Association between humoral serological markers levels and risk of SARS-CoV-2 infection after the primary COVID-19 vaccine course among ANRS0001S COV- POPART cohort participants

Association between humoral serological markers levels and risk of SARS-CoV-2 infection after the primary COVID-19 vaccine course among ANRS0001S COV- POPART cohort participants | 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 Association between humoral serological markers levels and risk of SARS-CoV-2 infection after the primary COVID-19 vaccine course among ANRS0001S COV- POPART cohort participants Mathieu Chalouni, Paul Loubet, Edouard Lhomme, Laetitia Ninove, and 24 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510677/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Sep, 2024 Read the published version in BMC Infectious Diseases → Version 1 posted 4 You are reading this latest preprint version Abstract Background We assessed the prognostic value of serological humoral markers measured one month after the last dose of the primary COVID-19 vaccine course for predicting the risk of severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 infection over the following six months in specific populations. Methods ANRS0001SCOV-POPART (NCT04824651) is a French nationwide multicenter prospective observational cohort study assessing the immune response to Covid-19 vaccines routinely administered to 11 subgroups of patients with chronic disease and a control group. Participants from the ANRS0001S COV-POPART were included if they received at least two doses of Covid-19 vaccine for the primary vaccine course, had measurements of anti-Spike, anti-receptor binding domain (RBD) IgG-specific or neutralizing antibodies one month after the end of the primary vaccine course, without being infected by SARS-CoV-2 before the measurement. SARS-CoV-2 infections defined by a positive PCR/antigenic test or seroconversion to detectable anti nucleocapsid antibodies were evaluated until the first COVID-19 booster injection. Cox proportional hazards models taking into account interval-censored data were implemented to estimate the association between each antibody level and the risk of SARS-CoV-2 infection. Predictive performances were evaluated by the area under the receiving operating characteristic curve (AUROC). Results 2,570 adults with a chronic disease and 1,123 without a condition of interest were included. The cumulative probabilities of SARS-CoV-2 infections at five months were 6.0% 95% confidence interval: [5.0; 7.9] and 10.1% [8.3; 11.9], respectively. Higher levels of anti-Spike IgG antibody were associated with a lower risk of SARS-CoV-2 infections in participants without a condition of interest, but not in the specific populations. Among the specific populations, AUROC were 74.5%, 74.9%, and 72.4% for anti-Spike IgG, anti-RBD IgG, and neutralizing antibodies, respectively. AUROC were superior in participants without a condition of interest, 82.0%, 81.2%, and 81.4% for anti-Spike IgG, anti-RBD IgG, and neutralizing antibodies, respectively. Conclusions Vaccine-induced antibody response after the primary course of Covid-19 infection only moderately discriminated between participants developing a SARS-CoV-2 infection during the Omicron wave. Specific populations SARS-CoV-2-vaccine prediction Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, several vaccines have been validated and recommended ( 1 – 3 ). In France, the Covid-19 vaccination campaign started in December 2020, with BNT162b2 vaccine. In May 2021, three additional vaccines were available: mRNA-1273, ChAdOx1-nCoV19, and Ad26.COV2.S. For some specific populations a third dose in the primary vaccine course was recommended ( 4 ). Booster injections were recommended from October 2021 onwards ( 5 ). COVID-19 vaccines have been shown to reduce the risk of severe diseases, hospitalization, and death ( 6 , 7 ). Binding and neutralizing antibodies have been particularly studied as prognostic factors and potential correlates of protection ( 8 – 11 ). However, these studies were essentially conducted in clinical trials evaluating the ChadOx1 nCoV-19 (AZD1222) and ARNm-1273 (Moderna) vaccines in a context where the predominant circulating variant was the alpha variant (B.1.1.7) ( 8 , 12 ). Other variants have emerged, in particular, the Omicron (B.1.1.529) variant and sub-variants, which are associated with a decreased vaccine efficacy ( 13 ), higher breakthrough infections, but decreased severity ( 14 , 15 ) compared to previous variants or original strain. The current prognostic value of antibody levels in vaccinated populations is still not completely explored. In populations at risk of developing severe forms of SARS-CoV-2 infection, i.e immunocompromised patients, Covid-19 vaccine effectiveness is lower than in the overall population ( 16 , 17 ) and the role of the antibody response could be less important than the cellular response ( 18 ). We aimed to evaluate the prognostic value of humoral serological markers levels, i.e. anti-Spike IgG, anti-receptor binding domain (RBD) IgG, and neutralizing antibodies, measured one month after the last dose received during the primary vaccine course for the risk of SARS-CoV-2 infection up to 6 months after the lase dose in the ANRS0001S COV-POPART cohort. METHODS Study design ANRS0001S COV-POPART cohort (NCT04824651, Registration Date: 03/25/2021) is a French nationwide multicenter prospective cohort study of specific populations (solid cancer, solid organs transplanted, hematopoietic stem cell transplant, chronic kidney disease and dialysis, systemic autoimmune diseases, inflammatory rheumatic disease, multiple sclerosis/neuromyelitis optica spectrum disorder, hypogammaglobulinemia, diabetic, obese non-diabetic, and HIV) and a group without the above-mentioned chronic conditions. Participants older than 18 years, without known history of SARS-CoV-2 infection at inclusion were included between March 25th, 2021 to December 31st, 2021. The study design is further described in previous publications ( 5 , 19 ). Primary vaccine course choice was made according to the authorization, availability, national recommendations, and prescriber choice ( 4 ). Visits for characteristics and antibodies were measured were scheduled before the first dose injection, at the time of the first, second, and third dose if any, and 6, 12, and 24 months after the second dose. Supplementary visits were implemented at the time and one month after a booster injection ( 19 ). Study population We included participants from the ANRS0001S COV-POPART who received at least two doses during the primary vaccine course (a third dose within the primary course was defined as an injection in a three-month window after the second dose), had at least one antibody value among anti-Spike IgG, anti-RBD IgG, or neutralizing antibodies one month after the last dose received during the primary vaccine course, and without SARS-CoV-2 infection before the antibody level measurement. All analyses were implemented separately between participants from specific populations and the control group given the heterogeneity in antibody responses and the usually lower antibody response in specific populations compared to the overall population ( 16 , 17 ). Antibody measurements Antibody levels were measured one month (between 21 days and 56 days) after the last dose received during the primary vaccine course. The samples analyzed as part of the study were managed and stored within the « Biothèque ANRS ». All serological analyses were carried out centrally at the “Unité des virus émergents” Aix-Marseille Université, Institut de Recherche pour le Développement 190, Inserm 1207, Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France. Antibody assays used are described in the supplementary material (Supplementary materials antibodies measurement). For undetectable antibodies, half of the detection cut-off was imputed (15 BAU/mL and 10 fold dilution for anti-Spike IgG, and neutralizing antibodies, respectively). We estimated the geometric means of the anti-Spike IgG, anti-RBD IgG, and neutralizing antibody titers measured one month after the last injection. SARS-CoV-2 infection SARS-CoV-2 infection was defined by a positive antigenic test or RT-PCR, positive anti-NCP antibodies, or an increase in anti-Spike IgG antibody levels in the absence of a booster injection or the prescription of monoclonal antibodies. Anti-NCP antibodies are systematically evaluated at each visit in all participants as are anti-Spike IgG antibody levels. In case of a positive antigenic or RT-PCR test performed outside the cohort protocol, participants were asked to consult within 72 hours for a clinical examination and to implement the biological testing. Statistical methods Participants were followed from the antibody measurement one month after the primary vaccine course until the occurrence of a SARS-CoV-2 infection, a first booster injection, last follow-up visit available, or death. For positive anti-NCP and increase in anti-Spike IgG, the exact time of infection was interval-censored. Thus, an interval-censoring analysis using Cox proportional hazard models were implemented to estimate the cumulative incidences of SARS-CoV-2 infection and plotted up to 5 months after the antibody measurement, according to the populations and to the antibody value terciles. The association between the antibody value terciles and the risk of infection was evaluated using log-rank tests. Cox proportional hazards models were used to model the association between antibody levels and the risk of SARS-CoV-2 infection. Antibodies levels were included in univariable Cox proportional hazards models implemented for each antibody transformed using restricted cubic splines with two boundary knots and three interior knots at the quantiles of the antibody to take into account non-linearity. Then, age (in years), sex, body mass index (BMI) (in kg/m 2 ), and number of vaccine doses received during the primary vaccine course were added to the model. Models were stratified on the calendar month of the last received dose during the primary vaccine course (May 2021 and before, June 2021, July 2021, August 2021, and after) and on the specific populations. The effect of anti-Spike IgG on SARS-CoV-2 infections was presented for specific values (15 BAU/mL half of the level of detection and 264 BAU/mL identified as protective for the risk of infection post-vaccination ( 8 )). The Hazard Ratios (HR) were estimated by dividing the probabilities of events estimated using the parameters from the multivariable model for each specific value (e.g. p(SARS-CoV-2 = 1, IgG = 264 BAU/mL) / (p(SARS-CoV-2 = 1, IgG = 15 BAU/mL)). Predictive performances of the antibody measurements in univariable and multivariable analysis, and of a model without antibody measurement were evaluated at five months using a time-dependent area under the receiver operating characteristic (AUROC) ( 20 ) corrected for optimism by bootstrap ( 21 ). Sensitivity analyses To evaluate the robustness of our results, we implemented several sensitivity analyses. First, we estimated the association and the predictive abilities of the antibody values on the risk of SARS-CoV-2 infection after the outcome definition was modified to consider only positive antigenic test and RT-PCR. Second, as participants who received three doses during the primary vaccine course were excluded as a third dose injection during the primary vaccine course was recommended for participants with lower immune response. Third, we divided the specific populations into participants with a metabolic chronic condition (diabetic and/or obese), infectious disease (HIV), and other specific populations to take into account the difference in vaccine response ( 19 ) and risk of infection by populations. The analysis was implemented using R 4.1.2, the package icenReg for the Cox proportional hazard model timeROC for the AUROC estimation. RESULTS Characteristics of the study populations Of 6,108 participants in the ANRS0001S COV-POPART cohort study, 3,693 were included, 2,570 in the specific populations, and 1,123 in the control group (Fig. 1). Most of the participants in the specific populations ended their primary vaccine course between 1st May and 31st June 2021 (71.8%) and between 1st June and 31st July 2021 (71.3%) for the control group. Participants in the specific populations were older (52.5 years interquartile range (IQR): [41.9; 61.0] vs 47.4 [37.0; 57.8]) compared to the control group. Mainly prescribed primary vaccine course was two doses of BNT162b2 (81.8% and 84.4%, respectively). Of participants in specific populations, 33.3% were with HIV, 29.1% were obese non-diabetic, and 16.6% were diabetic, 7.5% received 3 doses in the primary vaccine course (Table 1). Description of antibody responses One month after the last dose received during the primary vaccine course the geometric means of anti-spike IgG, anti-RBD IgG, and neutralizing antibodies were 836.8 [789.7; 886.7] BAU/mL, 354.2 [330.8; 379.2] IU/mL and 139.4 [130.9; 148.5], respectively in specific populations. In the control group, geometric mean concentrations were higher 1415.7 [1347.4; 1487.4] BAU/mL, 585.2 [555.8; 616.2] IU/mL and 317.1 [297.5; 337.9], respectively 22 (Supplementary Table 1 and Supplementary Fig. 1). Description of SARS-CoV-2 infections Over a median follow-up of 5.0 months [4.4; 5.8], 257 SARS-CoV-2 infections were observed, 143 (105 identified by antigenic test or PCR, 32 positive anti-NCP, and 6 increase in anti-Spike IgG antibody levels) in specific populations and 114 (99 identified by antigenic test or PCR, 13 positive anti-NCP, and 2 increase in anti-Spike IgG antibody levels) in the control group. During follow-up, 24 deaths were observed, all in participants from the specific populations. The majority of SARS-CoV-2 infections occurred in December 2021 (18.9% and 21.9%) or in January 2022 (39.2% and 50.0%), respectively in specific populations and in the control group. The cumulative probabilities at five months were 6.0% specific populations (95% confidence interval (CI): [5.0; 7.0]) and 10.1% in the control group (CI: 8.3; 11.9) (Supplementary table 2 and Supplementary Fig. 2). Anti-SARS-CoV-2 antibody measurements and SARS-CoV-2 infection The risk of SARS-CoV-2 infection was similar according to terciles of antibody markers in specific populations and from the control group (Fig. 2). In the control group, after adjustment, higher levels of anti-Spike IgG antibody were associated with a lower risk of SARS-CoV-2 infection. The decrease in risk was more pronounced for lower values, but the risk continued to decrease for higher values of anti-Spike IgG (Fig. 3). Participants with a value of 264 BAU/mL of anti-Spike IgG antibodies had a lower risk of SARS-CoV-2 infection (HR: 0.4 [0.0; 0.9]) compared to a participant with a value of 15 BAU/mL. Risk of SARS-CoV-2 infection was not differentiated by neutralizing and RBD IgG antibodies (Fig. 3). When SARS-CoV-2 infection was defined using only antigenic test and PCR, similar results were estimated with a decreased risk for participants with higher anti-Spike IgG value in the control group, and no association for other markers in both populations (Supplementary Table 3). Predictive performances In specific populations, the predictive performances of the three antibodies were moderate, with better performances for anti-Spike IgG (AUROC: 73.2%), then anti-RBD IgG (70.9%), and neutralizing antibodies (68.5%). Adding variables to the model, slightly increased the predictive performances (74.5%, 74.9, and 72.4%, respectively for anti-Spike IgG, RBD IgG, and neutralizing antibodies), which were similar and superior to the one of a model without antibodies (67.0%). In the control group, the performances of the antibody were superior both in univariable (78.3%, 77.0%, and 78.8%, respectively for anti-Spike IgG, RBD IgG, and neutralizing antibodies) and in multivariable (82.0%, 81.2%, and 81.4%, respectively for anti-Spike IgG, RBD IgG, and neutralizing antibodies). However, the gain induced by the addition of the antibodies to the model was low (81.2%) (Table 2). When defining SARS-CoV-2 infection based on antigenic test and RT-PCR only, the predictive abilities of the antibody values decreased and were similar in both populations (Anti-Spike IgG: 71.0% and 71.1%, anti-RBD IgG: 70.1% and 67.8%, Neutralizing antibodies: 66.7% and 68.8%, respectively in specific population and the control group) (Supplementary table 5). In specific populations who received two doses during the primary vaccine course, diabetic or obese, and other specific populations than diabetic, obese, and persons with HIV, the results were similar to the overall specific population. Among participants with HIV, the predictive performances were low both in univariable and multivariable analysis (Supplementary Table 6). Factors associated with the risk of SARS-CoV-2 infections After adjustment on IgG anti-Spike value, older age (HR: 0.8 [0.7; 0.9] and 0.7 [0.6; 0.8] for an increase of 10 years, respectively in specific populations and the control group) and being a woman (0.7 [0.5; 1.0] and 0.7 [0.5; 1.0], respectively) were significantly associated with a decreased risk of SARS-CoV-2 infection, in both specific populations and the control group. In specific populations, higher BMI (1.1 [1.0; 1.3] for an increase of 5 kg/m 2 ) was associated with an increased risk of SARS-CoV-2 infection (Supplementary Table 3). The same factors were identified when modifying the definition of SARS-CoV-2 infection (Supplementary Table 4). DISCUSSION The cumulative probability of SARS-CoV-2 infection was low and mainly occurred after 1st December 2021, corresponding to the Omicron BA.1 wave in France. Higher anti-Spike IgG antibody levels at one month after the primary vaccine course was associated with a decreased risk of SARS-CoV-2 infection in the control group, but not in the specific populations. Our results indicate moderate performances to discriminate participants experiencing SARS-CoV-2 infection in the 5 months following the primary vaccine course in the specific populations, and good, but similar to the one of a model without antibody results in control participants. We observed higher probabilities of SARS-CoV-2 infections in the control group, with a sharp increase at the end of the follow-up period, compared to specific populations. Participants from the specific populations may have engaged in less risky behavior than the general population. In participants with a lower antibody response, the role of the antibody response is less important than the cellular response ( 18 ). In addition, all participants of the control group were responders with high antibody measurements at baseline. A progressive decrease in the protection could explain the infections observed at a later follow-up. Finally, due to the recommendation, participants in the control group received their booster injection later than participants from specific populations and were more exposed to the Omicron wave. The same factors could explain the decreased risk of SARS-CoV-2 with increasing age. As identified in previous studies, women ( 22 , 23 ) were at lower risk, and participants with high BMI ( 24 ) were at higher risk of SARS-CoV-2 infection. Increased anti-Spike IgG antibody level was associated with a decreased risk of SARS-CoV-2 infection in the control group. In the specific populations, antibody levels were not associated with the risk of SARS-CoV-2, and their predictive abilities were moderate. The association between anti-spike IgG antibody level and the risk of SARS-CoV-2 infection has been previously published but differs for the RBD IgG and neutralizing antibody levels, which have been identified as potential correlates of protection ( 8 , 12 , 25 – 28 ). This divergence could be explained by the differences with the previous studies which were realized using clinical trial data when the alpha-variant was predominant ( 8 , 12 ), whereas this study presents data collected at the time of Omicron variant emergence which is associated with a decreased efficacy of vaccines ( 13 ). The moderate predictive abilities do not question the role of these antibodies and their usefulness for the evaluation of the vaccine response. Especially since the humoral response after the primo-vaccination is less mature than after the booster injection ( 29 ). This study has some limitations. We cannot study severe forms (i.e. hospitalization, intensive care, or mortality) of SARS-CoV-2 infections. Previous studies identified antibodies as correlates of protection for symptomatic but not asymptomatic SARS-CoV-2 infections ( 8 , 12 , 25 ) which could explain why antibody levels were not predictive for SARS-CoV-2 infections in our analyses. Data about RT-PCR or antigenic test results were collected during visits made at the convenience of the participants and anti-NCP tests do not have a 100% sensitivity and wane over time ( 30 ). Therefore, we cannot rule out that we missed asymptomatic SARS-CoV-2 infection. Here, we focused on the abilities of the antibody measurements to predict the risk of SARS-CoV-2 infection before the booster injection when the immune response might not be mature yet and this might explain our results. A future study will evaluate the SARS-CoV-2 risk after booster injection. RBD-IgG and neutralizing antibodies for the Omicron variant are only measured on sub-samples of each subpopulation within the ANRS0001S COV-POPART study and given the low number of SARS-CoV-2 infection in the study period we could not explore this further. In conclusion, in a context where the predominant variant was Omicron, the ability of antibody values to discriminate participants who will develop a SARS-CoV-2 infection after the primary vaccine course and before the 1st booster injection was moderate in the specific populations and good in the control group but similar to a model without SARS-CoV-2 antibodies. These results add to the existing body of evidence that people from specific populations might need more intensive primary vaccine schedules. Further studies including antibody measurements after the booster vaccination are need to study the role of antibody responses in people from specific populations with regard to the risk of SARS-CoV-2 infection. List Of Abbreviations AUROC Area under the receiver operating characteristic CI Confidence Interval HIV Human immunodeficiency virus HR Hazard Ratio IQR Interquartile range SARS-CoV-2 Severe acute respiratory syndrome Declarations ETHICS APPROVAL AND CONSENT TO PARTICIPATE Written informed consent was obtained from each participant before enrolment taking into account the GDPR (European Union General Data Protection Regulation) requirements. The protocol (N° EudraCT / ID-RCB: 2021-A00348-33) was conducted in accordance with the Declaration of Helsinki and French law for research involving human subjects (known as Loi Jardé). The protocol was approved by Ethics Committees: the committee for protection of participants engaged in research “CPP Nord-Ouest IV” (file number: 21.02.12.47147) and the French national data protection authority “CNIL” (Commission Nationale Informatique et Liberté, authorization number 921111v1). CONSENT FOR PUBLICATION Not applicable AVAILABILITY OF DATA AND MATERIALS The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. COMPETING INTERESTS PL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Astrazeneca, GlaxoSmithKline, Janssen, Merck Sharp & Dohme, Pfizer, Sanofi Pasteur and Support for attending meetings and/or travel from Pfizer, Sanofi Pasteur. JM has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Abbvie, Biogen, BMS, Boerhinger Ingelheim, Galapagos, GSK, Fresenius Kabi, Lilly, Mylan, Novartis, Pfizer, Sanofi and grants outside the submitted work from Lilly, Novartis JPS has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Pfizer and Astrazeneca OL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Sanofi Pasteur; Pfizer, Janssen and, non-financial support from Sanofi Pasteur; Pfizer, Janssen, GlaxoSmithKline and grant from GlaxoSmithKline. The other authors declare having no conflict of interest. FUNDING The ANRS0001S COV-POPART cohort is sponsored by Inserm – ANRS MIE, conducted with the support of ANRS MIE and funded by French ministries (Ministère des Solidarités et de la Santé and Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation). AUTORS ‘ CONTRIBUTION MC and LW: original draft; MC, PL, EL, LN, BB, JYB, MH, JS, ML, BL, JDL, JM, SNQ, JPS, BT, AT, JFV, FV, SC, ET, BP, RT, LM, XL, OL, and LW: writing – review and editing, conceptualization; PL, LN, BB, JUB, MH, JS, ML, BL, JDL, JM, SNQ, JPS, BT; AT, JFV, FV, SC, ET, BP, WL, and OL: investigation; LW and MC: methodology; LW and MC: formal analysis; PL, LW, MG, AB, ET, XL and OL: project administration. All authors read, revised, and approved the final manuscript. References Voysey M, Clemens SAC, Madhi SA, Weckx LY, Folegatti PM, Aley PK, et al. 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Tables Table 1 Characteristics at the end of the primary vaccine course in participants of the ANRS0001S COV-POPART cohort Specific populations (n = 2570) Control group (n = 1123) Characteristics N Median [IQR] or n (%) N Median [IQR] or n (%) Age (years) 2570 52.5 [41.9; 61.0] 1123 47.4 [37.0; 57.8] < 65 years 2146 (83.3) 958 (85.3) ≥ 65 years 429 (16.7) 165 (14.7) Men 2570 1324 (51.5) 1123 552 (49.2) BMI (kg/m 2 ) 2570 25.6 [22.4; 31.1] 1123 23.6 [21.5; 26.0] Population 2570 1123 Solid cancer 172 (6.7) - Solid organs transplanted 70 (2.7) - Hematopoietic stem cell transplant 46 (1.8) - Chronic kidney disease and dialysis 75 (2.9) - Systemic autoimmune diseases 139 (5.4) - Inflammatory rheumatic disease 159 (6.2) - MS/NMOSD 363 (14.1) - Hypogammaglobulinemia 36 (1.4) - Diabetic 427 (16.6) - Obese non-diabetic 748 (29.1) - HIV 856 (33.3) - Number of doses in the primary vaccine course 2570 1123 2 2378 (92.5) 1123 (100.0) 3 192 (7.5) 0 (0.0) Type of vaccine 2564 1120 BNT162b2 + BNT162b2 2098 (81.8) 945 (84.4) BNT162b2 + BNT162b2 + BNT162b2 165 (6.4) 0 (0.0) mRNA-1273 + mRNA-1273 226 (8.8) 99 (8.8) AZD1222 + AZD1222 28 (1.1) 45 (4.0) Others 47 (1.8) 31 (2.8) Calendar period of last dose injection 2570 1123 April 2021 134 (5.2) 25 (2.2) May 2021 959 (37.3) 129 (11.5) June 2021 885 (34.4) 425 (37.8) July 2021 361 (14.0) 376 (33.5) August 2021 130 (5.1) 117 (10.4) September 2021 63 (2.5) 38 (3.4) After September 2021 38 (1.5) 13 (1.2) Monoclonal antibodies use 2570 19 (0.7) 1123 0 (0.0) Other morbidities 2570 1123 0 2079 (80.9) 1123 (100.0) 1 462 (18.0) 0 (0.0) 2 29 (1.1) 0 (0.0) Control group: participants not from specific population of interest Table 2 Area under receiving operating characteristic (AUROC) of the antibody value for the prediction of SARS-CoV-2 infection at five months after baseline in participants from the ANRS0001S COV-POPART cohort Specific populations Control group Antibodies Univariable Multivariable* Univariable Multivariable** Anti-Spike IgG (BAU/mL) 73.2 74.5 78.3 82.0 Anti-RBD IgG (IU/mL) 70.4 74.9 77.0 81.2 Neutralizing antibodies (fold dilution) 68.5 72.4 78.8 81.4 Model without antibody - 67.0 - 81.2 AUROC are corrected for optimism using 1000 bootstrap samples * Cox proportional hazards models adjusted on age, sex, BMI, number of doses and number of comorbidities and stratified by month of the last received injection during the primary vaccine course and the specific population ** Cox proportional hazards models adjusted on age, sex and BMI Control group: participants not from specific populations Additional Declarations Competing interest reported. PL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Astrazeneca, GlaxoSmithKline, Janssen, Merck Sharp & Dohme, Pfizer, Sanofi Pasteur and Support for attending meetings and/or travel from Pfizer, Sanofi Pasteur. JM has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Abbvie, Biogen, BMS, Boerhinger Ingelheim, Galapagos, GSK, Fresenius Kabi, Lilly, Mylan, Novartis, Pfizer, Sanofi and grants outside the submitted work from Lilly, Novartis JPS has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Pfizer and Astrazeneca OL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Sanofi Pasteur; Pfizer, Janssen and, non-financial support from Sanofi Pasteur; Pfizer, Janssen, GlaxoSmithKline and grant from GlaxoSmithKline. The other authors declare having no conflict of interest. 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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-4510677","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":311230076,"identity":"a070079d-6e08-4759-af1b-8bca95f8ba0c","order_by":0,"name":"Mathieu Chalouni","email":"","orcid":"","institution":"Université de Bordeaux, ISPED, INSERM, Bordeaux Population Health Research Center, U1219","correspondingAuthor":false,"prefix":"","firstName":"Mathieu","middleName":"","lastName":"Chalouni","suffix":""},{"id":311230077,"identity":"efbe9585-8a6d-49bb-8760-0ae254d1d87c","order_by":1,"name":"Paul Loubet","email":"","orcid":"","institution":"INSERM, F-CRIN, Reseau Innovative Clinical Research in Vaccinology (IREIVAC)","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Loubet","suffix":""},{"id":311230078,"identity":"918f9489-8f7c-420e-8d3e-879e6691c8ae","order_by":2,"name":"Edouard Lhomme","email":"","orcid":"","institution":"Université de Bordeaux, ISPED, INSERM, Bordeaux Population Health Research Center, U1219","correspondingAuthor":false,"prefix":"","firstName":"Edouard","middleName":"","lastName":"Lhomme","suffix":""},{"id":311230079,"identity":"a812f7db-00ed-4bd8-8c8d-76f89fc6a1c8","order_by":3,"name":"Laetitia Ninove","email":"","orcid":"","institution":"Aix-Marseille Université, Institut de Recherche pour le, Institut Hospitalo-Universitaire Méditerranée Infection","correspondingAuthor":false,"prefix":"","firstName":"Laetitia","middleName":"","lastName":"Ninove","suffix":""},{"id":311230080,"identity":"1676cc4d-563e-4ffa-8985-4c6781aa37a1","order_by":4,"name":"Benoit Barrou","email":"","orcid":"","institution":"Pitié-Salpêtrière Hospital","correspondingAuthor":false,"prefix":"","firstName":"Benoit","middleName":"","lastName":"Barrou","suffix":""},{"id":311230081,"identity":"cecf5688-222b-48fd-8c09-a35339daf96e","order_by":5,"name":"Jean-Yves Blay","email":"","orcid":"","institution":"Claude Bernard University Lyon 1","correspondingAuthor":false,"prefix":"","firstName":"Jean-Yves","middleName":"","lastName":"Blay","suffix":""},{"id":311230082,"identity":"120a31f6-3e2d-4307-97e4-e84813e14d01","order_by":6,"name":"Maryvonne Hourmant","email":"","orcid":"","institution":"CHU Nantes","correspondingAuthor":false,"prefix":"","firstName":"Maryvonne","middleName":"","lastName":"Hourmant","suffix":""},{"id":311230083,"identity":"fadd699e-9e75-4ba9-bf60-ac04f45f979e","order_by":7,"name":"Jérome Seze","email":"","orcid":"","institution":"CIC INSERM 1434, Strasbourg university hospital","correspondingAuthor":false,"prefix":"","firstName":"Jérome","middleName":"","lastName":"Seze","suffix":""},{"id":311230084,"identity":"414a88c6-6b82-4944-b6c8-27a49e891f6c","order_by":8,"name":"Martine Laville","email":"","orcid":"","institution":"INSERM U1191/UMR 5203, Université de Montpellier","correspondingAuthor":false,"prefix":"","firstName":"Martine","middleName":"","lastName":"Laville","suffix":""},{"id":311230085,"identity":"d1ebf02f-8972-41d1-824a-c61784450ce9","order_by":9,"name":"Bruno Laviolle","email":"","orcid":"","institution":"Université de Rennes, CHU Rennes, INSERM","correspondingAuthor":false,"prefix":"","firstName":"Bruno","middleName":"","lastName":"Laviolle","suffix":""},{"id":311230086,"identity":"dddcd01b-37c9-45e6-8f03-a31e54e37202","order_by":10,"name":"Jean-Daniel Lelièvre","email":"","orcid":"","institution":"Vaccine Research Institute, INSERM et APHP, Hôpital H. 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18:36:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4510677/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4510677/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-024-09861-5","type":"published","date":"2024-09-27T15:58:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59051066,"identity":"7c76f210-cb37-4bae-9fb2-5f06ebf688a9","added_by":"auto","created_at":"2024-06-25 20:02:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":120205,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the participants from the ANRS0001S COV-POPART cohort included in the study\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4510677/v1/a1ad120621238e06e0edcda5.png"},{"id":59051068,"identity":"b35336bc-f4ad-468a-a0be-a81a0f8322dd","added_by":"auto","created_at":"2024-06-25 20:02:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":287909,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative probabilities of SARS-CoV-2 infections from one month after the primary vaccine course according to the terciles of antibodies values in participants from the ANRS0001S COV-POPART cohort\u003c/p\u003e\n\u003cp\u003eP-values presented are from the log-rank tests for the global effect of antibodies categorized by terciles.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4510677/v1/e4a999b1b33ddb273cee6c32.png"},{"id":59051070,"identity":"9069baab-d609-4415-8470-230f8023ba4b","added_by":"auto","created_at":"2024-06-25 20:02:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":110716,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between antibody values and risk of SARS-CoV-2 infections after the primary vaccine course in participants of the ANRS0001S COV-POPART cohort study. Models were adjusted on age, sex, BMI, number of doses and number of other morbidities and stratified by month of the last received injection during the primary vaccine course and the specific population in specific populations and age, sex and BMI in the control group.\u003c/p\u003e\n\u003cp\u003eDark line is the Hazard Ratio (HR) estimated by a Cox proportional hazards model, gray area is the 95% confidence of the HR, and the white lines represent the position of the knots. The antibody value associated with the median probability of predicted events by the model served as the reference for estimating the HR.\u003c/p\u003e\n\u003cp\u003eValues associated with the median probability were: 1470 BAU/mL,1687 IU/mL, and 640 fold dilution in specific populations, and 2033 BAU/mL, 1524 IU/mL, and 320 in the control group, respectively.\u003c/p\u003e\n\u003cp\u003eP-values of the associations: 0.15, 0.22, and 0.85 for anti-Spike IgG, RBD, and neutralizing antibody levels in specific populations, and 0.01, 0.17, and 0.09, respectively in the control group.\u003c/p\u003e\n\u003cp\u003eControl group: participants not from specific populations\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4510677/v1/be26fba133660e6063de1a35.png"},{"id":65627567,"identity":"2c3b977d-4949-47ea-9fa2-e6d7c642453e","added_by":"auto","created_at":"2024-09-30 16:16:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1195076,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4510677/v1/1b1c1107-cc98-45f5-93fc-851125b015ec.pdf"},{"id":59051069,"identity":"056c67c7-c04d-44f2-849e-1b9508ac53fd","added_by":"auto","created_at":"2024-06-25 20:02:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":367649,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIALS.docx","url":"https://assets-eu.researchsquare.com/files/rs-4510677/v1/b192832887350f93b1cdfa2a.docx"}],"financialInterests":"Competing interest reported. PL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Astrazeneca, GlaxoSmithKline, Janssen, Merck Sharp \u0026 Dohme, Pfizer, Sanofi Pasteur and Support for attending meetings and/or travel from Pfizer, Sanofi Pasteur.\nJM has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Abbvie, Biogen, BMS, Boerhinger Ingelheim, Galapagos, GSK, Fresenius Kabi, Lilly, Mylan, Novartis, Pfizer, Sanofi and grants outside the submitted work from Lilly, Novartis\nJPS has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Pfizer and Astrazeneca\nOL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Sanofi Pasteur; Pfizer, Janssen and, non-financial support from Sanofi Pasteur; Pfizer, Janssen, GlaxoSmithKline and grant from GlaxoSmithKline.\nThe other authors declare having no conflict of interest.","formattedTitle":"Association between humoral serological markers levels and risk of SARS-CoV-2 infection after the primary COVID-19 vaccine course among ANRS0001S COV- POPART cohort participants","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSince the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, several vaccines have been validated and recommended (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e–\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In France, the Covid-19 vaccination campaign started in December 2020, with BNT162b2 vaccine. In May 2021, three additional vaccines were available: mRNA-1273, ChAdOx1-nCoV19, and Ad26.COV2.S. For some specific populations a third dose in the primary vaccine course was recommended (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Booster injections were recommended from October 2021 onwards (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). COVID-19 vaccines have been shown to reduce the risk of severe diseases, hospitalization, and death (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Binding and neutralizing antibodies have been particularly studied as prognostic factors and potential correlates of protection (\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e–\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, these studies were essentially conducted in clinical trials evaluating the ChadOx1 nCoV-19 (AZD1222) and ARNm-1273 (Moderna) vaccines in a context where the predominant circulating variant was the alpha variant (B.1.1.7) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Other variants have emerged, in particular, the Omicron (B.1.1.529) variant and sub-variants, which are associated with a decreased vaccine efficacy (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), higher breakthrough infections, but decreased severity (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) compared to previous variants or original strain. The current prognostic value of antibody levels in vaccinated populations is still not completely explored. In populations at risk of developing severe forms of SARS-CoV-2 infection, i.e immunocompromised patients, Covid-19 vaccine effectiveness is lower than in the overall population (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and the role of the antibody response could be less important than the cellular response (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe aimed to evaluate the prognostic value of humoral serological markers levels, i.e. anti-Spike IgG, anti-receptor binding domain (RBD) IgG, and neutralizing antibodies, measured one month after the last dose received during the primary vaccine course for the risk of SARS-CoV-2 infection up to 6 months after the lase dose in the ANRS0001S COV-POPART cohort.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e \u003cstrong\u003eStudy design\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eANRS0001S COV-POPART cohort (NCT04824651, Registration Date: 03/25/2021) is a French nationwide multicenter prospective cohort study of specific populations (solid cancer, solid organs transplanted, hematopoietic stem cell transplant, chronic kidney disease and dialysis, systemic autoimmune diseases, inflammatory rheumatic disease, multiple sclerosis/neuromyelitis optica spectrum disorder, hypogammaglobulinemia, diabetic, obese non-diabetic, and HIV) and a group without the above-mentioned chronic conditions. Participants older than 18 years, without known history of SARS-CoV-2 infection at inclusion were included between March 25th, 2021 to December 31st, 2021. The study design is further described in previous publications (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Primary vaccine course choice was made according to the authorization, availability, national recommendations, and prescriber choice (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Visits for characteristics and antibodies were measured were scheduled before the first dose injection, at the time of the first, second, and third dose if any, and 6, 12, and 24 months after the second dose. Supplementary visits were implemented at the time and one month after a booster injection (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eStudy population\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWe included participants from the ANRS0001S COV-POPART who received at least two doses during the primary vaccine course (a third dose within the primary course was defined as an injection in a three-month window after the second dose), had at least one antibody value among anti-Spike IgG, anti-RBD IgG, or neutralizing antibodies one month after the last dose received during the primary vaccine course, and without SARS-CoV-2 infection before the antibody level measurement.\u003c/p\u003e\u003cp\u003eAll analyses were implemented separately between participants from specific populations and the control group given the heterogeneity in antibody responses and the usually lower antibody response in specific populations compared to the overall population (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eAntibody measurements\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eAntibody levels were measured one month (between 21 days and 56 days) after the last dose received during the primary vaccine course. The samples analyzed as part of the study were managed and stored within the « Biothèque ANRS ». All serological analyses were carried out centrally at the “Unité des virus émergents” Aix-Marseille Université, Institut de Recherche pour le Développement 190, Inserm 1207, Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France. Antibody assays used are described in the supplementary material (Supplementary materials antibodies measurement). For undetectable antibodies, half of the detection cut-off was imputed (15 BAU/mL and 10 fold dilution for anti-Spike IgG, and neutralizing antibodies, respectively).\u003c/p\u003e\u003cp\u003eWe estimated the geometric means of the anti-Spike IgG, anti-RBD IgG, and neutralizing antibody titers measured one month after the last injection.\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eSARS-CoV-2 infection\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eSARS-CoV-2 infection was defined by a positive antigenic test or RT-PCR, positive anti-NCP antibodies, or an increase in anti-Spike IgG antibody levels in the absence of a booster injection or the prescription of monoclonal antibodies. Anti-NCP antibodies are systematically evaluated at each visit in all participants as are anti-Spike IgG antibody levels. In case of a positive antigenic or RT-PCR test performed outside the cohort protocol, participants were asked to consult within 72 hours for a clinical examination and to implement the biological testing.\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eStatistical methods\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eParticipants were followed from the antibody measurement one month after the primary vaccine course until the occurrence of a SARS-CoV-2 infection, a first booster injection, last follow-up visit available, or death.\u003c/p\u003e\u003cp\u003eFor positive anti-NCP and increase in anti-Spike IgG, the exact time of infection was interval-censored. Thus, an interval-censoring analysis using Cox proportional hazard models were implemented to estimate the cumulative incidences of SARS-CoV-2 infection and plotted up to 5 months after the antibody measurement, according to the populations and to the antibody value terciles. The association between the antibody value terciles and the risk of infection was evaluated using log-rank tests.\u003c/p\u003e\u003cp\u003eCox proportional hazards models were used to model the association between antibody levels and the risk of SARS-CoV-2 infection. Antibodies levels were included in univariable Cox proportional hazards models implemented for each antibody transformed using restricted cubic splines with two boundary knots and three interior knots at the quantiles of the antibody to take into account non-linearity. Then, age (in years), sex, body mass index (BMI) (in kg/m\u003csup\u003e2\u003c/sup\u003e), and number of vaccine doses received during the primary vaccine course were added to the model. Models were stratified on the calendar month of the last received dose during the primary vaccine course (May 2021 and before, June 2021, July 2021, August 2021, and after) and on the specific populations. The effect of anti-Spike IgG on SARS-CoV-2 infections was presented for specific values (15 BAU/mL half of the level of detection and 264 BAU/mL identified as protective for the risk of infection post-vaccination (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)). The Hazard Ratios (HR) were estimated by dividing the probabilities of events estimated using the parameters from the multivariable model for each specific value (e.g. p(SARS-CoV-2 = 1, IgG = 264 BAU/mL) / (p(SARS-CoV-2 = 1, IgG = 15 BAU/mL)).\u003c/p\u003e\u003cp\u003ePredictive performances of the antibody measurements in univariable and multivariable analysis, and of a model without antibody measurement were evaluated at five months using a time-dependent area under the receiver operating characteristic (AUROC) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) corrected for optimism by bootstrap (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eSensitivity analyses\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eTo evaluate the robustness of our results, we implemented several sensitivity analyses. First, we estimated the association and the predictive abilities of the antibody values on the risk of SARS-CoV-2 infection after the outcome definition was modified to consider only positive antigenic test and RT-PCR.\u003c/p\u003e\u003cp\u003eSecond, as participants who received three doses during the primary vaccine course were excluded as a third dose injection during the primary vaccine course was recommended for participants with lower immune response.\u003c/p\u003e\u003cp\u003eThird, we divided the specific populations into participants with a metabolic chronic condition (diabetic and/or obese), infectious disease (HIV), and other specific populations to take into account the difference in vaccine response (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and risk of infection by populations.\u003c/p\u003e\u003cp\u003eThe analysis was implemented using R 4.1.2, the package icenReg for the Cox proportional hazard model timeROC for the AUROC estimation.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cstrong\u003eCharacteristics of the study populations\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eOf 6,108 participants in the ANRS0001S COV-POPART cohort study, 3,693 were included, 2,570 in the specific populations, and 1,123 in the control group (Fig.\u0026nbsp;1). Most of the participants in the specific populations ended their primary vaccine course between 1st May and 31st June 2021 (71.8%) and between 1st June and 31st July 2021 (71.3%) for the control group. Participants in the specific populations were older (52.5 years interquartile range (IQR): [41.9; 61.0] \u003cem\u003evs\u003c/em\u003e 47.4 [37.0; 57.8]) compared to the control group. Mainly prescribed primary vaccine course was two doses of BNT162b2 (81.8% and 84.4%, respectively). Of participants in specific populations, 33.3% were with HIV, 29.1% were obese non-diabetic, and 16.6% were diabetic, 7.5% received 3 doses in the primary vaccine course (Table\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eDescription of antibody responses\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eOne month after the last dose received during the primary vaccine course the geometric means of anti-spike IgG, anti-RBD IgG, and neutralizing antibodies were 836.8 [789.7; 886.7] BAU/mL, 354.2 [330.8; 379.2] IU/mL and 139.4 [130.9; 148.5], respectively in specific populations. In the control group, geometric mean concentrations were higher 1415.7 [1347.4; 1487.4] BAU/mL, 585.2 [555.8; 616.2] IU/mL and 317.1 [297.5; 337.9], respectively \u003csup\u003e22\u003c/sup\u003e (Supplementary Table\u0026nbsp;1 and Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eDescription of SARS-CoV-2 infections\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eOver a median follow-up of 5.0 months [4.4; 5.8], 257 SARS-CoV-2 infections were observed, 143 (105 identified by antigenic test or PCR, 32 positive anti-NCP, and 6 increase in anti-Spike IgG antibody levels) in specific populations and 114 (99 identified by antigenic test or PCR, 13 positive anti-NCP, and 2 increase in anti-Spike IgG antibody levels) in the control group. During follow-up, 24 deaths were observed, all in participants from the specific populations. The majority of SARS-CoV-2 infections occurred in December 2021 (18.9% and 21.9%) or in January 2022 (39.2% and 50.0%), respectively in specific populations and in the control group. The cumulative probabilities at five months were 6.0% specific populations (95% confidence interval (CI): [5.0; 7.0]) and 10.1% in the control group (CI: 8.3; 11.9) (Supplementary table 2 and Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eAnti-SARS-CoV-2 antibody measurements and SARS-CoV-2 infection\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eThe risk of SARS-CoV-2 infection was similar according to terciles of antibody markers in specific populations and from the control group (Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eIn the control group, after adjustment, higher levels of anti-Spike IgG antibody were associated with a lower risk of SARS-CoV-2 infection. The decrease in risk was more pronounced for lower values, but the risk continued to decrease for higher values of anti-Spike IgG (Fig.\u0026nbsp;3). Participants with a value of 264 BAU/mL of anti-Spike IgG antibodies had a lower risk of SARS-CoV-2 infection (HR: 0.4 [0.0; 0.9]) compared to a participant with a value of 15 BAU/mL. Risk of SARS-CoV-2 infection was not differentiated by neutralizing and RBD IgG antibodies (Fig.\u0026nbsp;3).\u003c/p\u003e\u003cp\u003eWhen SARS-CoV-2 infection was defined using only antigenic test and PCR, similar results were estimated with a decreased risk for participants with higher anti-Spike IgG value in the control group, and no association for other markers in both populations (Supplementary Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003ePredictive performances\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eIn specific populations, the predictive performances of the three antibodies were moderate, with better performances for anti-Spike IgG (AUROC: 73.2%), then anti-RBD IgG (70.9%), and neutralizing antibodies (68.5%). Adding variables to the model, slightly increased the predictive performances (74.5%, 74.9, and 72.4%, respectively for anti-Spike IgG, RBD IgG, and neutralizing antibodies), which were similar and superior to the one of a model without antibodies (67.0%). In the control group, the performances of the antibody were superior both in univariable (78.3%, 77.0%, and 78.8%, respectively for anti-Spike IgG, RBD IgG, and neutralizing antibodies) and in multivariable (82.0%, 81.2%, and 81.4%, respectively for anti-Spike IgG, RBD IgG, and neutralizing antibodies). However, the gain induced by the addition of the antibodies to the model was low (81.2%) (Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eWhen defining SARS-CoV-2 infection based on antigenic test and RT-PCR only, the predictive abilities of the antibody values decreased and were similar in both populations (Anti-Spike IgG: 71.0% and 71.1%, anti-RBD IgG: 70.1% and 67.8%, Neutralizing antibodies: 66.7% and 68.8%, respectively in specific population and the control group) (Supplementary table 5).\u003c/p\u003e\u003cp\u003eIn specific populations who received two doses during the primary vaccine course, diabetic or obese, and other specific populations than diabetic, obese, and persons with HIV, the results were similar to the overall specific population. Among participants with HIV, the predictive performances were low both in univariable and multivariable analysis (Supplementary Table\u0026nbsp;6).\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eFactors associated with the risk of SARS-CoV-2 infections\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eAfter adjustment on IgG anti-Spike value, older age (HR: 0.8 [0.7; 0.9] and 0.7 [0.6; 0.8] for an increase of 10 years, respectively in specific populations and the control group) and being a woman (0.7 [0.5; 1.0] and 0.7 [0.5; 1.0], respectively) were significantly associated with a decreased risk of SARS-CoV-2 infection, in both specific populations and the control group. In specific populations, higher BMI (1.1 [1.0; 1.3] for an increase of 5 kg/m\u003csup\u003e2\u003c/sup\u003e) was associated with an increased risk of SARS-CoV-2 infection (Supplementary Table\u0026nbsp;3). The same factors were identified when modifying the definition of SARS-CoV-2 infection (Supplementary Table\u0026nbsp;4).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe cumulative probability of SARS-CoV-2 infection was low and mainly occurred after 1st December 2021, corresponding to the Omicron BA.1 wave in France. Higher anti-Spike IgG antibody levels at one month after the primary vaccine course was associated with a decreased risk of SARS-CoV-2 infection in the control group, but not in the specific populations. Our results indicate moderate performances to discriminate participants experiencing SARS-CoV-2 infection in the 5 months following the primary vaccine course in the specific populations, and good, but similar to the one of a model without antibody results in control participants.\u003c/p\u003e\u003cp\u003eWe observed higher probabilities of SARS-CoV-2 infections in the control group, with a sharp increase at the end of the follow-up period, compared to specific populations. Participants from the specific populations may have engaged in less risky behavior than the general population. In participants with a lower antibody response, the role of the antibody response is less important than the cellular response (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In addition, all participants of the control group were responders with high antibody measurements at baseline. A progressive decrease in the protection could explain the infections observed at a later follow-up. Finally, due to the recommendation, participants in the control group received their booster injection later than participants from specific populations and were more exposed to the Omicron wave. The same factors could explain the decreased risk of SARS-CoV-2 with increasing age. As identified in previous studies, women (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) were at lower risk, and participants with high BMI (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) were at higher risk of SARS-CoV-2 infection.\u003c/p\u003e\u003cp\u003eIncreased anti-Spike IgG antibody level was associated with a decreased risk of SARS-CoV-2 infection in the control group. In the specific populations, antibody levels were not associated with the risk of SARS-CoV-2, and their predictive abilities were moderate. The association between anti-spike IgG antibody level and the risk of SARS-CoV-2 infection has been previously published but differs for the RBD IgG and neutralizing antibody levels, which have been identified as potential correlates of protection (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e–\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). This divergence could be explained by the differences with the previous studies which were realized using clinical trial data when the alpha-variant was predominant (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), whereas this study presents data collected at the time of Omicron variant emergence which is associated with a decreased efficacy of vaccines (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The moderate predictive abilities do not question the role of these antibodies and their usefulness for the evaluation of the vaccine response. Especially since the humoral response after the primo-vaccination is less mature than after the booster injection (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study has some limitations. We cannot study severe forms (i.e. hospitalization, intensive care, or mortality) of SARS-CoV-2 infections. Previous studies identified antibodies as correlates of protection for symptomatic but not asymptomatic SARS-CoV-2 infections (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) which could explain why antibody levels were not predictive for SARS-CoV-2 infections in our analyses. Data about RT-PCR or antigenic test results were collected during visits made at the convenience of the participants and anti-NCP tests do not have a 100% sensitivity and wane over time (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Therefore, we cannot rule out that we missed asymptomatic SARS-CoV-2 infection.\u003c/p\u003e\u003cp\u003eHere, we focused on the abilities of the antibody measurements to predict the risk of SARS-CoV-2 infection before the booster injection when the immune response might not be mature yet and this might explain our results. A future study will evaluate the SARS-CoV-2 risk after booster injection. RBD-IgG and neutralizing antibodies for the Omicron variant are only measured on sub-samples of each subpopulation within the ANRS0001S COV-POPART study and given the low number of SARS-CoV-2 infection in the study period we could not explore this further.\u003c/p\u003e\u003cp\u003eIn conclusion, in a context where the predominant variant was Omicron, the ability of antibody values to discriminate participants who will develop a SARS-CoV-2 infection after the primary vaccine course and before the 1st booster injection was moderate in the specific populations and good in the control group but similar to a model without SARS-CoV-2 antibodies. These results add to the existing body of evidence that people from specific populations might need more intensive primary vaccine schedules. Further studies including antibody measurements after the booster vaccination are need to study the role of antibody responses in people from specific populations with regard to the risk of SARS-CoV-2 infection.\u003c/p\u003e"},{"header":"List Of Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the receiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman immunodeficiency virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARS-CoV-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSevere acute respiratory syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from each participant before enrolment taking into account the GDPR (European Union General Data Protection Regulation) requirements. The protocol (N° EudraCT / ID-RCB: 2021-A00348-33) was conducted in accordance with the Declaration of Helsinki and French law for research involving human subjects (known as Loi Jardé). The protocol was approved by Ethics Committees: the committee for protection of participants engaged in research “CPP Nord-Ouest IV” (file number: 21.02.12.47147) and the French national data protection authority “CNIL” (Commission Nationale Informatique et Liberté, authorization number 921111v1).\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 used and/or analysed during the current study 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\u003ePL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Astrazeneca, GlaxoSmithKline, Janssen, Merck Sharp \u0026amp; Dohme, Pfizer, Sanofi Pasteur and Support for attending meetings and/or travel from Pfizer, Sanofi Pasteur.\u003c/p\u003e\n\u003cp\u003eJM has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Abbvie, Biogen, BMS, Boerhinger Ingelheim, Galapagos, GSK, Fresenius Kabi, Lilly, Mylan, Novartis, Pfizer, Sanofi and grants outside the submitted work from Lilly, Novartis\u003c/p\u003e\n\u003cp\u003eJPS has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Pfizer and Astrazeneca\u003cbr\u003eOL has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Sanofi Pasteur; Pfizer, Janssen and, non-financial support from Sanofi Pasteur; Pfizer, Janssen, GlaxoSmithKline and grant from GlaxoSmithKline.\u003cbr\u003eThe other authors declare having no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ANRS0001S COV-POPART cohort is sponsored by Inserm – ANRS MIE, conducted with the support of ANRS MIE and funded by French ministries (Ministère des Solidarités et de la Santé and Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTORS\u0026nbsp;‘ CONTRIBUTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMC and LW: original draft; MC, PL, EL, LN, BB, JYB, MH, JS, ML, BL, JDL, JM, SNQ, JPS, BT, AT, JFV, FV, SC, ET, BP, RT, LM, XL, OL, and LW: writing – review and editing, conceptualization; PL, LN, BB, JUB, MH, JS, ML, BL, JDL, JM, SNQ, JPS, BT; AT, JFV, FV, SC, ET, BP, WL, and OL: investigation; LW and MC: methodology; LW and MC: formal analysis; PL, LW, MG, AB, ET, XL and OL: project administration. All authors read, revised, and approved the final manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVoysey M, Clemens SAC, Madhi SA, Weckx LY, Folegatti PM, Aley PK, et al. Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK. Lancet Lond Engl. 2021;397(10269):99\u0026ndash;111.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolack FP, Thomas SJ, Kitchin N, Absalon J, Gurtman A, Lockhart S, et al. Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine. N Engl J Med. 2020;383(27):2603\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Kaabi N, Zhang Y, Xia S, Yang Y, Al Qahtani MM, Abdulrazzaq N, et al. Effect of 2 Inactivated SARS-CoV-2 Vaccines on Symptomatic COVID-19 Infection in Adults: A Randomized Clinical Trial. JAMA. 2021;326(1):35\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaute Autorit\u0026eacute; de Sant\u0026eacute; [Internet]. [cited 2023 Jan 17]. 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Immune correlates analysis of the mRNA-1273 COVID-19 vaccine efficacy clinical trial. Science. 2022;375(6576):43\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePegu A, O\u0026rsquo;Connell SE, Schmidt SD, O\u0026rsquo;Dell S, Talana CA, Lai L, et al. Durability of mRNA-1273 vaccine-induced antibodies against SARS-CoV-2 variants. Science. 2021;373(6561):1372\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolter N, Jassat W, Walaza S, Welch R, Moultrie H, Groome M, et al. Early assessment of the clinical severity of the SARS-CoV-2 omicron variant in South Africa: a data linkage study. Lancet Lond Engl. 2022;399(10323):437\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaslo C, Friedland R, Toubkin M, Laubscher A, Akaloo T, Kama B. Characteristics and Outcomes of Hospitalized Patients in South Africa During the COVID-19 Omicron Wave Compared With Previous Waves. 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One-month humoral response following two or three doses of mRNA Covid-19 vaccines as primary vaccination in specific populations in France: first results from the ANRS0001S COV-POPART cohort. Clin Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Dis. 2022;S1198-743X(22)00522-5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlanche P, Dartigues JF, Jacqmin-Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med. 2013;32(30):5381\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoons KGM, Altman DG, Reitsma JB, Ioannidis JPA, Macaskill P, Steyerberg EW, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu C, Lee J, Ta C, Soroush A, Rogers JR, Kim JH, et al. Risk Factors Associated With SARS-CoV-2 Breakthrough Infections in Fully mRNA-Vaccinated Individuals: Retrospective Analysis. JMIR Public Health Surveill. 2022;8(5):e35311.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamal JM, Appana S, Wang M, Leon-Novelo L, Bakota E, Ye Y, et al. Trends and Correlates of Breakthrough Infections With SARS-CoV-2. Front Public Health. 2022;10:856532.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStefan N. Metabolic disorders, COVID-19 and vaccine-breakthrough infections. Nat Rev Endocrinol. 2022;18(2):75\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAldridge RW, Yavlinsky A, Nguyen V, Eyre MT, Shrotri M, Navaratnam AMD, et al. SARS-CoV-2 antibodies and breakthrough infections in the Virus Watch cohort. 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SARS-CoV-2 vaccine-induced antibodies protect against Omicron breakthrough infection. iScience. 2023;26(9):107621.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChu L, Vrbicky K, Montefiori D, Huang W, Nestorova B, Chang Y, et al. Immune response to SARS-CoV-2 after a booster of mRNA-1273: an open-label phase 2 trial. Nat Med. 2022;28(5):1042\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFollmann D, Janes HE, Buhule OD, Zhou H, Girard B, Marks K et al. Antinucleocapsid Antibodies After SARS-CoV-2 Infection in the Blinded Phase of the Randomized, Placebo-Controlled mRNA-1273 COVID-19 Vaccine Efficacy Clinical Trial. Ann Intern Med. 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGallian P, Pastorino B, Morel P, Chiaroni J, Ninove L, de Lamballerie X. Lower prevalence of antibodies neutralizing SARS-CoV-2 in group O French blood donors. Antiviral Res. 2020;181:104880.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":" \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 \u003cdiv class=\"SimplePara\"\u003eCharacteristics at the end of the primary vaccine course in participants of the ANRS0001S COV-POPART cohort\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpecific populations\u003c/div\u003e \u003cdiv class=\"SimplePara\"\u003e(n\u0026thinsp;=\u0026thinsp;2570)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eControl group (n\u0026thinsp;=\u0026thinsp;1123)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eCharacteristics\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eN\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eMedian [IQR] or n (%)\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eN\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eMedian [IQR] or n (%)\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAge (years)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e52.5 [41.9; 61.0]\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e47.4 [37.0; 57.8]\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;65 years\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e2146 (83.3)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e958 (85.3)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u0026ge;\u0026thinsp;65 years\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e429 (16.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e165 (14.7)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMen\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e1324 (51.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e552 (49.2)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eBMI (kg/m\u003c/span\u003e\u003csup\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e25.6 [22.4; 31.1]\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e23.6 [21.5; 26.0]\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003ePopulation\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eSolid cancer\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e172 (6.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eSolid organs transplanted\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e70 (2.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eHematopoietic stem cell transplant\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e46 (1.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eChronic kidney disease and dialysis\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e75 (2.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eSystemic autoimmune diseases\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e139 (5.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eInflammatory rheumatic disease\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e159 (6.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMS/NMOSD\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e363 (14.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eHypogammaglobulinemia\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e36 (1.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eDiabetic\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e427 (16.6)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eObese non-diabetic\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e748 (29.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eHIV\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e856 (33.3)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNumber of doses in the primary vaccine course\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e2\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e2378 (92.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123 (100.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e3\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e192 (7.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eType of vaccine\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2564\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1120\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eBNT162b2\u0026thinsp;+\u0026thinsp;BNT162b2\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e2098 (81.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e945 (84.4)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eBNT162b2\u0026thinsp;+\u0026thinsp;BNT162b2\u0026thinsp;+\u0026thinsp;BNT162b2\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e165 (6.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003emRNA-1273\u0026thinsp;+\u0026thinsp;mRNA-1273\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e226 (8.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e99 (8.8)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eAZD1222\u0026thinsp;+\u0026thinsp;AZD1222\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e28 (1.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e45 (4.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eOthers\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e47 (1.8)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e31 (2.8)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eCalendar period of last dose injection\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eApril 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e134 (5.2)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e25 (2.2)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eMay 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e959 (37.3)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e129 (11.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eJune 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e885 (34.4)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e425 (37.8)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eJuly 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e361 (14.0)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e376 (33.5)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eAugust 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e130 (5.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e117 (10.4)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eSeptember 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e63 (2.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e38 (3.4)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eAfter September 2021\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e38 (1.5)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e13 (1.2)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eMonoclonal antibodies use\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e19 (0.7)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eOther morbidities\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e2570\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e0\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e2079 (80.9)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e1123 (100.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e1\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e462 (18.0)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003e2\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e29 (1.1)\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e0 (0.0)\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eControl group: participants not from specific population of interest\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003cbr/\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 \u003cdiv class=\"SimplePara\"\u003eArea under receiving operating characteristic (AUROC) of the antibody value for the prediction of SARS-CoV-2 infection at five months after baseline in participants from the ANRS0001S COV-POPART cohort\u003c/div\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eSpecific populations\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eControl group\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003eAntibodies\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003eUnivariable\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003eMultivariable*\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003eUnivariable\u003c/div\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003eMultivariable**\u003c/div\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAnti-Spike IgG (BAU/mL)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e73.2\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e74.5\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e78.3\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e82.0\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eAnti-RBD IgG (IU/mL)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e70.4\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e74.9\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e77.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.2\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eNeutralizing antibodies (fold dilution)\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e68.5\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e72.4\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e78.8\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.4\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003eModel without antibody\u003c/span\u003e\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cdiv class=\"SimplePara\"\u003e67.0\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cdiv class=\"SimplePara\"\u003e-\u003c/div\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cdiv class=\"SimplePara\"\u003e81.2\u003c/div\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAUROC are corrected for optimism using 1000 bootstrap samples\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Cox proportional hazards models adjusted on age, sex, BMI, number of doses and number of comorbidities and stratified by month of the last received injection during the primary vaccine course and the specific population\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e** Cox proportional hazards models adjusted on age, sex and BMI\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eControl group: participants not from specific populations\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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":"[email protected]","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":"Specific populations, SARS-CoV-2-vaccine, prediction","lastPublishedDoi":"10.21203/rs.3.rs-4510677/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4510677/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe assessed the prognostic value of serological humoral markers measured one month after the last dose of the primary COVID-19 vaccine course for predicting the risk of severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 infection over the following six months in specific populations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eANRS0001SCOV-POPART (NCT04824651) is a French nationwide multicenter prospective observational cohort study assessing the immune response to Covid-19 vaccines routinely administered to 11 subgroups of patients with chronic disease and a control group. Participants from the ANRS0001S COV-POPART were included if they received at least two doses of Covid-19 vaccine for the primary vaccine course, had measurements of anti-Spike, anti-receptor binding domain (RBD) IgG-specific or neutralizing antibodies one month after the end of the primary vaccine course, without being infected by SARS-CoV-2 before the measurement. SARS-CoV-2 infections defined by a positive PCR/antigenic test or seroconversion to detectable anti nucleocapsid antibodies were evaluated until the first COVID-19 booster injection. Cox proportional hazards models taking into account interval-censored data were implemented to estimate the association between each antibody level and the risk of SARS-CoV-2 infection. Predictive performances were evaluated by the area under the receiving operating characteristic curve (AUROC).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003e2,570 adults with a chronic disease and 1,123 without a condition of interest were included. The cumulative probabilities of SARS-CoV-2 infections at five months were 6.0% 95% confidence interval: [5.0; 7.9] and 10.1% [8.3; 11.9], respectively. Higher levels of anti-Spike IgG antibody were associated with a lower risk of SARS-CoV-2 infections in participants without a condition of interest, but not in the specific populations. Among the specific populations, AUROC were 74.5%, 74.9%, and 72.4% for anti-Spike IgG, anti-RBD IgG, and neutralizing antibodies, respectively. AUROC were superior in participants without a condition of interest, 82.0%, 81.2%, and 81.4% for anti-Spike IgG, anti-RBD IgG, and neutralizing antibodies, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eVaccine-induced antibody response after the primary course of Covid-19 infection only moderately discriminated between participants developing a SARS-CoV-2 infection during the Omicron wave.\u003c/p\u003e","manuscriptTitle":"Association between humoral serological markers levels and risk of SARS-CoV-2 infection after the primary COVID-19 vaccine course among ANRS0001S COV- POPART cohort participants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-25 20:02:22","doi":"10.21203/rs.3.rs-4510677/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-06T08:07:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-06T05:22:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-06T05:21:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2024-05-31T18:33:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"94d885df-dbd1-4929-bd9c-9d817ac20681","owner":[],"postedDate":"June 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-30T16:08:35+00:00","versionOfRecord":{"articleIdentity":"rs-4510677","link":"https://doi.org/10.1186/s12879-024-09861-5","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2024-09-27 15:58:17","publishedOnDateReadable":"September 27th, 2024"},"versionCreatedAt":"2024-06-25 20:02:22","video":"","vorDoi":"10.1186/s12879-024-09861-5","vorDoiUrl":"https://doi.org/10.1186/s12879-024-09861-5","workflowStages":[]},"version":"v1","identity":"rs-4510677","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4510677","identity":"rs-4510677","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}