\u003eReinfection further enhanced antibody titers, with IgG increasing from 93.98 to 114.54 COI, IgM from 0.28 to 0.37 COI, and NAb from 440.31 to 481.70. The phenomenon is consistent with the concept of immunological memory, where memory B cells facilitate rapid antibody production upon reinfection[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. And research by Zhao et al. found that Omicron reinfection provided only a temporary immune boost but did not prevent subsequent decline[\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. The waning pattern of antibodies post-reinfection should be explored further to determine optimal vaccination schedules.\\u003c/p\\u003e\\u003cp\\u003eThe further statistical analysis revealed that the interval between infection and the last vaccination significantly influenced the decay of IgG and IgM, with individuals infected within 14 days of vaccination experiencing a slower decline compared to those infected 180 days post-vaccination. This finding aligns with previous reports suggesting that recent vaccination can enhance B cell activation and help sustain antibody levels[\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. However, our study found that while reinfection boosts NAb levels, their decay remains consistent, regardless of vaccination timing. The finding aligns with research demonstrated that reinfection at various intervals (2, 4, 6, and 12 months) post-primary infection significantly elevated plasma NAb titers, but the longevity of these antibodies was comparable across different timing groups. This suggests that while reinfection serves as a booster to the immune system, the timing of vaccination relative to infection does not markedly alter the rate at which NAb levels decline over time[\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Interestingly, the study did not find significant associations between antibody decay and demographic or clinical factors such as age, sex, BMI, past infection, underlying diseases, or immunosuppressive drug use. This contrasts with a study by Selvavinayagam et al., which reported that individuals over 60 years of age with underlying comorbid conditions had faster antibody decline[\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. The discrepancy may be due to differences in study populations, as our cohort consisted solely of HCWs with relatively homogeneous health profiles.\\u003c/p\\u003e\\u003cp\\u003eDespite the valuable insights provided by our study, several limitations should be acknowledged. First, our study was conducted within a specific cohort of HCWs, which may limit the generalizability of the findings to the broader population, particularly individuals with different occupational exposures and risk factors. Second, the follow-up period was limited to six months, and longer-term immunity patterns remain unknown. Further studies with extended follow-up durations are necessary to evaluate the persistence of antibody responses over a longer timeframe. Third, while we focused on humoral immunity by measuring antibody titers, cellular immune responses were not assessed. T-cell immunity plays a crucial role in long-term protection against SARS-CoV\\u0026minus;2, and future research should incorporate both humoral and cellular immunity assessments to provide a more comprehensive understanding of immune durability. Lastly, potential confounding factors such as prior asymptomatic infections or differences in vaccine-induced immunity were not fully accounted for, which may have influenced the observed antibody dynamics.\\u003c/p\\u003e\\u003cp\\u003eOverall, the present study emphasized the short-term solidity and long-term attenuation trend of humoral immunity after natural infection, while revealing the important role of vaccination timing in delaying antibody attenuation. Although the majority of individuals still maintained high levels of IgG and NAb within six months, reinfection still occurred in a significant proportion of individuals, suggesting that it is difficult to effectively block virus transmission by relying only on herd immunity established by natural infection, and that vaccine booster shots are still necessary for controlling the outbreak. In addition, the quantified antibody elevation and attenuation parameters in the model can provide a reference basis for evaluating the durability of vaccine protection and formulating individualized vaccination strategies.\\u003c/p\\u003e\\u003cp\\u003eFuture studies could further explore the contribution of T-cell immunity, cross-immunity persistence among different variants, and the relationship between antibody function (e.g., neutralization ability) and protection efficacy. Meanwhile, combined with big data tracking studies, it is expected to establish more accurate prediction models to realize early identification and intervention of COVID\\u0026minus;19 reinfection risk.\\u003c/p\\u003e\"},{\"header\":\"5 CONCLUSIONS\",\"content\":\"\\u003cp\\u003eThis study highlights the dynamic nature of antibody responses to Omicron infection and reinfection. While reinfection provides a temporary boost, antibody waning remains a concern, particularly in the absence of timely booster doses. Public health strategies should focus on optimizing vaccination schedules to sustain immunity among HCWs and other vulnerable populations. Future research should explore cellular immunity contributions and the impact of hybrid immunity from vaccination and natural infection to provide a more comprehensive understanding of long-term protection against COVID\\u0026minus;19.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eSARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; NAbs: Neutralizing antibodies; HCWs: Healthcare workers; COI: Cut off index; COVID-19: Corona virus disease 2019; CI: Confidence interval; BMI: Body-mass index\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported by Key Disciplines of Shanghai Three-year Action Plan to Strengthen the Construction of Public Health System (2023\\u0026ndash;2025) [Number GWVI-11.1-02 Infectious Diseases], Shanghai Pudong New Area Science and Technology Development Fund Project [Number PKJ2023-Y70] and the Key Discipline Program of Pudong New Area Health System [Number: PWZxk2022-25]. The above projects were awarded to Lipeng Hao, Laibao Yang and Yi Fei respectively.\\u0026nbsp;\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was conducted in accordance with the Declaration of Helsinki. This study was performed after Ethics committee of Shanghai Pudong New Area Center for Disease Control and Prevention approval was obtained. And each HCWs participated in the study provided the written informed consent (\\u003cstrong\\u003eSupplement file 3\\u003c/strong\\u003e) before the start of the study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets generated and/or analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported by Key Disciplines of Shanghai Three-year Action Plan to Strengthen the Construction of Public Health System (2023\\u0026ndash;2025) [Number GWVI-11.1-02 Infectious Diseases], Shanghai Pudong New Area Science and Technology Development Fund Project [Number PKJ2023-Y70] and the Key Discipline Program of Pudong New Area Health System [Number: PWZxk2022-25].\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eContributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLaibao Yang was the principal investigator of this study and designed the study protocol. Laibao Yang, Shaotan Xiao and Weibing Wang contributed to critical review and revising of the report. Yan-fei Wu contributed to the data interpretation, drafting, and revising of this manuscript. Shaohua Guo and Pengfei Deng led and participated in the site work, including the recruitment, follow-up, and data collection. Xiao Wang and Bing Zhao led the laboratory tests. Suyi Zhang contributed to statistical analysis. All authors read and approved the final manuscript.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAraf Y, Akter F, Tang YD, Fatemi R, Parvez MSA, Zheng C, Hossain MG: \\u003cstrong\\u003eOmicron variant of SARS-CoV-2: Genomics, transmissibility, and responses to current COVID-19 vaccines\\u003c/strong\\u003e. \\u003cem\\u003eJ Med Virol \\u003c/em\\u003e2022, \\u003cstrong\\u003e94\\u003c/strong\\u003e(5):1825-1832.\\u003c/li\\u003e\\n\\u003cli\\u003eHarvey WT, Carabelli AM, Jackson B, Gupta RK, Thomson EC, Harrison EM, Ludden C, Reeve R, Rambaut A, Peacock SJ\\u003cem\\u003e et al\\u003c/em\\u003e: \\u003cstrong\\u003eSARS-CoV-2 variants, spike mutations and immune escape\\u003c/strong\\u003e. \\u003cem\\u003eNat Rev Microbiol \\u003c/em\\u003e2021, \\u003cstrong\\u003e19\\u003c/strong\\u003e(7):409-424.\\u003c/li\\u003e\\n\\u003cli\\u003eGupta D, Sharma P, Singh M, Kumar M, Ethayathulla AS, Kaur P: \\u003cstrong\\u003eStructural and 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\\u003cstrong\\u003e374\\u003c/strong\\u003e(6572):abm0829.\\u003c/li\\u003e\\n\\u003cli\\u003eZhao XJ, Liu XL, Gu HJ, Liu T, Li DY, Zhang S, Wu J, Du KG, Tian S, Chen JJ\\u003cem\\u003e et al\\u003c/em\\u003e: \\u003cstrong\\u003eSARS-CoV-2 reinfection broadens the antibody responses and promotes the phenotypic differentiation of virus-specific memory T cells in adolescents\\u003c/strong\\u003e. \\u003cem\\u003eJ Med Virol \\u003c/em\\u003e2024, \\u003cstrong\\u003e96\\u003c/strong\\u003e(8):e29873.\\u003c/li\\u003e\\n\\u003cli\\u003eSrivastava K, Carre\\u0026ntilde;o JM, Gleason C, Monahan B, Singh G, Abbad A, Tcheou J, Raskin A, Kleiner G, van Bakel H\\u003cem\\u003e et al\\u003c/em\\u003e: \\u003cstrong\\u003eSARS-CoV-2-infection- and vaccine-induced antibody responses are long lasting with an initial waning phase followed by a stabilization phase\\u003c/strong\\u003e. \\u003cem\\u003eImmunity \\u003c/em\\u003e2024, \\u003cstrong\\u003e57\\u003c/strong\\u003e(3):587-599.e584.\\u003c/li\\u003e\\n\\u003cli\\u003eSelvavinayagam ST, Yong YK, Tan HY, Zhang Y, Subramanian G, Rajeshkumar M, Vasudevan K, Jayapal P, Narayanasamy K, Ramesh D\\u003cem\\u003e et al\\u003c/em\\u003e: \\u003cstrong\\u003eFactors Associated With the Decay of Anti-SARS-CoV-2 S1 IgG Antibodies Among Recipients of an Adenoviral Vector-Based AZD1222 and a Whole-Virion Inactivated BBV152 Vaccine\\u003c/strong\\u003e. \\u003cem\\u003eFront Med (Lausanne) \\u003c/em\\u003e2022, \\u003cstrong\\u003e9\\u003c/strong\\u003e:887974.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Omicron, neutralizing antibodies, IgG, IgM, antibody waning, reinfection, healthcare workers, vaccination timing\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6653332/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6653332/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eAntibody patterns to ssevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are the subject of current study, and the variations in antibodies to Omicron are yet unknown. The study investigated the six-month longitudinal dynamics and influencing factors of antibodies, including IgG, IgM, and neutralizing antibodies (NAbs), in healthcare workers (HCWs) following Omicron infection.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e\\u003cp\\u003eHCWs were recruited in Shanghai through multistage sampling, tested positive for SARS-CoV-2, and were followed up six times with blood sampling and questionnaires. The primary endpoints were the titers of the specific NAb against Omicron and the cut off index (COI) of IgG/IgM against Omicron. Antibody decay models were developed based on individual data of participants with single Omicron infection, and statistical analyses were conducted to explore influencing factors using Mann-Whitney U and Kruskal-Wallis tests.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eA total of 710 HCWs were enrolled, with IgG and NAb remaining high for five months but declining significantly in the sixth, but IgM declining rapidly throughout. After the single infection, IgG exhibited a mean short-term increase of 70.07 COI and a long-term elevation of 33.63 COI, with a gradual decline at a rate of \\u0026minus;\\u0026thinsp;0.0024 COI per day. IgM demonstrated a transient elevation, with a short-term boost of 23.66 COI and a modest long-term increase of 0.63, followed by a more rapid decay at \\u0026minus;\\u0026thinsp;0.0664 COI per day. NAb similarly rose significantly post-infection, with a short-term increase of 295.28 and a sustained long-term elevation of 292.07, declining at a rate of \\u0026minus;\\u0026thinsp;0.0021 COI per day. Reinfection occurred in 36.76% of HCWs, boosting antibody levels. Timing between infection and vaccination significantly influenced IgG/IgM waning but not NAbs. No associations were found between antibody decay and demographic or clinical factors.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e\\u003cp\\u003eWhile Omicron infection induces robust short-term antibody responses, immunity wanes significantly within six months, and reinfection temporarily boosts antibody levels. The findings highlight the limited durability of natural and hybrid immunity and underscore the need for timely booster vaccinations to sustain protection, particularly in high-risk groups like HCWs.\\u003c/p\\u003e\",\"manuscriptTitle\":\"The Impact of Omicron Infection on Antibody Response and Attenuation: A Six-Month Follow-Up Study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-07-15 09:46:35\",\"doi\":\"10.21203/rs.3.rs-6653332/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-08-04T08:54:37+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-08-02T17:42:45+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-08-01T18:18:35+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-07-26T23:24:17+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"68486591998382948819801851856035075941\",\"date\":\"2025-07-26T17:19:26+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"73963732165616864098417269662406929214\",\"date\":\"2025-07-26T11:07:00+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"143957556125675748023577315550601128794\",\"date\":\"2025-07-25T13:42:10+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"79358094543697213515859115479670474359\",\"date\":\"2025-07-24T07:25:20+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-07-09T19:24:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-06-18T12:15:37+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-06-02T09:10:22+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-05-30T07:05:18+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Infectious Diseases\",\"date\":\"2025-05-30T07:02:05+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"62bf3a4d-7131-4f32-b968-dd7f4af9bb52\",\"owner\":[],\"postedDate\":\"July 15th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-11-24T16:04:56+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6653332\",\"link\":\"https://doi.org/10.1186/s12879-025-11845-y\",\"journal\":{\"identity\":\"bmc-infectious-diseases\",\"isVorOnly\":false,\"title\":\"BMC Infectious Diseases\"},\"publishedOn\":\"2025-11-17 15:59:09\",\"publishedOnDateReadable\":\"November 17th, 2025\"},\"versionCreatedAt\":\"2025-07-15 09:46:35\",\"video\":\"\",\"vorDoi\":\"10.1186/s12879-025-11845-y\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12879-025-11845-y\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6653332\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6653332\",\"identity\":\"rs-6653332\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}