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Glemain B, de Lamballerie X, Zins M, Severi G, Touvier M, Deleuze JF, Lapidus N, Carrat F. Estimating SARS-CoV-2 infection probabilities with serological data and a Bayesian mixture model. Sci Rep 2024; 14:9503. [PMID: 38664455 PMCID: PMC11045781 DOI: 10.1038/s41598-024-60060-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 04/18/2024] [Indexed: 04/28/2024] Open
Abstract
The individual results of SARS-CoV-2 serological tests measured after the first pandemic wave of 2020 cannot be directly interpreted as a probability of having been infected. Plus, these results are usually returned as a binary or ternary variable, relying on predefined cut-offs. We propose a Bayesian mixture model to estimate individual infection probabilities, based on 81,797 continuous anti-spike IgG tests from Euroimmun collected in France after the first wave. This approach used serological results as a continuous variable, and was therefore not based on diagnostic cut-offs. Cumulative incidence, which is necessary to compute infection probabilities, was estimated according to age and administrative region. In France, we found that a "negative" or a "positive" test, as classified by the manufacturer, could correspond to a probability of infection as high as 61.8% or as low as 67.7%, respectively. "Indeterminate" tests encompassed probabilities of infection ranging from 10.8 to 96.6%. Our model estimated tailored individual probabilities of SARS-CoV-2 infection based on age, region, and serological result. It can be applied in other contexts, if estimates of cumulative incidence are available.
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Affiliation(s)
- Benjamin Glemain
- Sorbonne Université, Inserm, Institut Pierre-Louis d'épidémiologie et de santé publique, Paris, France.
- Département de santé publique, Hôpital Saint-Antoine, AP-HP. Sorbonne Université, Paris, France.
| | - Xavier de Lamballerie
- Unité des Virus Émergents, UVE, IRD 190, INSERM 1207, IHU Méditerranée Infection, Aix Marseille Univ, Marseille, France
| | - Marie Zins
- Paris University, Paris, France
- Université Paris-Saclay, Université de Paris, UVSQ, Inserm UMS 11, Villejuif, France
| | - Gianluca Severi
- CESP UMR1018, Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Villejuif, France
- Department of Statistics, Computer Science and Applications, University of Florence, Florence, Italy
| | - Mathilde Touvier
- Sorbonne Paris Nord University, Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center, University of Paris (CRESS), Bobigny, France
| | - Jean-François Deleuze
- Fondation Jean Dausset-CEPH (Centre d'Etude du Polymorphisme Humain), CEPH-Biobank, Paris, France
| | - Nathanaël Lapidus
- Sorbonne Université, Inserm, Institut Pierre-Louis d'épidémiologie et de santé publique, Paris, France
- Département de santé publique, Hôpital Saint-Antoine, AP-HP. Sorbonne Université, Paris, France
| | - Fabrice Carrat
- Sorbonne Université, Inserm, Institut Pierre-Louis d'épidémiologie et de santé publique, Paris, France
- Département de santé publique, Hôpital Saint-Antoine, AP-HP. Sorbonne Université, Paris, France
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Deschasaux-Tanguy M, Szabo de Edelenyi F, Druesne-Pecollo N, Esseddik Y, Allègre J, Srour B, Galan P, Hercberg S, Severi G, Zins M, Wiernik E, de Lamballerie X, Carrat F, Touvier M. ABO blood types and SARS-CoV-2 infection assessed using seroprevalence data in a large population-based sample: the SAPRIS-SERO multi-cohort study. Sci Rep 2023; 13:4775. [PMID: 36959255 PMCID: PMC10034870 DOI: 10.1038/s41598-023-30714-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/28/2023] [Indexed: 03/25/2023] Open
Abstract
ABO blood type has been reported as a potential factor influencing SARS-CoV-2 infection, but so far mostly in studies that involved small samples, selected population and/or used PCR test results. In contrast our study aimed to assess the association between ABO blood types and SARS-CoV-2 infection using seroprevalence data (independent of whether or not individuals had symptoms or sought for testing) in a large population-based sample. Our study included 67,340 French participants to the SAPRIS-SERO multi-cohort project. Anti-SARS-CoV-2 antibodies were detected using ELISA (targeting the proteins spike (S) and nucleocapsid (NP)) and seroneutralisation (SN) tests on dried blood spots collected in May-November 2020. Non-O individuals (and especially types A and AB) were more likely to bear anti SARS-CoV-2 antibodies (ELISA-S, 2964 positive cases: ORnon-Ovs.O = 1.09[1.01-1.17], ORAvs.O = 1.08[1.00-1.17]; ELISA-S/ELISA-NP/SN, 678 triple positive cases: ORnon-Ovs.O = 1.19 [1.02-1.39], ORAvs.O = 1.19[1.01-1.41], ORABvs.O = 1.43[1.01-2.03]). Hence, our results provided additional insights into the dynamic of SARS-CoV-2 infection, highlighting a higher susceptibility of infection for individuals of blood types A and AB and a lesser risk for blood type O.
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Affiliation(s)
- Mélanie Deschasaux-Tanguy
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France.
| | - Fabien Szabo de Edelenyi
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Nathalie Druesne-Pecollo
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Younes Esseddik
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Julien Allègre
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Bernard Srour
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Pilar Galan
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Serge Hercberg
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
| | - Gianluca Severi
- UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP UMR1018, Paris-Saclay University, Villejuif, France
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy
| | - Marie Zins
- Population-based Cohorts Unit, INSERM, UMS 011, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris Cité, Paris, France
| | - Emmanuel Wiernik
- Population-based Cohorts Unit, INSERM, UMS 011, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris Cité, Paris, France
| | - Xavier de Lamballerie
- Unité des Virus Emergents (UVE), IRD 190, INSERM 1207, Aix Marseille Univ, Marseille, France
| | - Fabrice Carrat
- Inserm, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, Sorbonne Université, Paris, France
- Département de Santé Publique, APHP, Sorbonne Université, Paris, France
| | - Mathilde Touvier
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center - Université Paris Cité (CRESS), Sorbonne Paris Nord University, Bobigny, France
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3
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Axfors C, Pezzullo AM, Contopoulos-Ioannidis DG, Apostolatos A, Ioannidis JPA. Differential COVID-19 infection rates in children, adults, and elderly: Systematic review and meta-analysis of 38 pre-vaccination national seroprevalence studies. J Glob Health 2023; 13:06004. [PMID: 36655924 PMCID: PMC9850866 DOI: 10.7189/jogh.13.06004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Background Debate exists about whether extra protection of elderly and other vulnerable individuals is feasible in COVID-19. We aimed to assess the relative infection rates in the elderly vs the non-elderly and, secondarily, in children vs adults. Methods We performed a systematic review and meta-analysis of seroprevalence studies conducted in the pre-vaccination era. We identified representative national studies without high risk of bias through SeroTracker and PubMed searches (last updated May 17, 2022). We noted seroprevalence estimates for children, non-elderly adults, and elderly adults, using cut-offs of 20 and 60 years (or as close to these ages, if they were unavailable) and compared them between different age groups. Results We included 38 national seroprevalence studies from 36 different countries comprising 826 963 participants. Twenty-six of these studies also included pediatric populations and twenty-five were from high-income countries. The median ratio of seroprevalence in elderly vs non-elderly adults (or non-elderly in general, if pediatric and adult population data were not offered separately) was 0.90-0.95 in different analyses, with large variability across studies. In five studies (all in high-income countries), we observed significant protection of the elderly with a ratio of <0.40, with a median of 0.83 in high-income countries and 1.02 elsewhere. The median ratio of seroprevalence in children vs adults was 0.89 and only one study showed a significant ratio of <0.40. The main limitation of our study is the inaccuracies and biases in seroprevalence studies. Conclusions Precision shielding of elderly community-dwelling populations before the availability of vaccines was indicated in some high-income countries, but most countries failed to achieve any substantial focused protection. Registration Open Science Framework (available at: https://osf.io/xvupr).
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Affiliation(s)
- Cathrine Axfors
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Department for Women’s and Children’s Health, Uppsala University, Uppsala, Sweden
| | - Angelo Maria Pezzullo
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Despina G Contopoulos-Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Division of Infectious Diseases, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
| | - Alexandre Apostolatos
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - John PA Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, Stanford University, Stanford, California, USA
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4
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Pezzullo AM, Axfors C, Contopoulos-Ioannidis DG, Apostolatos A, Ioannidis JPA. Age-stratified infection fatality rate of COVID-19 in the non-elderly population. ENVIRONMENTAL RESEARCH 2023; 216:114655. [PMID: 36341800 PMCID: PMC9613797 DOI: 10.1016/j.envres.2022.114655] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 10/21/2022] [Accepted: 10/22/2022] [Indexed: 05/02/2023]
Abstract
The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013-0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036-0.119%) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.002% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.123% at 50-59 years, and 0.506% at 60-69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.
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Affiliation(s)
- Angelo Maria Pezzullo
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Sezione di Igiene, Dipartimento di Scienze della Vita e Sanità Pubblica, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Cathrine Axfors
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
| | - Despina G Contopoulos-Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Division of Infectious Diseases, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexandre Apostolatos
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - John P A Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, Stanford University, Stanford, CA, USA.
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5
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Fadel M, Gilbert F, Legeay C, Dubée V, Esquirol Y, Verdun-Esquer C, Dinh A, Sembajwe G, Goldberg M, Roquelaure Y, Leclerc A, Wiernik E, Zins M, Descatha A. Association between COVID-19 infection and work exposure assessed by the Mat-O-Covid job exposure matrix in the CONSTANCES cohort. Occup Environ Med 2022; 79:oemed-2022-108436. [PMID: 36126974 PMCID: PMC9606493 DOI: 10.1136/oemed-2022-108436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 08/01/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVES The COVID-19 pandemic has brought to light a new occupational health threat. We aimed to evaluate the association between COVID-19 infection and work exposure to SARS-CoV-2 assessed by a job-exposure matrix (JEM), in a large population cohort. We also estimated the population-attributable fraction among exposed subjects. METHODS We used the SAPRIS-SERO sample of the CONSTANCES cohort, limited to subjects actively working, and with a job code available and a questionnaire on extra work activities. The following outcomes were assessed: COVID-19 diagnosis was made by a physician; a seropositivity to the ELISA-S test ('serology strict') and ELISA-S test intermediate with positive ELISA-NP or a positive neutralising antibodies SN ('serology large'). Job exposure was assessed using Mat-O-Covid, an expert-based JEM with an Index used as a continuous variable and a threshold at 13/1000. RESULTS The sample included 18 999 subjects with 389 different jobs, 47.7% were men with a mean age of 46.2 years (±9.2 years). The Mat-O-Covid index taken as a continuous variable or with a threshold greater than 13/1000 was associated with all the outcomes in bivariable and multivariable logistic models. ORs were between 1.30 and 1.58, and proportion of COVID-19 attributable to work among exposed participants was between 20% and 40%. DISCUSSION Using the Mat-O-Covid JEM applied to a large population, we found a significant association between work exposure to SARS-CoV-2 and COVID-19 infection, though the estimation of attributable fraction among exposed people remained low to moderate. Further studies during other exposed periods and with other methods are necessary.
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Affiliation(s)
- Marc Fadel
- Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Ester Unit, SFR ICAT, CAPTV CDC, Angers, France
| | - Fabien Gilbert
- Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Ester Unit, SFR ICAT, CAPTV CDC, Angers, France
| | - Clément Legeay
- Infection Control and Prevention Unit, CHU Angers, Angers, France
| | - Vincent Dubée
- Infectious and Tropical Diseases Department, University Hospital CHU Angers, Angers, France
- Immunology and New Concepts in ImmunoTherapy, INCIT, UMR 1302/EMR6001, Univ Angers, Nantes Université, INSERM, CNRS, Nantes, France
| | - Yolande Esquirol
- Occupational and Environmental Health Department, CHU, CERPOP UMR 1295, Université Paul Sabatier Toulouse 3, Inserm, Toulouse, France
| | - Catherine Verdun-Esquer
- Service Santé Travail Environnement, INSERM U1219, EPICENE, CHU de Bordeaux, Univ Bordeaux, Bordeaux, France
| | - Aurelien Dinh
- Infectious Disease Unit, Raymond-Poincaré University Hospital, AP-HP (Paris Hospital), Paris Saclay University, Paris, France
| | - Grace Sembajwe
- Department of Occupational Medicine, Epidemiology and Prevention, Donald and Barbara Zucker School of Medicine, Hofstra/ Northwell, Great Neck, New York, USA
| | - Marcel Goldberg
- Unité "Cohortes en Population" UMS 011, Inserm/Université de Paris/Université Paris Saclay/UVSQ, Villejuif, France
| | - Yves Roquelaure
- Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Ester Unit, SFR ICAT, CAPTV CDC, Angers, France
| | - Annette Leclerc
- Unité "Cohortes en Population" UMS 011, Inserm/Université de Paris/Université Paris Saclay/UVSQ, Villejuif, France
| | - Emmanuel Wiernik
- Unité "Cohortes en Population" UMS 011, Inserm/Université de Paris/Université Paris Saclay/UVSQ, Villejuif, France
| | - Marie Zins
- Unité "Cohortes en Population" UMS 011, Inserm/Université de Paris/Université Paris Saclay/UVSQ, Villejuif, France
| | - Alexis Descatha
- Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Ester Unit, SFR ICAT, CAPTV CDC, Angers, France
- Department of Occupational Medicine, Epidemiology and Prevention, Donald and Barbara Zucker School of Medicine, Hofstra/ Northwell, Great Neck, New York, USA
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6
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Ding J, Liu C, Wang Z, Guo H, Zhang K, Ma L, Wang B, Zhao H, Song M, Guan X. Characteristics and Prognosis of Antibody Non-responders With Coronavirus Disease 2019. Front Med (Lausanne) 2022; 9:813820. [PMID: 35795627 PMCID: PMC9251059 DOI: 10.3389/fmed.2022.813820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 05/23/2022] [Indexed: 01/08/2023] Open
Abstract
Background Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been spreading globally. Information regarding the characteristics and prognosis of antibody non-responders to COVID-19 is limited. Methods In this retrospective, single-center study, we included all patients with confirmed COVID-19 using real-time reverse transcriptase-polymerase chain reaction (RT-PCR) admitted to the Fire God Mountain hospital from February 3, 2020, to April 14, 2020. A total of 1,921 patients were divided into the antibody-negative (n = 94) and antibody-positive (n = 1,827) groups, and 1:1 propensity score matching was used to match the two groups. Results In the antibody-negative group, 40 patients (42.6%) were men, and 49 (52.1%) were older than 65 years. Cough was the most common symptom in the antibody negative group. White blood cell counts, neutrophils, C-reactive protein, procalcitonin, interleukin-6, lactate dehydrogenase, creatine kinase, creatine kinase isoenzyme, urea nitrogen, and creatinine were significantly higher in the antibody-negative patients than in the antibody-positive group (P < 0.005). The number of days of nucleic acid-negative conversion in the antibody-negative group was shorter than that in the antibody-positive group (P < 0.001). The hospitalization time of the antibody-negative patients was shorter than that of the antibody-positive patients (P < 0.001). Conclusion Some COVID-19 patients without specific antibodies had mild symptoms; however, the inflammatory reaction caused by innate clinical immunity was more intense than those associated with antibodies. Non-specific immune responses played an essential role in virus clearance. There was no direct correlation between excessive inflammatory response and adverse outcomes in patients. The risk of reinfection and vaccination strategies for antibody-negative patients need to be further explored.
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Affiliation(s)
- Junyu Ding
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Changxin Liu
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Zhao Wang
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Hua Guo
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Kan Zhang
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Lin Ma
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Bo Wang
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Huijun Zhao
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Manya Song
- Medical School of Chinese PLA, Beijing, China
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Xizhou Guan
- Department of Pulmonary and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army General Hospital, Beijing, China
- *Correspondence: Xizhou Guan
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7
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Carrat F, Villarroel PMS, Lapidus N, Fourié T, Blanché H, Dorival C, Nicol J, Deleuze JF, Robineau O, Touvier M, Severi G, Zins M, de Lamballerie X. Heterogeneous SARS-CoV-2 humoral response after COVID-19 vaccination and/or infection in the general population. Sci Rep 2022; 12:8622. [PMID: 35597776 PMCID: PMC9123863 DOI: 10.1038/s41598-022-11787-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 04/28/2022] [Indexed: 01/07/2023] Open
Abstract
Assessment of the intensity, dynamics and determinants of the antibody response after SARS-CoV-2 infection or vaccination in the general population is critical to guide vaccination policies. This study characterized the anti-spike IgG titers in 13,971 participants included in a French multicohort population-based serological survey on COVID-19 between April and October 2020 and followed-up with serological testing between May and October 2021. Eight follow-up profiles were defined depending on SARS-CoV-2 infection (0, 1 or 2) and COVID-19 vaccination (0, 1, 2 or 3). The anti-spike titer was lower in adults with no vaccination even in case of infection or reinfection, while it was higher in adults with infection followed by vaccination. The anti-spike titer was negatively correlated with age in vaccinated but uninfected adults, whereas it was positively correlated with age in unvaccinated but infected adults. In adults with 2 vaccine injections and no infection, the vaccine protocol, age, gender, and time since the last vaccine injection were independently associated with the anti-spike titer. The decrease in anti-spike titer was much more rapid in vaccinated than in infected subjects. These results highlight the strong heterogeneity of the antibody response against SARS-CoV-2 in the general population depending on previous infection and vaccination.
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Affiliation(s)
- Fabrice Carrat
- Institut Pierre-Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Inserm, Département de santé publique, Hôpital Saint-Antoine, APHP, 27 rue Chaligny, 75571, Paris Cedex 12, France.
| | - Paola Mariela Saba Villarroel
- Unité des Virus Émergents, UVE, IRD 190, INSERM 1207, Aix Marseille Univ, IHU Méditerranée Infection, Marseille, France
| | - Nathanael Lapidus
- Institut Pierre-Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Inserm, Département de santé publique, Hôpital Saint-Antoine, APHP, 27 rue Chaligny, 75571, Paris Cedex 12, France
| | - Toscane Fourié
- Unité des Virus Émergents, UVE, IRD 190, INSERM 1207, Aix Marseille Univ, IHU Méditerranée Infection, Marseille, France
| | - Hélène Blanché
- Fondation Jean Dausset-CEPH (Centre d'Etude du Polymorphisme Humain), CEPH-Biobank, Paris, France
| | - Céline Dorival
- Institut Pierre-Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Inserm, Paris, France
| | - Jérôme Nicol
- Institut Pierre-Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Inserm, Paris, France
| | - Jean-François Deleuze
- Fondation Jean Dausset-CEPH (Centre d'Etude du Polymorphisme Humain), CEPH-Biobank, Paris, France
| | - Olivier Robineau
- Institut Pierre-Louis d'Épidémiologie et de Santé Publique, Sorbonne Université, Inserm, Paris, France
| | - Mathilde Touvier
- Inserm U1153, Inrae U1125, Cnam, Nutritional Epidemiology Research Team (EREN), Sorbonne Paris Nord University, Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France
| | - Gianluca Severi
- CESP UMR1018, UVSQ, Inserm, Université Paris-Saclay, Gustave Roussy, Villejuif, France
- Department of Statistics, Computer Science and Applications, University of Florence, Florence, Italy
| | - Marie Zins
- Paris University, Paris, France
- UVSQ, Inserm UMS 11, Université Paris-Saclay, Université de Paris, Villejuif, France
| | - Xavier de Lamballerie
- Unité des Virus Émergents, UVE, IRD 190, INSERM 1207, Aix Marseille Univ, IHU Méditerranée Infection, Marseille, France
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Molino D, Durier C, Radenne A, Desaint C, Ropers J, Courcier S, Vieillard LV, Rekacewicz C, Parfait B, Appay V, Batteux F, Barillot E, Cogné M, Combadière B, Eberhardt CS, Gorochov G, Hupé P, Ninove L, Paul S, Pellegrin I, van der Werf S, Lefebvre M, Botelho-Nevers E, Ortega-Perez I, Jaspard M, Sow S, Lelièvre JD, de Lamballerie X, Kieny MP, Tartour E, Launay O. A comparison of Sars-Cov-2 vaccine platforms: the CoviCompare project. Nat Med 2022; 28:882-884. [PMID: 35513532 DOI: 10.1038/s41591-022-01785-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Diana Molino
- Université Paris Cité, National Institute for Health and Medical Research (INSERM) CIC 1417 Cochin Pasteur, Innovative Clinical Research Network in Vaccinology (I-REIVAC), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Cochin, Paris, France
| | | | - Anne Radenne
- AP-HP, Hôpitaux Universitaires Pitié Salpêtrière-Charles Foix, Unité de Recherche Clinique des Hôpitaux Universitaires Pitié Salpêtrière, Paris, France
| | | | - Jacques Ropers
- AP-HP, Hôpitaux Universitaires Pitié Salpêtrière-Charles Foix, Unité de Recherche Clinique des Hôpitaux Universitaires Pitié Salpêtrière, Paris, France
| | - Soizic Courcier
- Université Paris Cité, National Institute for Health and Medical Research (INSERM) CIC 1417 Cochin Pasteur, Innovative Clinical Research Network in Vaccinology (I-REIVAC), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Cochin, Paris, France
| | - Louis Victorien Vieillard
- Université Paris Cité, National Institute for Health and Medical Research (INSERM) CIC 1417 Cochin Pasteur, Innovative Clinical Research Network in Vaccinology (I-REIVAC), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Cochin, Paris, France
| | - Claire Rekacewicz
- Université Paris Cité, National Institute for Health and Medical Research (INSERM) CIC 1417 Cochin Pasteur, Innovative Clinical Research Network in Vaccinology (I-REIVAC), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Cochin, Paris, France
| | - Beatrice Parfait
- AP-HP, Hôpital Cochin, Fédération des Centres de Ressources Biologiques-Plateforme de Ressources Biologiques Centre de Ressources Biologique Cochin, Paris, France
| | - Victor Appay
- Centre Hospitalier Universitaire (CHU) Bordeaux, Laboratory of Immunology and Immunogenetics, Université de Bordeaux, Centre National de la Recherche Scientifique (CNRS) Unité Mixte de Recherche (UMR) 5164, INSERM ERL 1303, ImmunoConcEpT, Bordeaux, France
| | - Frédéric Batteux
- AP-HP, Hôpital Cochin, Service d'Immunologie Biologique et Plateforme d'Immunomonitoring Vaccinal, Paris, France
| | - Emmanuel Barillot
- Institut Curie, PSL Research University-INSERM U900-MINES ParisTech, PSL, Paris, France
| | - Michel Cogné
- Laboratory of Immunology-Research Unit INSERM U 1236, B cell Ig Remodelling Singularities (BIGRES), Faculty of Medicine, French Blood Center (EFS Bretagne) & University Hospital, Rennes, France
| | - Béhazine Combadière
- Centre d'Immunologie et des Maladies Infectieuses-Paris (Cimi-Paris), INSERM U1135, Sorbonne Université, Paris, France
| | - Christiane S Eberhardt
- University of Geneva, Faculty of Medicine, Division of General Pediatrics, Department of Woman, Child and Adolescent Medicine and Center for Vaccinology, Geneva, Switzerland
| | - Guy Gorochov
- Sorbonne Université, INSERM, Centre d'Immunologie et des Maladies Infectieuses (CIMI-Paris), Département d'Immunologie, AP-HP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Philippe Hupé
- Institut Curie, PSL Research University-INSERM U900-MINES ParisTech, PSL, Paris, France.,CNRS, UMR 144, Paris, France
| | - Laetitia Ninove
- Aix Marseille Université, Research Institute for Sustainable Development (IRD) 190, INSERM 1207, IHU Méditerranée Infection, Unité des Virus Émergents, Marseille, France
| | - Stéphane Paul
- INSERM, U1111, CNRS, UMR 530, Immunology and Immunomonitoring Laboratory, iBiothera, CIRI-GIMAP, UCBL 1, UJM, CIC 1408, Saint-Etienne, France
| | - Isabelle Pellegrin
- Centre Hospitalier Universitaire (CHU) Bordeaux, Laboratory of Immunology and Immunogenetics, Université de Bordeaux, Centre National de la Recherche Scientifique (CNRS) Unité Mixte de Recherche (UMR) 5164, INSERM ERL 1303, ImmunoConcEpT, Bordeaux, France
| | - Sylvie van der Werf
- Université Paris Cité, Institut Pasteur, Unité Génétique Moléculaire Virus à ARN UMR 3569 CNRS, Paris, France
| | - Maeva Lefebvre
- CHU de Nantes, INSERM CIC1413, Maladies Infectieuses et Tropicales, Centre de Prévention des Maladies Infectieuses et Transmissibles, Nantes, France
| | - Elisabeth Botelho-Nevers
- INSERM CIC 1408, Axe Vaccinologie, CHU de Saint-Etienne, Service d'Infectiologie, Saint-Etienne, France
| | | | - Marie Jaspard
- The Alliance for International Medical Action (ALIMA), Paris, France.,University of Bordeaux, INSERM, IRD, Bordeaux Population Health Center, UMR 1219, Bordeaux, France
| | - Samba Sow
- The Center for Vaccine Development, Bamako, Mali
| | | | - Xavier de Lamballerie
- Aix Marseille Université, Research Institute for Sustainable Development (IRD) 190, INSERM 1207, IHU Méditerranée Infection, Unité des Virus Émergents, Marseille, France
| | | | - Eric Tartour
- AP-HP, Hôpital Européen Georges Pompidou, INSERM U970, PARCC, Paris, France
| | - Odile Launay
- Université Paris Cité, National Institute for Health and Medical Research (INSERM) CIC 1417 Cochin Pasteur, Innovative Clinical Research Network in Vaccinology (I-REIVAC), Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital Cochin, Paris, France.
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