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Ayoub HH, Tomy M, Chemaitelly H, Altarawneh HN, Coyle P, Tang P, Hasan MR, Al Kanaani Z, Al Kuwari E, Butt AA, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Nasrallah GK, Benslimane FM, Al Khatib HA, Yassine HM, Al Kuwari MG, Al Romaihi HE, Abdul-Rahim HF, Al-Thani MH, Al Khal A, Bertollini R, Abu-Raddad LJ. Estimating protection afforded by prior infection in preventing reinfection: applying the test-negative study design. Am J Epidemiol 2024; 193:883-897. [PMID: 38061757 DOI: 10.1093/aje/kwad239] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 11/20/2023] [Accepted: 12/04/2023] [Indexed: 06/04/2024] Open
Abstract
The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection ($P{E}_S$) by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case-control study design to derive $P{E}_S$. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for $P{E}_S$ and true value of $P{E}_S$ was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of $P{E}_S$ and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated $P{E}_S$, but the underestimate was considerable only when > 50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated $P{E}_S$. The test-negative design was applied to national-level testing data in Qatar to estimate $P{E}_S$ for SARS-CoV-2. $P{E}_S$ against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI, 93.6-98.6) and 85.5% (95% CI, 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.
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Affiliation(s)
- Houssein H Ayoub
- Mathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Milan Tomy
- Mathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, Doha, Qatar
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
| | - Heba N Altarawneh
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast BT9 7BL, United Kingdom
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | | | | | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
- Hamad Medical Corporation, Doha, Qatar
| | | | | | | | | | - Gheyath K Nasrallah
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Fatiha M Benslimane
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Hebah A Al Khatib
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Hadi M Yassine
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | | | | | - Hanan F Abdul-Rahim
- Department of Public Health, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | | | | | | | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
- Department of Public Health, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
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2
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Acuña-Castillo C, Vidal M, Vallejos-Vidal E, Luraschi R, Barrera-Avalos C, Inostroza-Molina A, Molina-Cabrera S, Valdes D, Schafer C, Maisey K, Imarai M, Vera R, Vargas S, Rojo LE, Leiva-Salcedo E, Escobar A, Reyes-Cerpa S, Gaete A, Palma-Vejares R, Travisany D, Torres C, Reyes-López FE, Sandino AM. A retrospective study suggests 55 days of persistence of SARS-CoV-2 during the first wave of the pandemic in Santiago de Chile. Heliyon 2024; 10:e24419. [PMID: 38601544 PMCID: PMC11004068 DOI: 10.1016/j.heliyon.2024.e24419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 12/12/2023] [Accepted: 01/08/2024] [Indexed: 04/12/2024] Open
Abstract
Background As the COVID-19 pandemic persists, infections continue to surge globally. Presently, the most effective strategies to curb the disease and prevent outbreaks involve fostering immunity, promptly identifying positive cases, and ensuring their timely isolation. Notably, there are instances where the SARS-CoV-2 virus remains infectious even after patients have completed their quarantine. Objective Understanding viral persistence post-quarantine is crucial as it could account for localized infection outbreaks. Therefore, studying and documenting such instances is vital for shaping future public health policies. Design This study delves into a unique case of SARS-CoV-2 persistence in a 60-year-old female healthcare worker with a medical history of hypertension and hypothyroidism. The research spans 55 days, marking the duration between her initial and subsequent diagnosis during Chile's first COVID-19 wave, with the analysis conducted using RT-qPCR. Results Genomic sequencing-based phylogenetic analysis revealed that the SARS-CoV-2 detected in both Nasopharyngeal swab samples (NPSs) was consistent with the 20B clade of the Nextstrain classification, even after a 55-day interval. Conclusion This research underscores the need for heightened vigilance concerning cases of viral persistence. Such instances, albeit rare, might be pivotal in understanding sporadic infection outbreaks that occur post-quarantine.
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Affiliation(s)
- Claudio Acuña-Castillo
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Departamento de Biología, Universidad de Santiago de Chile, Santiago, Chile
| | - Mabel Vidal
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Concepción, Chile
| | - Eva Vallejos-Vidal
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Centro de Nanociencia y Nanotecnología CEDENNA, Universidad de Santiago de Chile, Chile
- Núcleo de Investigaciones Aplicadas en Ciencias Veterinarias y Agronómicas, Facultad de Medicina Veterinaria y Agronomía, Universidad De Las Américas, La Florida, Santiago, Chile
| | - Roberto Luraschi
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
| | | | | | | | - Daniel Valdes
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Departamento de Biología, Universidad de Santiago de Chile, Santiago, Chile
| | - Carolina Schafer
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
| | - Kevin Maisey
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
| | - Mónica Imarai
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Departamento de Biología, Universidad de Santiago de Chile, Santiago, Chile
| | - Rodrigo Vera
- Hospital de Urgencia Asistencia Pública (HUAP), Santiago, Chile
| | - Sergio Vargas
- Hospital de Urgencia Asistencia Pública (HUAP), Santiago, Chile
| | - Leonel E. Rojo
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Departamento de Biología, Universidad de Santiago de Chile, Santiago, Chile
| | | | - Alejandro Escobar
- Laboratorio Biología Celular y Molecular, Instituto de Investigación en Ciencias Odontológicas, Universidad de Chile, Santiago, Chile
| | - Sebastián Reyes-Cerpa
- Centro de Genómica y Bioinformática, Facultad de Ciencias, Ingeniería y Tecnología, Universidad Mayor, Santiago, Chile
- Escuela de Biotecnología, Facultad de Ciencias, Ingeniería y Tecnología, Universidad Mayor, Santiago, Chile
| | - Alexis Gaete
- Laboratorio de Bioinformática y Expresión Génica, Instituto de Nutrición y Tecnología de Los Alimentos, Universidad de Chile, Santiago, Chile
- Fondap Center for Genome Regulation, Universidad de Chile, Santiago, Chile
| | - Ricardo Palma-Vejares
- Centro de Modelamiento Matemático UMI-CNRS 2807, Universidad de Chile, Santiago, Chile
| | - Dante Travisany
- Fondap Center for Genome Regulation, Universidad de Chile, Santiago, Chile
- Centro de Modelamiento Matemático UMI-CNRS 2807, Universidad de Chile, Santiago, Chile
- Inria Chile Research Center, Santiago, Chile
| | - Claudio Torres
- Department of Neurobiology Drexel University, Philadelphia, United States
| | | | - Ana María Sandino
- Centro de Biotecnología Acuícola, Universidad de Santiago de Chile, Santiago, Chile
- Departamento de Biología, Universidad de Santiago de Chile, Santiago, Chile
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Chemaitelly H, Ayoub HH, Tang P, Yassine HM, Al Thani AA, Hasan MR, Coyle P, Al-Kanaani Z, Al-Kuwari E, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Butt AA, Al-Romaihi HE, Al-Thani MH, Al-Khal A, Bertollini R, Abu-Raddad LJ. Addressing bias in the definition of SARS-CoV-2 reinfection: implications for underestimation. Front Med (Lausanne) 2024; 11:1363045. [PMID: 38529118 PMCID: PMC10961414 DOI: 10.3389/fmed.2024.1363045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 02/22/2024] [Indexed: 03/27/2024] Open
Abstract
Introduction Reinfections are increasingly becoming a feature in the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, accurately defining reinfection poses methodological challenges. Conventionally, reinfection is defined as a positive test occurring at least 90 days after a previous infection diagnosis. Yet, this extended time window may lead to an underestimation of reinfection occurrences. This study investigated the prospect of adopting an alternative, shorter time window for defining reinfection. Methods A longitudinal study was conducted to assess the incidence of reinfections in the total population of Qatar, from February 28, 2020 to November 20, 2023. The assessment considered a range of time windows for defining reinfection, spanning from 1 day to 180 days. Subgroup analyses comparing first versus repeat reinfections and a sensitivity analysis, focusing exclusively on individuals who underwent frequent testing, were performed. Results The relationship between the number of reinfections in the population and the duration of the time window used to define reinfection revealed two distinct dynamical domains. Within the initial 15 days post-infection diagnosis, almost all positive tests for SARS-CoV-2 were attributed to the original infection. However, surpassing the 30-day post-infection threshold, nearly all positive tests were attributed to reinfections. A 40-day time window emerged as a sufficiently conservative definition for reinfection. By setting the time window at 40 days, the estimated number of reinfections in the population increased from 84,565 to 88,384, compared to the 90-day time window. The maximum observed reinfections were 6 and 4 for the 40-day and 90-day time windows, respectively. The 40-day time window was appropriate for defining reinfection, irrespective of whether it was the first, second, third, or fourth occurrence. The sensitivity analysis, confined to high testers exclusively, replicated similar patterns and results. Discussion A 40-day time window is optimal for defining reinfection, providing an informed alternative to the conventional 90-day time window. Reinfections are prevalent, with some individuals experiencing multiple instances since the onset of the pandemic.
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Affiliation(s)
- Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | - Houssein H. Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | - Hadi M. Yassine
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Asmaa A. Al Thani
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Mohammad R. Hasan
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Peter Coyle
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Hamad Medical Corporation, Doha, Qatar
- Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom
| | | | | | | | | | | | | | - Hanan F. Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K. Nasrallah
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | - Adeel A. Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
- Hamad Medical Corporation, Doha, Qatar
- Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | | | | | | | | | - Laith J. Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
- College of Health and Life Sciences, Hamad bin Khalifa University, Doha, Qatar
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4
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Aninagyei E, Ayivor-Djanie R, Gyamfi J, Aboagye ME, Kpeli GS, Ampofo WK, Gyapong JO, Duedu KO. Pre-vaccination seroprevalence of SARS-CoV-2 antibodies in the Volta Region, Ghana. IJID REGIONS 2024; 10:179-182. [PMID: 38328557 PMCID: PMC10847139 DOI: 10.1016/j.ijregi.2024.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 01/15/2024] [Accepted: 01/17/2024] [Indexed: 02/09/2024]
Abstract
Objectives Before administration of the first dose of the AstraZeneca 2019 SARS-CoV-2 vaccine to selected prioritized groups in the Volta regional capital of Ghana, we determined the pre-vaccination status of prospective recipients and established the baseline exposure status 1 year after the first case was reported. Methods After informed consent, blood samples were collected for the detection of SARS-CoV-2 immunoglobulin (Ig) M/IgG antibodies using rapid diagnostic test kits. A total of 409 individuals (mean age 27 years) consented and participated in the study, comprising 70% students and others were health staff and educators who presented themselves for vaccination. Results The overall exposure rate of SARS-CoV-2 was 12.7% (95% confidence interval [CI] 9.6-16.3). The prevalence of SARS-CoV-2 IgM and IgG were 4.2% (95% CI 2.4-6.6) and 5.6% (95% CI 3.6-8.3), respectively. IgM and IgG were detected in 2.9% (95% CI 1.5-5.1) of the respondents. The exposure rates were higher in participants over 40 years old (15.5%). Participants without a history of COVID-19-like symptoms had an exposure rate of 13.0% and those without any chronic diseases was 13.2%. Conclusion Pre-vaccination exposure was relatively low and underscored the need for vaccination i to increase protection in communities and disease outcomes.
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Affiliation(s)
- Enoch Aninagyei
- Department of Biomedical Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana
| | - Reuben Ayivor-Djanie
- Department of Biomedical Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), University of Ghana, Legon, Ghana
| | - Jones Gyamfi
- Department of Medical Laboratory Sciences, School of Allied Health Sciences, University of Health and Allied Sciences, Ho, Ghana
- School of Health & Life Sciences, Teesside University, Middlesbrough, United Kingdom
| | - Marfo Edward Aboagye
- Department of Biomedical Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana
| | - Grace Semabia Kpeli
- Department of Biomedical Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana
| | - William Kwabena Ampofo
- Virology Department, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
| | - John Owusu Gyapong
- Centre for Neglected Tropical Diseases, Institute of Health Research, University of Health and Allied Sciences, Ho, Ghana
| | - Kwabena Obeng Duedu
- Department of Biomedical Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana
- College of Life Sciences, Faculty of Health, Education and Life Sciences, Birmingham City University, City South Campus, Birmingham, United Kingdom
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5
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Rakhshan SA, Zaj M, Ghane FH, Nejad MS. Exploring the potential of learning methods and recurrent dynamic model with vaccination: A comparative case study of COVID-19 in Austria, Brazil, and China. Phys Rev E 2024; 109:014212. [PMID: 38366403 DOI: 10.1103/physreve.109.014212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 12/11/2023] [Indexed: 02/18/2024]
Abstract
In order to effectively manage infectious diseases, it is crucial to understand the interplay between disease dynamics and human conduct. Various factors can impact the control of an epidemic, including social interventions, adherence to health protocols, mask-wearing, and vaccination. This article presents the development of an innovative hybrid model, known as the Combined Dynamic-Learning Model, that integrates classical recurrent dynamic models with four different learning methods. The model is composed of two approaches: The first approach introduces a traditional dynamic model that focuses on analyzing the impact of vaccination on the occurrence of an epidemic, and the second approach employs various learning methods to forecast the potential outcomes of an epidemic. Furthermore, our numerical results offer an interesting comparison between the traditional approach and modern learning techniques. Our classic dynamic model is a compartmental model that aims to analyze and forecast the diffusion of epidemics. The model we propose has a recurrent structure with piecewise constant parameters and includes compartments for susceptible, exposed, vaccinated, infected, and recovered individuals. This model can accurately mirror the dynamics of infectious diseases, which enables us to evaluate the impact of restrictive measures on the spread of diseases. We conduct a comprehensive dynamic analysis of our model. Additionally, we suggest an optimal numerical design to determine the parameters of the system. Also, we use regression tree learning, bidirectional long short-term memory, gated recurrent unit, and a combined deep learning method for training and evaluation of an epidemic. In the final section of our paper, we apply these methods to recently published data on COVID-19 in Austria, Brazil, and China from 26 February 2021 to 4 August 2021, which is when vaccination efforts began. To evaluate the numerical results, we utilized various metrics such as RMSE and R-squared. Our findings suggest that the dynamic model is ideal for long-term analysis, data fitting, and identifying parameters that impact epidemics. However, it is not as effective as the supervised learning method for making long-term forecasts. On the other hand, supervised learning techniques, compared to dynamic models, are more effective for predicting the spread of diseases, but not for analyzing the behavior of epidemics.
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Affiliation(s)
- Seyed Ali Rakhshan
- Department of Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Marzie Zaj
- Department of Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran
| | | | - Mahdi Soltani Nejad
- Department of Railway Engineering, Iran University of Science and Technology, Tehran, Iran
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6
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Holdenrieder S, Dos Santos Ferreira CE, Izopet J, Theel ES, Wieser A. Clinical and laboratory considerations: determining an antibody-based composite correlate of risk for reinfection with SARS-CoV-2 or severe COVID-19. Front Public Health 2023; 11:1290402. [PMID: 38222091 PMCID: PMC10788057 DOI: 10.3389/fpubh.2023.1290402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/30/2023] [Indexed: 01/16/2024] Open
Abstract
Much of the global population now has some level of adaptive immunity to SARS-CoV-2 induced by exposure to the virus (natural infection), vaccination, or a combination of both (hybrid immunity). Key questions that subsequently arise relate to the duration and the level of protection an individual might expect based on their infection and vaccination history. A multi-component composite correlate of risk (CoR) could inform individuals and stakeholders about protection and aid decision making. This perspective evaluates the various elements that need to be accommodated in the development of an antibody-based composite CoR for reinfection with SARS-CoV-2 or development of severe COVID-19, including variation in exposure dose, transmission route, viral genetic variation, patient factors, and vaccination status. We provide an overview of antibody dynamics to aid exploration of the specifics of SARS-CoV-2 antibody testing. We further discuss anti-SARS-CoV-2 immunoassays, sample matrices, testing formats, frequency of sampling and the optimal time point for such sampling. While the development of a composite CoR is challenging, we provide our recommendations for each of these key areas and highlight areas that require further work to be undertaken.
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Affiliation(s)
- Stefan Holdenrieder
- Institute of Laboratory Medicine, German Heart Centre Munich, Technical University Munich, Munich, Germany
| | | | - Jacques Izopet
- Laboratory of Virology, Toulouse University Hospital and INFINITY Toulouse Institute for Infections and Inflammatory Diseases, INSERM UMR 1291 CNRS UMR 5051, University Toulouse III, Toulouse, France
| | - Elitza S. Theel
- Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany
- German Centre for Infection Research (DZIF), Munich, Germany
- Faculty of Medicine, Max Von Pettenkofer Institute, LMU Munich, Munich, Germany
- Immunology, Infection and Pandemic Research, Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Munich, Germany
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7
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Tong MZW, Sng JDJ, Carney M, Cooper L, Brown S, Lineburg KE, Chew KY, Collins N, Ignacio K, Airey M, Burr L, Joyce BA, Jayasinghe D, McMillan CLD, Muller DA, Adhikari A, Gallo LA, Dorey ES, Barrett HL, Gras S, Smith C, Good‐Jacobson K, Short KR. Elevated BMI reduces the humoral response to SARS-CoV-2 infection. Clin Transl Immunology 2023; 12:e1476. [PMID: 38050635 PMCID: PMC10693902 DOI: 10.1002/cti2.1476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 11/05/2023] [Accepted: 11/09/2023] [Indexed: 12/06/2023] Open
Abstract
Objective Class III obesity (body mass index [BMI] ≥ 40 kg m-2) significantly impairs the immune response to SARS-CoV-2 vaccination. However, the effect of an elevated BMI (≥ 25 kg m-2) on humoral immunity to SARS-CoV-2 infection and COVID-19 vaccination remains unclear. Methods We collected blood samples from people who recovered from SARS-CoV-2 infection approximately 3 and 13 months of post-infection (noting that these individuals were not exposed to SARS-CoV-2 or vaccinated in the interim). We also collected blood samples from people approximately 5 months of post-second dose COVID-19 vaccination (the majority of whom did not have a prior SARS-CoV-2 infection). We measured their humoral responses to SARS-CoV-2, grouping individuals based on a BMI greater or less than 25 kg m-2. Results Here, we show that an increased BMI (≥ 25 kg m-2), when accounting for age and sex differences, is associated with reduced antibody responses after SARS-CoV-2 infection. At 3 months of post-infection, an elevated BMI was associated with reduced antibody titres. At 13 months of post-infection, an elevated BMI was associated with reduced antibody avidity and a reduced percentage of spike-positive B cells. In contrast, no significant association was noted between a BMI ≥ 25 kg m-2 and humoral immunity to SARS-CoV-2 at 5 months of post-secondary vaccination. Conclusions Taken together, these data showed that elevated BMI is associated with an impaired humoral immune response to SARS-CoV-2 infection. The impairment of infection-induced immunity in individuals with a BMI ≥ 25 kg m-2 suggests an added impetus for vaccination rather than relying on infection-induced immunity.
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Affiliation(s)
- Marcus ZW Tong
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Julian DJ Sng
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Meagan Carney
- School of Mathematics and PhysicsThe University of QueenslandSt LuciaQLDAustralia
| | - Lucy Cooper
- Department of Biochemistry and Molecular BiologyMonash UniversityClaytonVICAustralia
- Immunity Program, Biomedicine Discovery InstituteMonash UniversityClaytonVICAustralia
| | - Samuel Brown
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Katie E Lineburg
- QIMR Berghofer Centre for Immunotherapy and Vaccine Development and Translational and Human Immunology Laboratory, Infection and Inflammation ProgramQIMR Berghofer Medical Research InstituteHerstonQLDAustralia
| | - Keng Yih Chew
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Neve Collins
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Kirsten Ignacio
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Megan Airey
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Lucy Burr
- QIMR Berghofer Centre for Immunotherapy and Vaccine Development and Translational and Human Immunology Laboratory, Infection and Inflammation ProgramQIMR Berghofer Medical Research InstituteHerstonQLDAustralia
- Department of Respiratory MedicineMater HealthBrisbaneQLDAustralia
| | - Briony A Joyce
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
| | - Dhilshan Jayasinghe
- Department of Biochemistry and Molecular BiologyMonash UniversityClaytonVICAustralia
- Department of Biochemistry and ChemistryLa Trobe Institute for Molecular Science, La Trobe UniversityBundooraVICAustralia
| | - Christopher LD McMillan
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
- Australian Infectious Diseases Research CentreThe University of QueenslandSt LuciaQLDAustralia
| | - David A Muller
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
- Australian Infectious Diseases Research CentreThe University of QueenslandSt LuciaQLDAustralia
| | - Anurag Adhikari
- Department of Biochemistry and ChemistryLa Trobe Institute for Molecular Science, La Trobe UniversityBundooraVICAustralia
| | - Linda A Gallo
- School of HealthUniversity of the Sunshine CoastPetrieQLDAustralia
| | - Emily S Dorey
- Mater ResearchThe University of QueenslandSouth BrisbaneQLDAustralia
| | - Helen L Barrett
- Mater ResearchThe University of QueenslandSouth BrisbaneQLDAustralia
- University of New South Wales MedicineKensingtonNSWAustralia
- Obstetric MedicineRoyal Hospital for WomenRandwickNSWAustralia
| | - Stephanie Gras
- Department of Biochemistry and Molecular BiologyMonash UniversityClaytonVICAustralia
- Department of Biochemistry and ChemistryLa Trobe Institute for Molecular Science, La Trobe UniversityBundooraVICAustralia
| | - Corey Smith
- QIMR Berghofer Centre for Immunotherapy and Vaccine Development and Translational and Human Immunology Laboratory, Infection and Inflammation ProgramQIMR Berghofer Medical Research InstituteHerstonQLDAustralia
| | - Kim Good‐Jacobson
- Department of Biochemistry and Molecular BiologyMonash UniversityClaytonVICAustralia
- Immunity Program, Biomedicine Discovery InstituteMonash UniversityClaytonVICAustralia
| | - Kirsty R Short
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQLDAustralia
- Australian Infectious Diseases Research CentreThe University of QueenslandSt LuciaQLDAustralia
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8
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Zirou C, Gumeni S, Bellos I, Ntanasis-Stathopoulos I, Sklirou AD, Bagratuni T, Korompoki E, Apostolakou F, Papassotiriou I, Trougakos IP, Terpos E. Longitudinal Analysis of Antibody Response Following SARS-CoV-2 Infection Depending on Disease Severity: A Prospective Cohort Study. Viruses 2023; 15:2250. [PMID: 38005927 PMCID: PMC10674840 DOI: 10.3390/v15112250] [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: 09/29/2023] [Revised: 11/06/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
OBJECTIVE Severe coronavirus disease 19 (COVID-19) is characterized by a dysregulated inflammatory response, with humoral immunity playing a central role in the disease course. The objective of this study was to assess the immune response and the effects of vaccination in recovered individuals with variable disease severity up to one year following natural infection. METHODS A prospective cohort study was conducted including patients with laboratory-confirmed COVID-19. Disease severity was classified as mild, moderate, and severe based on clinical presentation and outcomes. Anti-RBD (receptor binding domain) and neutralizing antibodies were evaluated at multiple timepoints during the first year after COVID-19 diagnosis. RESULTS A total of 106 patients were included; of them, 28 were diagnosed with mild, 38 with moderate, and 40 with severe disease. At least one vaccine dose was administered in 58 individuals during the follow-up. Participants with mild disease presented significantly lower anti-RBD and neutralizing antibodies compared to those with moderate and severe disease up to the 3rd and 6th months after the infection, respectively. After adjusting for covariates, in the third month, severe COVID-19 was associated with significantly higher anti-RBD (β: 563.09; 95% confidence intervals (CI): 257.02 to 869.17) and neutralizing (β: 21.47; 95% CI: 12.04 to 30.90) antibodies. Among vaccinated individuals, at the 12th month, a history of moderate disease was associated with significantly higher anti-RBD levels (β: 5615.19; 95% CI: 657.92 to 10,572.46). CONCLUSIONS Severe COVID-19 is associated with higher anti-RBD and neutralizing antibodies up to 6 months after the infection. Vaccination of recovered patients is associated with a remarkable augmentation of antibody titers up to one year after COVID-19 diagnosis, regardless of disease severity.
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Affiliation(s)
- Christina Zirou
- Department of Internal Medicine, Sotiria General and Chest Diseases Hospital of Athens, 11527 Athens, Greece
| | - Sentiljana Gumeni
- Department of Cell Biology and Biophysics, Faculty of Biology, National and Kapodistrian University of Athens, 15771 Athens, Greece
| | - Ioannis Bellos
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Ioannis Ntanasis-Stathopoulos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece
| | - Aimilia D. Sklirou
- Department of Cell Biology and Biophysics, Faculty of Biology, National and Kapodistrian University of Athens, 15771 Athens, Greece
| | - Tina Bagratuni
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece
| | - Eleni Korompoki
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece
| | - Filia Apostolakou
- Department of Clinical Biochemistry, “Aghia Sophia” Children’s Hospital, 11527 Athens, Greece
| | - Ioannis Papassotiriou
- Department of Clinical Biochemistry, “Aghia Sophia” Children’s Hospital, 11527 Athens, Greece
| | - Ioannis P. Trougakos
- Department of Cell Biology and Biophysics, Faculty of Biology, National and Kapodistrian University of Athens, 15771 Athens, Greece
| | - Evangelos Terpos
- Department of Clinical Therapeutics, School of Medicine, National and Kapodistrian University of Athens, 11528 Athens, Greece
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Altarawneh HN, Chemaitelly H, Ayoub HH, Tang P, Hasan MR, Yassine HM, Al-Khatib HA, Al Thani AA, Coyle P, Al-Kanaani Z, Al-Kuwari E, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Butt AA, Al-Romaihi HE, Al-Thani MH, Al-Khal A, Bertollini R, Abu-Raddad LJ. Effects of previous infection, vaccination, and hybrid immunity against symptomatic Alpha, Beta, and Delta SARS-CoV-2 infections: an observational study. EBioMedicine 2023; 95:104734. [PMID: 37515986 PMCID: PMC10404859 DOI: 10.1016/j.ebiom.2023.104734] [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: 04/29/2023] [Revised: 07/02/2023] [Accepted: 07/15/2023] [Indexed: 07/31/2023] Open
Abstract
BACKGROUND Protection against SARS-CoV-2 symptomatic infection and severe COVID-19 of previous infection, mRNA two-dose vaccination, mRNA three-dose vaccination, and hybrid immunity of previous infection and vaccination were investigated in Qatar for the Alpha, Beta, and Delta variants. METHODS Six national, matched, test-negative, case-control studies were conducted between January 18 and December 18, 2021 on a sample of 239,120 PCR-positive tests and 6,103,365 PCR-negative tests. FINDINGS Effectiveness of previous infection against Alpha, Beta, and Delta reinfection was 89.5% (95% CI: 85.5-92.3%), 87.9% (95% CI: 85.4-89.9%), and 90.0% (95% CI: 86.7-92.5%), respectively. Effectiveness of two-dose BNT162b2 vaccination against Alpha, Beta, and Delta infection was 90.5% (95% CI, 83.9-94.4%), 80.5% (95% CI: 79.0-82.0%), and 58.1% (95% CI: 54.6-61.3%), respectively. Effectiveness of three-dose BNT162b2 vaccination against Delta infection was 91.7% (95% CI: 87.1-94.7%). Effectiveness of hybrid immunity of previous infection and two-dose BNT162b2 vaccination was 97.4% (95% CI: 95.4-98.5%) against Beta infection and 94.5% (95% CI: 92.8-95.8%) against Delta infection. Effectiveness of previous infection and three-dose BNT162b2 vaccination was 98.1% (95% CI: 85.7-99.7%) against Delta infection. All five forms of immunity had >90% protection against severe, critical, or fatal COVID-19 regardless of variant. Similar effectiveness estimates were observed for mRNA-1273. A mathematical model accurately predicted hybrid immunity protection by assuming that the individual effects of previous infection and vaccination acted independently. INTERPRETATION Hybrid immunity, offering the strongest protection, was mathematically predicted by assuming that the immunities obtained from previous infection and vaccination act independently, without synergy or redundancy. FUNDING The Biomedical Research Program and the Biostatistics, Epidemiology, and the Biomathematics Research Core, both at Weill Cornell Medicine-Qatar, Ministry of Public Health, Hamad Medical Corporation, Sidra Medicine, Qatar Genome Programme, Qatar University Biomedical Research Center, and Qatar University Internal Grant ID QUCG-CAS-23/24-114.
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Affiliation(s)
- Heba N Altarawneh
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Houssein H Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | | | - Hadi M Yassine
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hebah A Al-Khatib
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Asmaa A Al Thani
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Peter Coyle
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar; Hamad Medical Corporation, Doha, Qatar; Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom
| | | | | | | | | | | | | | - Hanan F Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K Nasrallah
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar; Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA; Hamad Medical Corporation, Doha, Qatar; Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | | | | | | | | | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA; Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar; College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar.
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10
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Kovanen PT, Vuorio A. SARS-CoV-2 reinfection: Adding insult to dysfunctional endothelium in patients with atherosclerotic cardiovascular disease. ATHEROSCLEROSIS PLUS 2023; 53:1-5. [PMID: 37293388 PMCID: PMC10238112 DOI: 10.1016/j.athplu.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 05/24/2023] [Accepted: 06/02/2023] [Indexed: 06/10/2023]
Abstract
In this short narrative review, we aim at defining the pathophysiological role endothelial dysfunction in the observed COVID-19-associated rise in risk of cardiovascular disease. Variants of the SARS-CoV-2 virus have caused several epidemic waves of COVID-19, and the emergence and rapid spread of new variants and subvariants are likely. Based on a large cohort study, the incidence rate of SARS-CoV-2 reinfection is about 0.66 per 10 000 person-weeks. Both the first infection and reinfection with SARS-CoV-2 increase cardiac event risk, particularly in vulnerable patients with cardiovascular risk factors and the accompanying systemic endothelial dysfunction. By worsening pre-existing endothelial dysfunction, both the first infection and reinfection with ensuing COVID-19 may turn the endothelium procoagulative and prothrombotic, and ultimately lead to local thrombus formation. When occurring in an epicardial coronary artery, the risk of an acute coronary syndrome increases, and when occurring in intramyocardial microvessels, scattered myocardial injuries will ensue, both predisposing the COVID-19 patients to adverse cardiovascular outcomes. In conclusion, considering weakened protection against the cardiovascular risk-enhancing reinfections with emerging new subvariants of SARS-CoV-2, treatment of COVID-19 patients with statins during the illness and thereafter is recommended, partly because the statins tend to reduce endothelial dysfunction.
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Affiliation(s)
| | - Alpo Vuorio
- Mehiläinen, Airport Health Center, Vantaa, Finland
- University of Helsinki, Department of Forensic Medicine, Helsinki, Finland
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11
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Qassim SH, Chemaitelly H, Ayoub HH, Coyle P, Tang P, Yassine HM, Al Thani AA, Al-Khatib HA, Hasan MR, Al-Kanaani Z, Al-Kuwari E, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Butt AA, Al-Romaihi HE, Al-Thani MH, Al-Khal A, Bertollini R, Abu-Raddad LJ. Population immunity of natural infection, primary-series vaccination, and booster vaccination in Qatar during the COVID-19 pandemic: an observational study. EClinicalMedicine 2023; 62:102102. [PMID: 37533414 PMCID: PMC10393554 DOI: 10.1016/j.eclinm.2023.102102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/29/2023] [Accepted: 06/29/2023] [Indexed: 08/04/2023] Open
Abstract
Background Waning of natural infection protection and vaccine protection highlight the need to evaluate changes in population immunity over time. Population immunity of previous SARS-CoV-2 infection or of COVID-19 vaccination are defined, respectively, as the overall protection against reinfection or against breakthrough infection at a given point in time in a given population. Methods We estimated these population immunities in Qatar's population between July 1, 2020 and November 30, 2022, to discern generic features of the epidemiology of SARS-CoV-2. Effectiveness of previous infection, mRNA primary-series vaccination, and mRNA booster (third-dose) vaccination in preventing infection were estimated, month by month, using matched, test-negative, case-control studies. Findings Previous-infection effectiveness against reinfection was strong before emergence of Omicron, but declined with time after a wave and rebounded after a new wave. Effectiveness dropped after Omicron emergence from 88.3% (95% CI: 84.8-91.0%) in November 2021 to 51.0% (95% CI: 48.3-53.6%) in December 2021. Primary-series effectiveness against infection was 84.0% (95% CI: 83.0-85.0%) in April 2021, soon after introduction of vaccination, before waning gradually to 52.7% (95% CI: 46.5-58.2%) by November 2021. Effectiveness declined linearly by ∼1 percentage point every 5 days. After Omicron emergence, effectiveness dropped from 52.7% (95% CI: 46.5-58.2%) in November 2021 to negligible levels in December 2021. Booster effectiveness dropped after Omicron emergence from 83.0% (95% CI: 65.6-91.6%) in November 2021 to 32.9% (95% CI: 26.7-38.5%) in December 2021, and continued to decline thereafter. Effectiveness of previous infection and vaccination against severe, critical, or fatal COVID-19 were generally >80% throughout the study duration. Interpretation High population immunity against infection may not be sustained beyond a year, but population immunity against severe COVID-19 is durable with slow waning even after Omicron emergence. Funding The Biomedical Research Program and the Biostatistics, Epidemiology, and the Biomathematics Research Core, both at Weill Cornell Medicine-Qatar, Ministry of Public Health, Hamad Medical Corporation, Sidra Medicine, Qatar Genome Programme, Qatar University Biomedical Research Center, and Qatar University Internal Grant ID QUCG-CAS-23/24-114.
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Affiliation(s)
- Suelen H. Qassim
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Houssein H. Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | - Hadi M. Yassine
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Asmaa A. Al Thani
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Hebah A. Al-Khatib
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | | | | | | | | | | | | | | | - Hanan F. Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K. Nasrallah
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | | | - Adeel A. Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Hamad Medical Corporation, Doha, Qatar
- Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | | | | | | | | | - Laith J. Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
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12
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Akuno AO, Ramírez-Ramírez LL, Espinoza JF. Inference on a Multi-Patch Epidemic Model with Partial Mobility, Residency, and Demography: Case of the 2020 COVID-19 Outbreak in Hermosillo, Mexico. ENTROPY (BASEL, SWITZERLAND) 2023; 25:968. [PMID: 37509915 PMCID: PMC10378648 DOI: 10.3390/e25070968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/02/2023] [Accepted: 06/14/2023] [Indexed: 07/30/2023]
Abstract
Most studies modeling population mobility and the spread of infectious diseases, particularly those using meta-population multi-patch models, tend to focus on the theoretical properties and numerical simulation of such models. As such, there is relatively scant literature focused on numerical fit, inference, and uncertainty quantification of epidemic models with population mobility. In this research, we use three estimation techniques to solve an inverse problem and quantify its uncertainty for a human-mobility-based multi-patch epidemic model using mobile phone sensing data and confirmed COVID-19-positive cases in Hermosillo, Mexico. First, we utilize a Brownian bridge model using mobile phone GPS data to estimate the residence and mobility parameters of the epidemic model. In the second step, we estimate the optimal model epidemiological parameters by deterministically inverting the model using a Darwinian-inspired evolutionary algorithm (EA)-that is, a genetic algorithm (GA). The third part of the analysis involves performing inference and uncertainty quantification in the epidemic model using two Bayesian Monte Carlo sampling methods: t-walk and Hamiltonian Monte Carlo (HMC). The results demonstrate that the estimated model parameters and incidence adequately fit the observed daily COVID-19 incidence in Hermosillo. Moreover, the estimated parameters from the HMC method yield large credible intervals, improving their coverage for the observed and predicted daily incidences. Furthermore, we observe that the use of a multi-patch model with mobility yields improved predictions when compared to a single-patch model.
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Affiliation(s)
- Albert Orwa Akuno
- Departamento de Probabilidad y Estadística, Centro de Investigación en Matemáticas A.C., Jalisco s/n, Colonia Valenciana, Guanajuato C.P. 36023, Gto, Mexico
| | - L Leticia Ramírez-Ramírez
- Departamento de Probabilidad y Estadística, Centro de Investigación en Matemáticas A.C., Jalisco s/n, Colonia Valenciana, Guanajuato C.P. 36023, Gto, Mexico
| | - Jesús F Espinoza
- Departamento de Matemáticas, Universidad de Sonora, Rosales y Boulevard Luis Encinas, Hermosillo C.P. 83000, Sonora, Mexico
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13
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Mathew M, Sebastian J, Doddaiah N, Thomas A, Narayanappa S. Clinico-epidemiological profile and outcome of infected health care workers during the three consecutive waves of COVID-19 pandemic: a longitudinal cohort study. Ther Adv Vaccines Immunother 2023; 11:25151355231181744. [PMID: 37362156 PMCID: PMC10285439 DOI: 10.1177/25151355231181744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 05/15/2023] [Indexed: 06/28/2023] Open
Abstract
Background Health care workers are considered as high-risk population, who deal with many unknown, undiagnosed, and subclinical infectious diseases in their daily life. Currently, the COVID-19 pandemic posed as an add-on burden for these frontline workers in all aspects. Although, many adverse physical and mental effects of pandemic among health care workers (HCWs) were discussed worldwide, a long-term study for delayed complications needed to be explored. Aim The study evaluates and compares three waves of the pandemic in various aspects such as the incidence, prevalence, severity, risk factors, and variations in the pattern of COVID-19 infection, impact of vaccination, and post-infection complications among the HCWs. Methodology A longitudinal observational study was carried out over a period of 2 years and another 6 months for follow-up. The study included all HCWs who tested positive in any one wave of COVID-19 pandemic with any one of the confirmed COVID-19 test. Each COVID-19-affected HCW was followed up through telephone calls and direct interviews conducted at the study site. Admission details and other background details of the study population were collected from the hospital records. Results A total of 968 HCWs were COVID-19 positive in any of the three waves, and highest incidence (53.00%) was caused by the Omicron variant. High severity and hospitalization was observed in the first wave (no vaccination) and fully immunized personnel were found to be out of danger of being hospitalized during all succeeding waves (chi-square value: 87.04, p < 0.05). Predictors such as female gender, occupational exposure, and comorbid status were identified as possible risk factors for infection. A total of 70 HCWs reported with 104 complications, of which chronic diseases such as new onset of diabetes (n = 3), cardiovascular events (n = 8), worsening of preexisting comorbidities (n = 8), etc. were found out. Conclusions This study proves the benefit of being immunized rather than the risk of being infected. This study documents that immunization impacted complication and hospitalization rates of COVID-19 infection. This evidence may help in tackling vaccine hesitancy across the nations.
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Affiliation(s)
- Merrin Mathew
- Department of Pharmacy Practice, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru, India
| | - Juny Sebastian
- Department of Pharmacy Practice, College of Pharmacy, Gulf Medical University, Ajman, United Arab Emirates
| | | | - Anmaria Thomas
- Department of Pharmacy Practice, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru, India
| | - Sinchana Narayanappa
- Department of Radio Diagnosis, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru, India
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Morrison H, Jackson S, McShane H. Controlled human infection models in COVID-19 and tuberculosis: current progress and future challenges. Front Immunol 2023; 14:1211388. [PMID: 37304270 PMCID: PMC10248465 DOI: 10.3389/fimmu.2023.1211388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 05/09/2023] [Indexed: 06/13/2023] Open
Abstract
Controlled Human Infection Models (CHIMs) involve deliberately exposing healthy human volunteers to a known pathogen, to allow the detailed study of disease processes and evaluate methods of treatment and prevention, including next generation vaccines. CHIMs are in development for both tuberculosis (TB) and Covid-19, but challenges remain in their ongoing optimisation and refinement. It would be unethical to deliberately infect humans with virulent Mycobacteria tuberculosis (M.tb), however surrogate models involving other mycobacteria, M.tb Purified Protein Derivative or genetically modified forms of M.tb either exist or are under development. These utilise varying routes of administration, including via aerosol, per bronchoscope or intradermal injection, each with their own advantages and disadvantages. Intranasal CHIMs with SARS-CoV-2 were developed against the backdrop of the evolving Covid-19 pandemic and are currently being utilised to both assess viral kinetics, interrogate the local and systemic immunological responses post exposure, and identify immune correlates of protection. In future it is hoped they can be used to assess new treatments and vaccines. The changing face of the pandemic, including the emergence of new virus variants and increasing levels of vaccination and natural immunity within populations, has provided a unique and complex environment within which to develop a SARS-CoV-2 CHIM. This article will discuss current progress and potential future developments in CHIMs for these two globally significant pathogens.
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15
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Serwanga J, Baine C, Mugaba S, Ankunda V, Auma BO, Oluka GK, Kato L, Kitabye I, Sembera J, Odoch G, Ejou P, Nalumansi A, Gombe B, Musenero M, Kaleebu P. Seroprevalence and durability of antibody responses to AstraZeneca vaccination in Ugandans with prior mild or asymptomatic COVID-19: implications for vaccine policy. Front Immunol 2023; 14:1183983. [PMID: 37205095 PMCID: PMC10187141 DOI: 10.3389/fimmu.2023.1183983] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 04/06/2023] [Indexed: 05/21/2023] Open
Abstract
Introduction The duration and timing of immunity conferred by COVID-19 vaccination in sub-Saharan Africa are crucial for guiding pandemic policy interventions, but systematic data for this region is scarce. This study investigated the antibody response after AstraZeneca vaccination in COVID-19 convalescent Ugandans. Methods We recruited 86 participants with a previous rt-PCR-confirmed mild or asymptomatic COVID-19 infection and measured the prevalence and levels of spike-directed IgG, IgM, and IgA antibodies at baseline, 14 and 28 days after the first dose (priming), 14 days after the second dose (boosting), and at six- and nine-months post-priming. We also measured the prevalence and levels of nucleoprotein-directed antibodies to assess breakthrough infections. Results Within two weeks of priming, vaccination substantially increased the prevalence and concentrations of spike-directed antibodies (p < 0.0001, Wilcoxon signed rank test), with 97.0% and 66% of vaccinated individuals possessing S-IgG and S-IgA antibodies before administering the booster dose. S-IgM prevalence changed marginally after the initial vaccination and barely after the booster, consistent with an already primed immune system. However, we also observed a rise in nucleoprotein seroprevalence, indicative of breakthroughs six months after the initial vaccination. Discussion Our results suggest that vaccination of COVID-19 convalescent individuals with the AstraZeneca vaccine induces a robust and differential spike-directed antibody response. The data highlights the value of vaccination as an effective method for inducing immunity in previously infected individuals and the importance of administering two doses to maintain protective immunity. Monitoring anti-spike IgG and IgA when assessing vaccine-induced antibody responses is suggested for this population; assessing S-IgM will underestimate the response. The AstraZeneca vaccine is a valuable tool in the fight against COVID-19. Further research is needed to determine the durability of vaccine-induced immunity and the potential need for booster doses.
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Affiliation(s)
- Jennifer Serwanga
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Claire Baine
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Susan Mugaba
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Violet Ankunda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Betty Oliver Auma
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Gerald Kevin Oluka
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Laban Kato
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Isaac Kitabye
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Jackson Sembera
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Geoffrey Odoch
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Peter Ejou
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Amina Nalumansi
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Ben Gombe
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Monica Musenero
- Science, Technology, and Innovation Secretariat, Office of the President, Government of Uganda, Kampala, Uganda
| | - Pontiano Kaleebu
- Pathogen Genomics, Phenotype, and Immunity Program, Medical Research Council, Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
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16
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AlNuaimi AA, Chemaitelly H, Semaan S, AlMukdad S, Al-Kanaani Z, Kaleeckal AH, Latif AN, Al-Romaihi HE, Butt AA, Al-Thani MH, Bertollini R, AbdulMalik M, Al-Khal A, Abu-Raddad LJ. All-cause and COVID-19 mortality in Qatar during the COVID-19 pandemic. BMJ Glob Health 2023; 8:bmjgh-2023-012291. [PMID: 37142299 PMCID: PMC10163334 DOI: 10.1136/bmjgh-2023-012291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 04/21/2023] [Indexed: 05/06/2023] Open
Abstract
OBJECTIVE To investigate all-cause mortality, COVID-19 mortality and all-cause non-COVID-19 mortality in Qatar during the COVID-19 pandemic. METHODS A national, retrospective cohort analysis and national, matched, retrospective cohort studies were conducted between 5 February 2020 and 19 September 2022. RESULTS There were 5025 deaths during a follow-up time of 5 247 220 person-years, of which 675 were COVID-19 related. Incidence rates were 0.96 (95% CI 0.93 to 0.98) per 1000 person-years for all-cause mortality, 0.13 (95% CI 0.12 to 0.14) per 1000 person-years for COVID-19 mortality and 0.83 (95% CI 0.80 to 0.85) per 1000 person-years for all-cause non-COVID-19 mortality. Adjusted HR, comparing all-cause non-COVID-19 mortality relative to Qataris, was lowest for Indians at 0.38 (95% CI 0.32 to 0.44), highest for Filipinos at 0.56 (95% CI 0.45 to 0.69) and was 0.51 (95% CI 0.45 to 0.58) for craft and manual workers (CMWs). Adjusted HR, comparing COVID-19 mortality relative to Qataris, was lowest for Indians at 1.54 (95% CI 0.97 to 2.44), highest for Nepalese at 5.34 (95% CI 1.56 to 18.34) and was 1.86 (95% CI 1.32 to 2.60) for CMWs. Incidence rate of all-cause mortality for each nationality group was lower than the crude death rate in the country of origin. CONCLUSIONS Risk of non-COVID-19 death was low and was lowest among CMWs, perhaps reflecting the healthy worker effect. Risk of COVID-19 death was also low, but was highest among CMWs, largely reflecting higher exposure during first epidemic wave, before advent of effective COVID-19 treatments and vaccines.
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Affiliation(s)
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University,Qatar Foundation - Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA
| | - Sandy Semaan
- Primary Health Care Corporation, Doha, Ad Dawhah, Qatar
| | - Sawsan AlMukdad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University,Qatar Foundation - Education City, Doha, Qatar
| | | | | | | | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA
- Hamad Medical Corporation, Doha, Qatar
- Department of Medicine, Weill Cornell Medicine, Cornell University, New York, New York, USA
| | | | | | | | | | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University,Qatar Foundation - Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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17
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Facciuolo A, Van Kessel J, Kroeker A, Liao M, Lew JM, Falzarano D, Kelvin AA, Gerdts V, Napper S. Longitudinal analysis of SARS-CoV-2 reinfection reveals distinct kinetics and emergence of cross-neutralizing antibodies to variants of concern. Front Microbiol 2023; 14:1148255. [PMID: 37065160 PMCID: PMC10090301 DOI: 10.3389/fmicb.2023.1148255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
The ongoing evolution of SARS-CoV-2 continues to raise new questions regarding the duration of immunity to reinfection with emerging variants. To address these knowledge gaps, controlled investigations in established animal models are needed to assess duration of immunity induced by each SARS-CoV-2 lineage and precisely evaluate the extent of cross-reactivity and cross-protection afforded. Using the Syrian hamster model, we specifically investigated duration of infection acquired immunity to SARS-CoV-2 ancestral Wuhan strain over 12 months. Plasma spike- and RBD-specific IgG titers against ancestral SARS-CoV-2 peaked at 4 months post-infection and showed a modest decline by 12 months. Similar kinetics were observed with plasma virus neutralizing antibody titers which peaked at 2 months post-infection and showed a modest decline by 12 months. Reinfection with ancestral SARS-CoV-2 at regular intervals demonstrated that prior infection provides long-lasting immunity as hamsters were protected against severe disease when rechallenged at 2, 4, 6, and 12 months after primary infection, and this coincided with the induction of high virus neutralizing antibody titers. Cross-neutralizing antibody titers against the B.1.617.2 variant (Delta) progressively waned in blood over 12 months, however, re-infection boosted these titers to levels equivalent to ancestral SARS-CoV-2. Conversely, cross-neutralizing antibodies to the BA.1 variant (Omicron) were virtually undetectable at all time-points after primary infection and were only detected following reinfection at 6 and 12 months. Collectively, these data demonstrate that infection with ancestral SARS-CoV-2 strains generates antibody responses that continue to evolve long after resolution of infection with distinct kinetics and emergence of cross-reactive and cross-neutralizing antibodies to Delta and Omicron variants and their specific spike antigens.
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Affiliation(s)
- Antonio Facciuolo
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
- Department of Veterinary Microbiology, University of Saskatchewan, Saskatoon, SK, Canada
- *Correspondence: Antonio Facciuolo,
| | - Jill Van Kessel
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
| | - Andrea Kroeker
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
| | - Mingmin Liao
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
| | - Jocelyne M. Lew
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
| | - Darryl Falzarano
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
- Department of Veterinary Microbiology, University of Saskatchewan, Saskatoon, SK, Canada
| | - Alyson A. Kelvin
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
- Department of Biochemistry, Microbiology and Immunology, University of Saskatchewan, Saskatoon, SK, Canada
| | - Volker Gerdts
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
- Department of Veterinary Microbiology, University of Saskatchewan, Saskatoon, SK, Canada
| | - Scott Napper
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, Canada
- Department of Biochemistry, Microbiology and Immunology, University of Saskatchewan, Saskatoon, SK, Canada
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18
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Ortiz-Millán G. COVID-19 Health Passes: Practical and Ethical Issues. JOURNAL OF BIOETHICAL INQUIRY 2023; 20:125-138. [PMID: 36630062 PMCID: PMC9832398 DOI: 10.1007/s11673-022-10227-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 08/28/2022] [Indexed: 05/04/2023]
Abstract
Several countries have implemented COVID-19 health passes or certificates to promote a safer return to in-person social activities. These passes have been proposed as a way to prove that someone has been vaccinated, has recovered from the disease, or has negative results on a diagnostic test. However, many people have questioned their ethical justification. This article presents some practical and ethical problems to consider in the event of wishing to implement these passes. Among the former, it is questioned how accurate diagnostic tests are as a means of ensuring that a person is not contagious, whether vaccination guarantees immunity, the fact that health passes can be forged, whether they encourage vaccination, and the problem that there is no universally recognized health pass. Among the ethical issues, it is discussed whether health passes promote discrimination and inequality and whether they violate rights to privacy and freedom. It is concluded that health passes have enough ethical justification to be implemented.
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Affiliation(s)
- Gustavo Ortiz-Millán
- Instituto de Investigaciones Filosóficas, Universidad Nacional Autónoma de México (UNAM), Circuito Mario de la Cueva s/n, Ciudad Universitaria, Coyoacán, 04510, Mexico City, Mexico.
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19
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Effect of the incremental protection of previous infection against Omicron infection among individuals with a hybrid of infection- and vaccine-induced immunity: a population-based cohort study in Canada. Int J Infect Dis 2023; 127:69-76. [PMID: 36455812 DOI: 10.1016/j.ijid.2022.11.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/03/2022] [Accepted: 11/23/2022] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVES We examined the incremental protection and durability of infection-acquired immunity against Omicron infection in individuals with hybrid immunity in Ontario, Canada. METHODS We followed up 6 million individuals with at least one multiplex reverse transcriptase-polymerase chain reaction test before November 21, 2021, until an Omicron infection. Protection via infection-acquired immunity was assessed by comparing Omicron infection risk between previously infected individuals and those without documented infection under different vaccination scenarios and stratified by time since the last infection or vaccination. RESULTS A previous infection was associated with 68% (95% CI 61-73) and 43% (95% CI 27-56) increased protection against Omicron infection in individuals with two and three doses, respectively. Among individuals with two-dose vaccination, the incremental protection of infection-induced immunity decreased from 79% (95% CI 75-81) within 3 months after vaccination or infection to 27% (95% CI 14-37) at 9-11 months. In individuals with three-dose vaccination, it decreased from 57% (95% CI 50-63) within 3 months to 37% (95% CI 19-51) at 3-5 months after vaccination or infection. CONCLUSION Previous SARS-CovV-2 infections provide added cross-variant immunity to vaccination. Given the limited durability of infection-acquired protection in individuals with hybrid immunity, its influence on shield-effects at the population level and reinfection risks at the individual level may be limited.
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20
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Zsichla L, Müller V. Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors. Viruses 2023; 15:175. [PMID: 36680215 PMCID: PMC9863423 DOI: 10.3390/v15010175] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/04/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.
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Affiliation(s)
- Levente Zsichla
- Institute of Biology, Eötvös Loránd University, 1117 Budapest, Hungary
- National Laboratory for Health Security, Eötvös Loránd University, 1117 Budapest, Hungary
| | - Viktor Müller
- Institute of Biology, Eötvös Loránd University, 1117 Budapest, Hungary
- National Laboratory for Health Security, Eötvös Loránd University, 1117 Budapest, Hungary
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21
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Montes-González JA, Zaragoza-Jiménez CA, Antonio-Villa NE, Fermín-Martínez CA, Ramírez-García D, Vargas-Vázquez A, Gutiérrez-Vargas RI, García-Rodríguez G, López-Gatell H, Valdés-Ferrer SI, Bello-Chavolla OY. Protection of hybrid immunity against SARS-CoV-2 reinfection and severe COVID-19 during periods of Omicron variant predominance in Mexico. Front Public Health 2023; 11:1146059. [PMID: 37081954 PMCID: PMC10110947 DOI: 10.3389/fpubh.2023.1146059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/07/2023] [Indexed: 04/22/2023] Open
Abstract
Background With the widespread transmission of the Omicron SARS-CoV-2 variant, reinfections have become increasingly common. Here, we explored the role of immunity, primary infection severity, and variant predominance in the risk of reinfection and severe COVID-19 during Omicron predominance in Mexico. Methods We analyzed reinfections in Mexico in individuals with a primary infection separated by at least 90 days from reinfection using a national surveillance registry of SARS-CoV-2 cases from March 3rd, 2020, to August 13th, 2022. Immunity-generating events included primary infection, partial or complete vaccination, and booster vaccines. Reinfections were matched by age and sex with controls with primary SARS-CoV-2 infection and negative RT-PCR or antigen test at least 90 days after primary infection to explore reinfection and severe disease risk factors. We also compared the protective efficacy of heterologous and homologous vaccine boosters against reinfection. Results We detected 231,202 SARS-CoV-2 reinfections in Mexico, most occurring in unvaccinated individuals (41.55%). Over 207,623 reinfections occurred during periods of Omicron (89.8%), BA.1 (36.74%), and BA.5 (33.67%) subvariant predominance and a case-fatality rate of 0.22%. Vaccination protected against reinfection, without significant influence of the order of immunity-generating events and provided >90% protection against severe reinfections. Heterologous booster schedules were associated with ~11% and ~ 54% lower risk for reinfection and reinfection-associated severe COVID-19, respectively, modified by time-elapsed since the last immunity-generating event, when compared against complete primary schedules. Conclusion SARS-CoV-2 reinfections increased during Omicron predominance. Hybrid immunity provides protection against reinfection and associated severe COVID-19, with potential benefit from heterologous booster schedules.
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Affiliation(s)
| | | | | | - Carlos A. Fermín-Martínez
- Dirección de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
| | | | - Arsenio Vargas-Vázquez
- MD/PhD (PECEM) Program, Facultad de Medicina, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
| | | | | | - Hugo López-Gatell
- Subsecretaría de Prevención y Promoción de la Salud, Secretaría de Salud, Mexico City, Mexico
| | - Sergio Iván Valdés-Ferrer
- Departamento de Neurología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Omar Yaxmehen Bello-Chavolla
- Dirección de Investigación, Instituto Nacional de Geriatría, Mexico City, Mexico
- *Correspondence: Omar Yaxmehen Bello-Chavolla,
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22
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Dehgani-Mobaraki P, Wang C, Floridi A, Floridi E, Dawoodi S, Zaidi AK. Long-term persistence of IgG antibodies in recovered COVID-19 individuals at 18 months post-infection and the impact of two-dose BNT162b2 (Pfizer-BioNTech) mRNA vaccination on the antibody response: Analysis using fixed-effects linear regression model. Virology 2023; 578:111-116. [PMID: 36516688 PMCID: PMC9725186 DOI: 10.1016/j.virol.2022.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/21/2022] [Accepted: 12/02/2022] [Indexed: 12/12/2022]
Abstract
This era of emerging variants needs a thorough evaluation of data on the long-term efficacy of immune responses in vaccinated as well as recovered individuals, to understand the overall evolution of the pandemic. In this study, we aimed to assess the dynamics of IgG response over 18 months in n = 36 patients from the Umbria region in Italy, who had a documented history of COVID-19 infection in March 2020, and then compared the impact of two-dose BNT162b2 (Pfizer-BioNTech) vaccination on the antibody responses of these patients with the ones who did not receive any dose of vaccine. This is the longest observation (March 2020-September 2021) for the presence of antibodies against SARS-CoV-2 in recovered individuals along with the impact of 2 dose-BNT162b2 vaccination on these responses. Fixed-effect regression models were used for statistical analysis which could be also used to predict future titer trends. At 18 months, 97% participants tested positive for anti-NCP hinting towards the persistence of infection-induced immunity even for the vaccinated individuals. Our study findings demonstrate that while double dose vaccination boosted the IgG levels in recovered individuals 161 times, this "boost" was relatively short-lived. The unvaccinated recovered individuals, in contrast, continued to show a steady decline but detectable antibody levels. Further studies are required to re-evaluate the timing and dose regimen of vaccines for an adequate immune response in recovered individuals.
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Affiliation(s)
- Puya Dehgani-Mobaraki
- Associazione Naso Sano, Umbria Regional Registry of Volunteer Activities, Via Luca Benincasa 2, San Mariano, 06073, Perugia, Italy.
| | - Chao Wang
- Health & Social Care Statistic, Faculty of Health, Social Care and Education, Kingston University and St George's, University of London, London, SW17 0RE, UK.
| | | | - Emanuela Floridi
- Centro Ricerche Analisi Biochimico Specialistiche, Perugia, Italy.
| | | | - Asiya K Zaidi
- Associazione Naso Sano, Umbria Regional Registry of Volunteer Activities and Research, San Mariano, Italy.
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23
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Epidemiological Surveillance of SARSCov2 in β-Thalassemia Patients in the Last Two Years: Reinfection Rate, Insights and Future Challenges. Mediterr J Hematol Infect Dis 2023; 15:e2023007. [PMID: 36660359 PMCID: PMC9833304 DOI: 10.4084/mjhid.2023.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 12/20/2022] [Indexed: 01/03/2023] Open
Abstract
Background: Although the association between comorbidities and the severity of COVID-19 infection has been extensively discussed, data on COVID-19 and hemoglobinopathies are still limited. SARS-Cov2 reinfections with severe acute respiratory syndrome have been described in the general population, usually with a milder outcome compared to the primary infection.
The aim of our study was to determine the rate of reinfection and clinical features in a population of β-thalassemia patients.
Results: Following the first infection, patients showed an adequate humoral immune response, however, all four patients are considered immune impaired owing to chronic transfusional support coupled with iron chelating treatment and splenectomy in three of the four.
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24
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Chemaitelly H, Nagelkerke N, Ayoub HH, Coyle P, Tang P, Yassine HM, Al-Khatib HA, Smatti MK, Hasan MR, Al-Kanaani Z, Al-Kuwari E, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Butt AA, Al-Romaihi HE, Al-Thani MH, Al-Khal A, Bertollini R, Abu-Raddad LJ. Duration of immune protection of SARS-CoV-2 natural infection against reinfection. J Travel Med 2022; 29:6731972. [PMID: 36179099 PMCID: PMC9619565 DOI: 10.1093/jtm/taac109] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 09/14/2022] [Accepted: 09/17/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND The future of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic hinges on virus evolution and duration of immune protection of natural infection against reinfection. We investigated the duration of protection afforded by natural infection, the effect of viral immune evasion on duration of protection and protection against severe reinfection, in Qatar, between 28 February 2020 and 5 June 2022. METHODS Three national, matched, retrospective cohort studies were conducted to compare the incidence of SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) severity among unvaccinated persons with a documented SARS-CoV-2 primary infection, to incidence among those infection-naïve and unvaccinated. Associations were estimated using Cox proportional hazard regression models. RESULTS Effectiveness of pre-Omicron primary infection against pre-Omicron reinfection was 85.5% [95% confidence interval (CI): 84.8-86.2%]. Effectiveness peaked at 90.5% (95% CI: 88.4-92.3%) in the 7th month after the primary infection, but waned to ~ 70% by the 16th month. Extrapolating this waning trend using a Gompertz curve suggested an effectiveness of 50% in the 22nd month and < 10% by the 32nd month. Effectiveness of pre-Omicron primary infection against Omicron reinfection was 38.1% (95% CI: 36.3-39.8%) and declined with time since primary infection. A Gompertz curve suggested an effectiveness of < 10% by the 15th month. Effectiveness of primary infection against severe, critical or fatal COVID-19 reinfection was 97.3% (95% CI: 94.9-98.6%), irrespective of the variant of primary infection or reinfection, and with no evidence for waning. Similar results were found in sub-group analyses for those ≥50 years of age. CONCLUSIONS Protection of natural infection against reinfection wanes and may diminish within a few years. Viral immune evasion accelerates this waning. Protection against severe reinfection remains very strong, with no evidence for waning, irrespective of variant, for over 14 months after primary infection.
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Affiliation(s)
- Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Research Department, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.,World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar.,Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Nico Nagelkerke
- Infectious Disease Epidemiology Group, Research Department, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
| | - Houssein H Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar.,Biomedical Research Center, QU Health, Qatar University, Doha, Qatar.,Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, UK
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | - Hadi M Yassine
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar.,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hebah A Al-Khatib
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar.,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Maria K Smatti
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar.,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | | | | | | | | | | | | | - Hanan F Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K Nasrallah
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar.,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.,Hamad Medical Corporation, Doha, Qatar.,Department of Medicine, Weill Cornell Medicine, Cornell University,New York, NY, USA
| | | | | | | | | | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Research Department, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.,World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar.,Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA.,Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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25
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Casey SM, Legler A, Hanchate AD, Perkins RB. Likelihood of COVID-19 reinfection in an urban community cohort in Massachusetts. DIALOGUES IN HEALTH 2022; 1:100057. [PMID: 36785636 PMCID: PMC9547391 DOI: 10.1016/j.dialog.2022.100057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 10/03/2022] [Accepted: 10/04/2022] [Indexed: 11/22/2022]
Abstract
Background Understanding the association of prior SARS-CoV-2 infection with subsequent reinfection has public health relevance. Objective To explore COVID-19 severity and SARS-CoV-2 infection and reinfection rates. Design Retrospective cohort study. Setting Boston, Massachusetts, during the first COVID-19 surge (01/01/2020-05/31/2020; Period-1) and after the first surge (06/01/2020-02/28/2021; Period-2); Period-2 included the second surge (11/01/2020-02/28/2021). Participants Patients in an academic medical center and six community health centers who received a clinical diagnosis of COVID-19 between 01/01/2020 and 05/31/2020 or SARS-CoV-2 testing between 01/01/2020 and 02/28/2021. Measurements COVID-19 severity was compared between Period-1 and Period-2. Poisson regression models adjusted for demographic variables, medical comorbidities, and census tract were used to assess reinfection risk among patients with COVID-19 diagnoses or SARS-CoV-2 testing during Period-1 and additional SARS-CoV-2 testing during Period-2. Results Among 142,047 individuals receiving SARS-CoV-2 testing or clinical diagnoses during the study period, 15.8% were infected. Among COVID-19 patients, 22.5% visited the emergency department, 13% were hospitalized, and 4% received critical care. Healthcare utilization was higher during Period-1 than Period-2 (22.9% vs. 18.9% emergency department use, 14.7% vs. 9.9% hospitalization, 5.5% vs. 2.5% critical care; p < 0.001). Reinfection was assessed among 8961 patients with a SARS-CoV-2 test or COVID-19 diagnosis in Period-1 who underwent additional testing in Period-2. A total of 2.7% (n = 65/2431) with SARS-CoV-2 in Period-1 tested positive in Period-2, compared with 12.6% (n = 821/6530) of those who initially tested negative (IRR of reinfection = 0.19, 95% CI: 0.15-0.25). Conclusions Prior SARS-CoV-2 infection among this observational cohort was associated with an 81% lower reinfection rate.
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Affiliation(s)
- Sharon M. Casey
- Department of Obstetrics and Gynecology, Boston University School of Medicine and Boston Medical Center, Boston, MA, United States of America
| | - Aaron Legler
- Department of Obstetrics and Gynecology, Boston University School of Medicine and Boston Medical Center, Boston, MA, United States of America
| | - Amresh D. Hanchate
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Rebecca B. Perkins
- Department of Obstetrics and Gynecology, Boston University School of Medicine and Boston Medical Center, Boston, MA, United States of America,Corresponding author at: 85 E. Concord St., Boston, MA 02118, United States of America
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26
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Chemaitelly H, Ayoub HH, AlMukdad S, Coyle P, Tang P, Yassine HM, Al-Khatib HA, Smatti MK, Hasan MR, Al-Kanaani Z, Al-Kuwari E, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Butt AA, Al-Romaihi HE, Al-Thani MH, Al-Khal A, Bertollini R, Abu-Raddad LJ. Protection from previous natural infection compared with mRNA vaccination against SARS-CoV-2 infection and severe COVID-19 in Qatar: a retrospective cohort study. THE LANCET. MICROBE 2022; 3:e944-e955. [PMID: 36375482 PMCID: PMC9651957 DOI: 10.1016/s2666-5247(22)00287-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/24/2022] [Accepted: 09/21/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND Understanding protection conferred by natural SARS-CoV-2 infection versus COVID-19 vaccination is important for informing vaccine mandate decisions. We compared protection conferred by natural infection versus that from the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines in Qatar. METHODS We conducted two matched retrospective cohort studies that emulated target trials. Data were obtained from the national federated databases for COVID-19 vaccination, SARS-CoV-2 testing, and COVID-19-related hospitalisation and death between Feb 28, 2020 (pandemic onset in Qatar) and May 12, 2022. We matched individuals with a documented primary infection and no vaccination record (natural infection cohort) with individuals who had received two doses (primary series) of the same vaccine (BNT162b2-vaccinated or mRNA-1273-vaccinated cohorts) at the start of follow-up (90 days after the primary infection). Individuals were exact matched (1:1) by sex, 10-year age group, nationality, comorbidity count, and timing of primary infection or first-dose vaccination. Incidence of SARS-CoV-2 infection and COVID-19-related hospitalisation and death in the natural infection cohorts was compared with incidence in the vaccinated cohorts, using Cox proportional hazards regression models with adjustment for matching factors. FINDINGS Between Jan 5, 2021 (date of second-dose vaccine roll-out) and May 12, 2022, 104 500 individuals vaccinated with BNT162b2 and 61 955 individuals vaccinated with mRNA-1273 were matched to unvaccinated individuals with a documented primary infection. During follow-up, 7123 SARS-CoV-2 infections were recorded in the BNT162b2-vaccinated cohort and 3583 reinfections were recorded in the matched natural infection cohort. 4282 SARS-CoV-2 infections were recorded in the mRNA-1273-vaccinated cohort and 2301 reinfections were recorded in the matched natural infection cohort. The overall adjusted hazard ratio (HR) for SARS-CoV-2 infection was 0·47 (95% CI 0·45-0·48) after previous natural infection versus BNT162b2 vaccination, and 0·51 (0·49-0·54) after previous natural infection versus mRNA-1273 vaccination. The overall adjusted HR for severe (acute care hospitalisations), critical (intensive care unit hospitalisations), or fatal COVID-19 cases was 0·24 (0·08-0·72) after previous natural infection versus BNT162b2 vaccination, and 0·24 (0·05-1·19) after previous natural infection versus mRNA-1273 vaccination. Severe, critical, or fatal COVID-19 was rare in both the natural infection and vaccinated cohorts. INTERPRETATION Previous natural infection was associated with lower incidence of SARS-CoV-2 infection, regardless of the variant, than mRNA primary-series vaccination. Vaccination remains the safest and most optimal tool for protecting against infection and COVID-19-related hospitalisation and death, irrespective of previous infection status. FUNDING The Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core, Weill Cornell Medicine-Qatar; Qatar Ministry of Public Health; Hamad Medical Corporation; Sidra Medicine; Qatar Genome Programme; and Qatar University Biomedical Research Center.
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Affiliation(s)
- Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar,WHO Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar,Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA,Correspondence to: Dr Hiam Chemaitelly, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha 24144, Qatar
| | - Houssein H Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Sawsan AlMukdad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar,WHO Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar,Biomedical Research Center, QU Health, Qatar University, Doha, Qatar,Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, UK
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | - Hadi M Yassine
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hebah A Al-Khatib
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Maria K Smatti
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | | | | | | | | | | | | | - Hanan F Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K Nasrallah
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar,Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA,Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA,Hamad Medical Corporation, Doha, Qatar
| | | | | | | | | | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar,WHO Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha, Qatar,Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, USA,Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar,Professor Laith J Abu-Raddad, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation-Education City, Doha 24144, Qatar
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27
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Field CJ, Heinly TA, Patel DR, Sim DG, Luley E, Gupta SL, Vanderford TH, Wrammert J, Sutton TC. Immune durability and protection against SARS-CoV-2 re-infection in Syrian hamsters. Emerg Microbes Infect 2022; 11:1103-1114. [PMID: 35333692 PMCID: PMC9037228 DOI: 10.1080/22221751.2022.2058419] [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: 12/13/2021] [Accepted: 03/22/2022] [Indexed: 01/08/2023]
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a pandemic. As immunity to endemic human coronaviruses (i.e. NL63 or OC43) wanes leading to re-infection, it was unknown if SARS-CoV-2 immunity would also decline permitting repeat infections. Recent case reports confirm previously infected individuals can become re-infected; however, re-infection may be due to heterogeneity in the initial infection or the host immune response, or may be the result of infection with a variant strain that escapes pre-existing immunity. To control these variables, we utilized the Syrian hamster model to evaluate the duration of immunity and susceptibility to re-infection with SARS-CoV-2. Hamsters were given a primary mock or SARS-CoV-2 infection (culture media or 105 TCID50 USA/WA1/2020 isolate, respectively). Mock and SARS-CoV-2 infected hamsters were then given a secondary SARS-CoV-2 infection at 1, 2, 4, or 6 months post-primary infection (n = 14/time point/group). After the primary SARS-CoV-2 infection, hamsters developed anti-spike protein IgG, IgA, and neutralizing antibodies, and these antibodies were maintained for at least 6 months. Upon secondary SARS-CoV-2 challenge, previously SARS-CoV-2 infected animals were protected from weight loss, while all previously mock-infected animals became infected and lost weight. Importantly, despite having high titres of antibodies, one SARS-CoV-2 infected animal re-challenged at 4 months had a breakthrough infection with replicating virus in the upper and lower respiratory tract. These studies demonstrate immunity to SARS-CoV-2 is maintained for 6 months; however, protection may be incomplete and, even in the presence of high antibody titres, previously infected hosts may become re-infected.
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Affiliation(s)
- C. J. Field
- Department of Veterinary and Biomedical Science, The Pennsylvania State University, University Park, PA, USA
- The Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Emory-UGA Center of Excellence of Influenza Research and Surveillance (CEIRS), University Park, PA, USA
| | - T. A. Heinly
- Department of Veterinary and Biomedical Science, The Pennsylvania State University, University Park, PA, USA
- The Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Emory-UGA Center of Excellence of Influenza Research and Surveillance (CEIRS), University Park, PA, USA
| | - D. R. Patel
- Department of Veterinary and Biomedical Science, The Pennsylvania State University, University Park, PA, USA
- The Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
| | - D. G. Sim
- The Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Department of Biology, The Pennsylvania State University, University Park, PA, USA
| | - E. Luley
- Animal Diagnostic Lab, The Pennsylvania State University, University Park, PA, USA
| | - S. L. Gupta
- Department of Pediatrics, Division of Infectious Disease, School of Medicine, Emory University, Atlanta, GA, USA
| | - T. H. Vanderford
- Division of Microbiology and Immunology, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
| | - J. Wrammert
- Emory-UGA Center of Excellence of Influenza Research and Surveillance (CEIRS), University Park, PA, USA
- Department of Pediatrics, Division of Infectious Disease, School of Medicine, Emory University, Atlanta, GA, USA
| | - T. C. Sutton
- Department of Veterinary and Biomedical Science, The Pennsylvania State University, University Park, PA, USA
- The Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Emory-UGA Center of Excellence of Influenza Research and Surveillance (CEIRS), University Park, PA, USA
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28
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Chen Q, Zhu K, Liu X, Zhuang C, Huang X, Huang Y, Yao X, Quan J, Lin H, Huang S, Su Y, Wu T, Zhang J, Xia N. The Protection of Naturally Acquired Antibodies Against Subsequent SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis. Emerg Microbes Infect 2022; 11:793-803. [PMID: 35195494 PMCID: PMC8920404 DOI: 10.1080/22221751.2022.2046446] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The specific antibodies induced by SARS-CoV-2 infection may provide protection against a subsequent infection. However, the efficacy and duration of protection provided by naturally acquired immunity against subsequent SARS-CoV-2 infection remain controversial. We systematically searched for the literature describing COVID-19 reinfection published before 07 February 2022. The outcomes were the pooled incidence rate ratio (IRR) for estimating the risk of subsequent infection. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included studies. Statistical analyses were conducted using the R programming language 4.0.2. We identified 19 eligible studies including more than 3.5 million individuals without the history of COVID-19 vaccination. The efficacy of naturally acquired antibodies against reinfection was estimated at 84% (pooled IRR = 0.16, 95% CI: 0.14-0.18), with higher efficacy against symptomatic COVID-19 cases (pooled IRR = 0.09, 95% CI = 0.07-0.12) than asymptomatic infection (pooled IRR = 0.28, 95% CI = 0.14-0.54). In the subgroup analyses, the pooled IRRs of COVID-19 infection in health care workers (HCWs) and the general population were 0.22 (95% CI = 0.16-0.31) and 0.14 (95% CI = 0.12-0.17), respectively, with a significant difference (P = 0.02), and those in older (over 60 years) and younger (under 60 years) populations were 0.26 (95% CI = 0.15–0.48) and 0.16 (95% CI = 0.14-0.19), respectively. The risk of subsequent infection in the seropositive population appeared to increase slowly over time. In conclusion, naturally acquired antibodies against SARS-CoV-2 can significantly reduce the risk of subsequent infection, with a protection efficacy of 84%. Registration number: CRD42021286222
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Affiliation(s)
- Qi Chen
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Kongxin Zhu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Xiaohui Liu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Chunlan Zhuang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Xingcheng Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Yue Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Xingmei Yao
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Jiali Quan
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Hongyan Lin
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Shoujie Huang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Yingying Su
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Ting Wu
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Jun Zhang
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China
| | - Ningshao Xia
- State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, Strait Collaborative Innovation Center of Biomedicine and Pharmaceutics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China.,The Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen City, Fujian Province, People's Republic of China
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29
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Reis HC, Turk V. COVID-DSNet: A novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and Chest X-Ray images. Artif Intell Med 2022; 134:102427. [PMID: 36462906 PMCID: PMC9574866 DOI: 10.1016/j.artmed.2022.102427] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 10/07/2022] [Accepted: 10/13/2022] [Indexed: 12/14/2022]
Abstract
COVID-19 (SARS-CoV-2), which causes acute respiratory syndrome, is a contagious and deadly disease that has devastating effects on society and human life. COVID-19 can cause serious complications, especially in patients with pre-existing chronic health problems such as diabetes, hypertension, lung cancer, weakened immune systems, and the elderly. The most critical step in the fight against COVID-19 is the rapid diagnosis of infected patients. Computed Tomography (CT), chest X-ray (CXR), and RT-PCR diagnostic kits are frequently used to diagnose the disease. However, due to difficulties such as the inadequacy of RT-PCR test kits and false negative (FN) results in the early stages of the disease, the time-consuming examination of medical images obtained from CT and CXR imaging techniques by specialists/doctors, and the increasing workload on specialists, it is challenging to detect COVID-19. Therefore, researchers have suggested searching for new methods in COVID- 19 detection. In analysis studies with CT and CXR radiography images, it was determined that COVID-19-infected patients experienced abnormalities related to COVID-19. The anomalies observed here are the primary motivation for artificial intelligence researchers to develop COVID-19 detection applications with deep convolutional neural networks. Here, convolutional neural network-based deep learning algorithms from artificial intelligence technologies with high discrimination capabilities can be considered as an alternative approach in the disease detection process. This study proposes a deep convolutional neural network, COVID-DSNet, to diagnose typical pneumonia (bacterial, viral) and COVID-19 diseases from CT, CXR, hybrid CT + CXR images. In the multi-classification study with the CT dataset, 97.60 % accuracy and 97.60 % sensitivity values were obtained from the COVID-DSNet model, and 100 %, 96.30 %, and 96.58 % sensitivity values were obtained in the detection of typical, common pneumonia and COVID-19, respectively. The proposed model is an economical, practical deep learning network that data scientists can benefit from and develop. Although it is not a definitive solution in disease diagnosis, it may help experts as it produces successful results in detecting pneumonia and COVID-19.
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Affiliation(s)
- Hatice Catal Reis
- Department of Geomatics Engineering, Gumushane University, Gumushane 2900, Turkey,Corresponding author at: Department of Geomatics Engineering, Gumushane University, Gumushane 2900, Turkey
| | - Veysel Turk
- Department of Computer Engineering, University of Harran, Sanliurfa, Turkey
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30
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Liu WD, Wang JT, Chao TL, Ieong SM, Tsai YM, Kuo PH, Tsai MJ, Chen YJ, Li GC, Ho SY, Chen HH, Huang YS, Hung CC, Chen YC, Chang SY, Chang SC. Evolution of neutralizing antibodies and cross-activity against different variants of SARS-CoV-2 in patients recovering from COVID-19. J Formos Med Assoc 2022:S0929-6646(22)00436-3. [PMID: 36496300 PMCID: PMC9705194 DOI: 10.1016/j.jfma.2022.11.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/17/2022] [Accepted: 11/22/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Patients recovering from COVID-19 may need vaccination against SARS-CoV-2 because acquired immunity from primary infection may wane, given the emergence of new SARS-CoV-2 variants. Understanding the trends of anti-spike IgG and neutralizing antibody titers in patients recovering from COVID-19 may inform the decision made on the appropriate interval between recovery and vaccination. METHODS Participants aged 20 years or older and diagnosed with COVID-19 between January and December, 2020 were enrolled. Serum specimens were collected every three months from 10 days to 12 months after the onset of symptom for determinations of anti-spike IgG and neutralizing antibody titers against SARS-CoV-2 Wuhan strain with D614G mutation, alpha, gamma and delta variants. RESULTS Of 19 participants, we found a decreasing trend of geometric mean titers of anti-spike IgG from 560.9 to 217 and 92 BAU/mL after a 4-month and a 7-month follow-up, respectively. The anti-spike IgG titers declined more quickly in the ten participants with severe or critical disease than the nine participants with only mild to moderate disease between one month and seven months after SARS-CoV-2 infection (-8.49 vs - 2.34-fold, p < 0.001). The neutralizing activity of the convalescent serum specimens collected from participants recovering from wild-type SARS-CoV-2 infection against different variants was lower, especially against the delta variants (p < 0.01 for each variant with Wuhan strain as reference). CONCLUSION Acquired immunity from primary infection with SARS-CoV-2 waned within 4-7 months in COVID-19 patients, and neutralizing cross-activities against different SARS-CoV-2 variants were lower compared with those against wild-type strain.
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Affiliation(s)
- Wang-Da Liu
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan,Department of Medicine, National Taiwan University Cancer Center, Taipei, Taiwan
| | - Jann-Tay Wang
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan,Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhunan, Taiwan,Corresponding author. Department of Internal Medicine, National Taiwan University Hospital, 7 Chung-Shan South Rd., Taipei City 10002, Taiwan
| | - Tai-Ling Chao
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Si-Man Ieong
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ya-Min Tsai
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Po-Hsien Kuo
- Department of Internal Medicine, National Taiwan University Hospital Biomedical Park Hospital, Hsinchu, Taiwan
| | - Ming-Jui Tsai
- Department of Internal Medicine, National Taiwan University Hospital Yun-Lin Branch, Yun-Lin County, Taiwan
| | - Yi-Jie Chen
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Guei-Chi Li
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Shu-Yuan Ho
- Department of Laboratory Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hui-Hou Chen
- Department of Laboratory Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yu-Shan Huang
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chien-Ching Hung
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan,Department of Internal Medicine, National Taiwan University Hospital Yun-Lin Branch, Yun-Lin County, Taiwan,Department of Tropical Medicine and Parasitology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yee-Chun Chen
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan,Center of Infection Control, National Taiwan University Hospital, Taipei, Taiwan
| | - Sui-Yuan Chang
- Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, Taipei, Taiwan,Department of Laboratory Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan,Corresponding author. Department of Laboratory Medicine, National Taiwan University Hospital, 7 Chung-Shan South Rd., Taipei City 10002, Taiwan
| | - Shan-Chwen Chang
- Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan,School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
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Diani S, Leonardi E, Cavezzi A, Ferrari S, Iacono O, Limoli A, Bouslenko Z, Natalini D, Conti S, Mantovani M, Tramonte S, Donzelli A, Serravalle E. SARS-CoV-2-The Role of Natural Immunity: A Narrative Review. J Clin Med 2022; 11:6272. [PMID: 36362500 PMCID: PMC9655392 DOI: 10.3390/jcm11216272] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 10/17/2022] [Accepted: 10/20/2022] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Both natural immunity and vaccine-induced immunity to COVID-19 may be useful to reduce the mortality/morbidity of this disease, but still a lot of controversy exists. AIMS This narrative review analyzes the literature regarding these two immunitary processes and more specifically: (a) the duration of natural immunity; (b) cellular immunity; (c) cross-reactivity; (d) the duration of post-vaccination immune protection; (e) the probability of reinfection and its clinical manifestations in the recovered patients; (f) the comparisons between vaccinated and unvaccinated as to the possible reinfections; (g) the role of hybrid immunity; (h) the effectiveness of natural and vaccine-induced immunity against Omicron variant; (i) the comparative incidence of adverse effects after vaccination in recovered individuals vs. COVID-19-naïve subjects. MATERIAL AND METHODS through multiple search engines we investigated COVID-19 literature related to the aims of the review, published since April 2020 through July 2022, including also the previous articles pertinent to the investigated topics. RESULTS nearly 900 studies were collected, and 246 pertinent articles were included. It was highlighted that the vast majority of the individuals after suffering from COVID-19 develop a natural immunity both of cell-mediated and humoral type, which is effective over time and provides protection against both reinfection and serious illness. Vaccine-induced immunity was shown to decay faster than natural immunity. In general, the severity of the symptoms of reinfection is significantly lower than in the primary infection, with a lower degree of hospitalizations (0.06%) and an extremely low mortality. CONCLUSIONS this extensive narrative review regarding a vast number of articles highlighted the valuable protection induced by the natural immunity after COVID-19, which seems comparable or superior to the one induced by anti-SARS-CoV-2 vaccination. Consequently, vaccination of the unvaccinated COVID-19-recovered subjects may not be indicated. Further research is needed in order to: (a) measure the durability of immunity over time; (b) evaluate both the impacts of Omicron BA.5 on vaccinated and healed subjects and the role of hybrid immunity.
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Affiliation(s)
- Sara Diani
- School of Musictherapy, Université Européenne Jean Monnet, 35129 Padova, Italy
| | | | | | | | - Oriana Iacono
- Physical Medicine and Rehabilitation Department, Mirandola Hospital, 41037 Mirandola, Italy
| | - Alice Limoli
- ARPAV (Regional Agency for the Environment Protection), 31100 Treviso, Italy
| | - Zoe Bouslenko
- Cardiology Department, Valdese Hospital, 10100 Torino, Italy
| | | | | | | | - Silvano Tramonte
- Environment and Health Commission, National Bioarchitecture Institute, 20121 Milano, Italy
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Matsuba I, Takuma T, Hatori N, Takai M, Watanabe Y, Takada N, Kishi S, Matsuzawa Y, Nishikawa T, Kunishima T, Degawa H, Nishikawa M, Ono Y, Miyakawa M, Hatori Y, Kanamori A. The Proportion of Long-term Response to Anti-N IgG Antibody after 12 Months for COVID-19 Subclinical Infections and a Longitudinal Survey for COVID-19 Subclinical Infections in 2021. Intern Med 2022; 61:3053-3062. [PMID: 35945024 PMCID: PMC9646357 DOI: 10.2169/internalmedicine.9628-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Objective To examine the continuation of antibody prevalence status after 12 months and background factors in antibody-positive subjects following asymptomatic infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods We initially determined the SARS-CoV-2 anti-nucleocapsid protein immunoglobulin G (anti-N IgG) antibody prevalence in 1,603 patients, doctors, and nurses at 65 medical institutions in Kanagawa Prefecture, Japan. We then obtained consent from 33 of the 39 subjects who tested positive and performed follow-up for 12 months. Results Follow-up for up to 12 months showed that a long-term response of the anti-N IgG antibody could be detected in 6 of the 33 participants (18.2%). The proportions with hypertension, using an angiotensin-receptor blocker, and without a drinking habit were higher among the participants with a long-term anti-N IgG antibody response for up to 12 months than among those without a long-term antibody response. Conclusions The proportion of individuals with subclinical COVID-19 who continuously had a positive result for the anti-N IgG antibody at 12 months was low.
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Suljič A, Sočan M, Mrzel M, Lunar MM, Korva M, Štorman A, Prosenc K, Janežič S, Žohar-Čretnik T, Zupanič T, Poljak M, Avšič-Županc T. Milder outcomes of SARS-CoV-2 genetically confirmed reinfections compared to primary infections with the delta variant: A retrospective case-control study. Front Med (Lausanne) 2022; 9:962653. [PMID: 36275814 PMCID: PMC9582599 DOI: 10.3389/fmed.2022.962653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/13/2022] [Indexed: 11/29/2022] Open
Abstract
Background SARS-CoV-2 infection does not confer long immunity. However, studies suggest that prior infection is associated with lower risk of reinfection and milder outcomes of recurrent infections. The aims of this retrospective observational case-control study were to describe the clinical and molecular characteristics of genetically confirmed Delta reinfection cases and to assess the potential protective role of preceding infection on the severity of reinfection. Methods We used next generation sequencing (NGS) to explore if cases with two positive real time RT-PCR tests > 90 days apart were infected with a different SARS-CoV-2 variant. Cases with confirmed reinfection between August 1st and October 31st, 2021 (the Delta wave) in Slovenia were matched 1:4 by age, sex and timeframe (week of positive test) with individuals with primary infection. Sociodemographic and epidemiologic data, vaccination status, and data on hospitalization and outcome of infection were retrieved from several centralized and standardized national databases. Additional epidemiologic surveys were performed on a limited number of cases and controls. Results We identified 628 cases of genetically confirmed reinfection during the study period and matched them with 2,512 control subjects with Delta primary infection. Primary infections in individuals with reinfection were mainly caused by B.1.258.17 (51.1%), followed by B.1.1.7 (15.1%) and reinfection was detected on average 271 days after primary infection (range 101–477 days). Our results show a substantially lower probability of hospitalization in cases with reinfection compared with controls (OR: 0.21, p = 0.017), but no significant difference was observed in intensive care unit admission and deaths. We observed a significantly lower proportion of vaccinated individuals among cases compared to controls (4.5% vs. 28.2%), suggesting that hybrid immunity leads to lower probability of reinfection. Detailed analysis of the temporal distribution of variants, responsible for reinfections, showed no significant differences in reinfection potential. Conclusion Reinfection with the SARS-CoV-2 Delta variant resulted in fewer hospitalizations compared to the primary Delta infection, suggesting that primary infection may, to some extent, produce at least short lasting protective immunity. This study provides additional insight into the reinfection dynamics that may allow appropriate public health measures to be taken in subsequent waves of the COVID-19 pandemic.
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Affiliation(s)
- Alen Suljič
- Faculty of Medicine, Institute of Microbiology and Immunology, University of Ljubljana, Ljubljana, Slovenia
| | - Maja Sočan
- National Institute of Public Health, Ljubljana, Slovenia,*Correspondence: Maja Sočan,
| | - Maja Mrzel
- National Institute of Public Health, Ljubljana, Slovenia
| | - Maja M. Lunar
- Faculty of Medicine, Institute of Microbiology and Immunology, University of Ljubljana, Ljubljana, Slovenia
| | - Miša Korva
- Faculty of Medicine, Institute of Microbiology and Immunology, University of Ljubljana, Ljubljana, Slovenia
| | - Alenka Štorman
- National Laboratory of Health, Environment, and Food, Maribor, Slovenia
| | - Katarina Prosenc
- National Laboratory of Health, Environment, and Food, Maribor, Slovenia
| | - Sandra Janežič
- National Laboratory of Health, Environment, and Food, Maribor, Slovenia
| | | | - Tina Zupanič
- National Institute of Public Health, Ljubljana, Slovenia
| | - Mario Poljak
- Faculty of Medicine, Institute of Microbiology and Immunology, University of Ljubljana, Ljubljana, Slovenia
| | - Tatjana Avšič-Županc
- Faculty of Medicine, Institute of Microbiology and Immunology, University of Ljubljana, Ljubljana, Slovenia
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Brasu N, Elia I, Russo V, Montacchiesi G, Stabile SA, De Intinis C, Fesi F, Gizzi K, Macagno M, Montone M, Mussolin B, Grifoni A, Faravelli S, Marchese S, Forneris F, De Francesco R, Sette A, Barnaba V, Sottile A, Sapino A, Pace L. Memory CD8 + T cell diversity and B cell responses correlate with protection against SARS-CoV-2 following mRNA vaccination. Nat Immunol 2022; 23:1445-1456. [PMID: 36138186 DOI: 10.1038/s41590-022-01313-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 08/10/2022] [Indexed: 02/04/2023]
Abstract
Understanding immune responses to SARS-CoV-2 messenger RNA (mRNA) vaccines is of great interest, principally because of the poor knowledge about the mechanisms of protection. In the present study, we analyzed longitudinally B cell and T cell memory programs against the spike (S) protein derived from ancestral SARS-CoV-2 (Wuhan-1), B.1.351 (beta), B.1.617.2 (delta) and B.1.1.529 (omicron) variants of concern (VOCs) after immunization with an mRNA-based vaccine (Pfizer). According to the magnitude of humoral responses 3 months after the first dose, we identified high and low responders. Opposite to low responders, high responders were characterized by enhanced antibody-neutralizing activity, increased frequency of central memory T cells and durable S-specific CD8+ T cell responses. Reduced binding antibodies titers combined with long-term specific memory T cells that had distinct polyreactive properties were found associated with subsequent breakthrough with VOCs in low responders. These results have important implications for the design of new vaccines and new strategies for booster follow-up.
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Affiliation(s)
- Nadia Brasu
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Department of Oncology, University of Turin, Turin, Italy
| | - Ines Elia
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | - Valentina Russo
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Department of Oncology, University of Turin, Turin, Italy
| | - Gaia Montacchiesi
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Department of Oncology, University of Turin, Turin, Italy
| | - Simona Aversano Stabile
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | - Carlo De Intinis
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | - Francesco Fesi
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | - Katiuscia Gizzi
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy.,Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | - Marco Macagno
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | - Monica Montone
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy
| | | | - Alba Grifoni
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Silvia Faravelli
- Armenise-Harvard Lab. of Structural Biology Dept. Biology and Biotechnology, University of Pavia, Pavia, Italy
| | - Silvia Marchese
- Istituto Nazionale Genetica Molecolare 'Romeo ed Enrica Invernizzi', Milan, Italy
| | - Federico Forneris
- Armenise-Harvard Lab. of Structural Biology Dept. Biology and Biotechnology, University of Pavia, Pavia, Italy
| | - Raffaele De Francesco
- Istituto Nazionale Genetica Molecolare 'Romeo ed Enrica Invernizzi', Milan, Italy.,Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA.,Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Vincenzo Barnaba
- Pasteur Institute Italy-Fondazione Cenci Bolognetti, Rome, Italy.,Departement Scienze Cliniche, Interistiche, Anestesiologiche e Cardiovascolari, Sapienza University, Rome, Italy
| | | | - Anna Sapino
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy.,Department of Medical Sciences, University of Turin, Turin, Italy
| | - Luigia Pace
- G. Armenise-Harvard Immune Regulation Unit, IIGM, Candiolo, TO, Italy. .,Candiolo Cancer Institute, FPO-IRCCS, Candiolo, TO, Italy.
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Wei X, Rong N, Liu J. Prospects of animal models and their application in studies on adaptive immunity to SARS-CoV-2. Front Immunol 2022; 13:993754. [PMID: 36189203 PMCID: PMC9523127 DOI: 10.3389/fimmu.2022.993754] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/05/2022] [Indexed: 01/08/2023] Open
Abstract
The adaptive immune response induced by SARS-CoV-2 plays a key role in the antiviral process and can protect the body from the threat of infection for a certain period of time. However, owing to the limitations of clinical studies, the antiviral mechanisms, protective thresholds, and persistence of the immune memory of adaptive immune responses remain unclear. This review summarizes existing research models for SARS-CoV-2 and elaborates on the advantages of animal models in simulating the clinical symptoms of COVID-19 in humans. In addition, we systematically summarize the research progress on the SARS-CoV-2 adaptive immune response and the remaining key issues, as well as the application and prospects of animal models in this field. This paper provides direction for in-depth analysis of the anti-SARS-CoV-2 mechanism of the adaptive immune response and lays the foundation for the development and application of vaccines and drugs.
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Affiliation(s)
- Xiaohui Wei
- National Health Commission Key Laboratory of Human Disease Comparative Medicine, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
| | | | - Jiangning Liu
- National Health Commission Key Laboratory of Human Disease Comparative Medicine, Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China
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Marinov GK, Mladenov M, Rangachev A, Alexiev I. SARS-CoV-2 reinfections during the first three major COVID-19 waves in Bulgaria. PLoS One 2022; 17:e0274509. [PMID: 36084070 PMCID: PMC9462809 DOI: 10.1371/journal.pone.0274509] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/30/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The COVID-19 pandemic has had a devastating impact on the world over the past two years (2020-2021). One of the key questions about its future trajectory is the protection from subsequent infections and disease conferred by a previous infection, as the SARS-CoV-2 virus belongs to the coronaviruses, a group of viruses the members of which are known for their ability to reinfect convalescent individuals. Bulgaria, with high rates of previous infections combined with low vaccination rates and an elderly population, presents a somewhat unique context to study this question. METHODS We use detailed governmental data on registered COVID-19 cases to evaluate the incidence and outcomes of COVID-19 reinfections in Bulgaria in the period between March 2020 and early December 2021. RESULTS For the period analyzed, a total of 4,106 cases of individuals infected more than once were observed, including 31 cases of three infections and one of four infections. The number of reinfections increased dramatically during the Delta variant-driven wave of the pandemic towards the end of 2021. We observe a moderate reduction of severe outcomes (hospitalization and death) in reinfections relative to primary infections, and a more substantial reduction of severe outcomes in breakthrough infections in vaccinated individuals. CONCLUSIONS In the available datasets from Bulgaria, prior infection appears to provide some protection from severe outcomes, but to a lower degree than the reduction in severity of breakthrough infections in the vaccinated compared to primary infections in the unvaccinated.
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Affiliation(s)
- Georgi K. Marinov
- Department of Genetics, Stanford University, Stanford, CA, United States of America
| | | | - Antoni Rangachev
- Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria
- International Center for Mathematical Sciences-Sofia, Sofia, Bulgaria
| | - Ivailo Alexiev
- National Center of Infectious and Parasitic Diseases, Sofia, Bulgaria
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Guevara R, Prado-Vivar B, Márquez S, Muñoz EB, Carvajal M, Guadalupe JJ, Becerra-Wong M, Proaño S, Bayas-Rea R, Coloma J, Grunauer M, Trueba G, Rojas-Silva P, Barragán V, Cárdenas P. Occurrence of SARS-CoV-2 reinfections at regular intervals in Ecuador. Front Cell Infect Microbiol 2022; 12:951383. [PMID: 36164552 PMCID: PMC9507970 DOI: 10.3389/fcimb.2022.951383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
SARS-CoV-2 reinfection is defined as a new infection with a different virus variant in an individual who has already recovered from a previous episode of COVID-19. The first case of reinfection in the world was described in August 2020, since then, reinfections have increased over time and their incidence has fluctuated with specific SARS-CoV-2 variant waves. Initially, reinfections were estimated to represent less than 1% of total COVID-19 infections. With the advent of the Omicron variant, reinfections became more frequent, representing up to 10% of cases (based on data from developed countries). The frequency of reinfections in Latin America has been scarcely reported. The current study shows that in Ecuador, the frequency of reinfections has increased 10-fold following the introduction of Omicron, after 22 months of surveillance in a single center of COVID-19 diagnostics. Suspected reinfections were identified retrospectively from a database of RT-qPCR-positive patients. Cases were confirmed by sequencing viral genomes from the first and second infections using the ONT MinION platform. Monthly surveillance showed that the main incidence peaks of reinfections were reached within four to five months, coinciding with the increase of COVID-19 cases in the country, suggesting that the emergence of reinfections is related to higher exposure to the virus during outbreaks. This study performed the longest monitoring of SARS-CoV-2 reinfections, showing an occurrence at regular intervals of 4-5 months and confirming a greater propensity of Omicron to cause reinfections.
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Affiliation(s)
- Rommel Guevara
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Belén Prado-Vivar
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Sully Márquez
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Erika B. Muñoz
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Mateo Carvajal
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Juan José Guadalupe
- Laboratorio de Biotecnología Vegetal, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Mónica Becerra-Wong
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Stefanie Proaño
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Rosa Bayas-Rea
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Josefina Coloma
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California Berkeley, Berkeley, CA, United States
| | - Michelle Grunauer
- Escuela de Medicina, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Gabriel Trueba
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Patricio Rojas-Silva
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Verónica Barragán
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Paúl Cárdenas
- Instituto de Microbiología, Universidad San Francisco de Quito USFQ, Quito, Ecuador
- *Correspondence: Paúl Cárdenas,
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Zaqout A, Almaslamani MA, Chemaitelly H, Hashim SA, Ittaman A, Alimam A, Rustom F, Daghfal J, Abukhattab M, AlMukdad S, Kaleeckal AH, Latif AN, Butt AA, Bertollini R, Al-Khal A, Omrani AS, Abu-Raddad LJ. Effectiveness of the neutralizing antibody sotrovimab among high-risk patients with mild to moderate SARS-CoV-2 in Qatar. Int J Infect Dis 2022; 124:96-103. [PMID: 36218031 PMCID: PMC9484101 DOI: 10.1016/j.ijid.2022.09.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/30/2022] [Accepted: 09/14/2022] [Indexed: 10/31/2022] Open
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Goldblatt D, Alter G, Crotty S, Plotkin SA. Correlates of protection against SARS-CoV-2 infection and COVID-19 disease. Immunol Rev 2022; 310:6-26. [PMID: 35661178 PMCID: PMC9348242 DOI: 10.1111/imr.13091] [Citation(s) in RCA: 123] [Impact Index Per Article: 61.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Antibodies against epitopes in S1 give the most accurate CoP against infection by the SARS-CoV-2 coronavirus. Measurement of those antibodies by neutralization or binding assays both have predictive value, with binding antibody titers giving the highest statistical correlation. However, the protective functions of antibodies are multiple. Antibodies with multiple functions other than neutralization influence efficacy. The role of cellular responses can be discerned with respect to CD4+ T cells and their augmentation of antibodies, and with respect to CD8+ cells with regard to control of viral replication, particularly in the presence of insufficient antibody. More information is needed on mucosal responses.
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Affiliation(s)
- David Goldblatt
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | - Galit Alter
- Massachusetts General HospitalRagon Institute of MGH, MIT and HarvardCambridgeMassachusettsUSA
| | - Shane Crotty
- Center for Infectious Disease and Vaccine ResearchLa Jolla Institute for Immunology (LJI)La JollaCaliforniaUSA
- Department of Medicine, Division of Infectious Diseases and Global Public HealthUniversity of California San Diego (UCSD)La JollaCaliforniaUSA
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Sette A, Crotty S. Immunological memory to SARS-CoV-2 infection and COVID-19 vaccines. Immunol Rev 2022; 310:27-46. [PMID: 35733376 PMCID: PMC9349657 DOI: 10.1111/imr.13089] [Citation(s) in RCA: 121] [Impact Index Per Article: 60.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 05/04/2022] [Indexed: 12/12/2022]
Abstract
Immunological memory is the basis of protective immunity provided by vaccines and previous infections. Immunological memory can develop from multiple branches of the adaptive immune system, including CD4 T cells, CD8 T cells, B cells, and long-lasting antibody responses. Extraordinary progress has been made in understanding memory to SARS-CoV-2 infection and COVID-19 vaccines, addressing development; quantitative and qualitative features of different cellular and anatomical compartments; and durability of each cellular component and antibodies. Given the sophistication of the measurements; the size of the human studies; the use of longitudinal samples and cross-sectional studies; and head-to-head comparisons between infection and vaccines or between multiple vaccines, the understanding of immune memory for 1 year to SARS-CoV-2 infection and vaccines already supersedes that of any other acute infectious disease. This knowledge may help inform public policies regarding COVID-19 and COVID-19 vaccines, as well as the scientific development of future vaccines against SARS-CoV-2 and other diseases.
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Affiliation(s)
- Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego (UCSD), La Jolla, CA 92037, USA
| | - Shane Crotty
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego (UCSD), La Jolla, CA 92037, USA
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IgG antibodies to SARS-CoV-2 in asymptomatic blood donors at two time points in Karachi. PLoS One 2022; 17:e0271259. [PMID: 36001587 PMCID: PMC9401161 DOI: 10.1371/journal.pone.0271259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 06/28/2022] [Indexed: 01/08/2023] Open
Abstract
Introduction An estimated 1.5 million cases were reported in Pakistan until 23 March, 2022. However, SARS-CoV-2 PCR testing capacity has been limited and the incidence of COVID-19 infections is unknown. Volunteer healthy blood donors can be a control population for assessment of SARS-CoV-2 exposure in the population. We determined COVID-19 seroprevalence during the second pandemic wave in Karachi in donors without known infections or symptoms in 4 weeks prior to enrollment. Materials and methods We enrolled 558 healthy blood donors at the Aga Khan University Hospital between December 2020 and February 2021. ABO blood groups were determined. Serum IgG reactivity were measured to spike and receptor binding domain (RBD) proteins. Results Study subjects were predominantly males (99.1%) with a mean age of 29.0±7.4 years. Blood groups were represented by; B (35.8%), O (33.3%), A (23.8%) and AB (7%). Positive IgG responses to spike were detected in 53.4% (95% CI, 49.3–37.5) of blood donors. Positive IgG antibodies to RBD were present in 16.7% (95% CI; 13.6–19.8) of individuals. No significant difference was found between the frequency of IgG antibodies to spike or RBD across age groups. Frequencies of IgG to Spike and RBD antibodies between December 2020 and February 2021 were found to be similar. Seropositivity to either antigen between individuals of different blood groups did not differ. Notably, 31.2% of individuals with IgG antibodies to spike also had IgG antibodies to RBD. Amongst donors who had previously confirmed COVID-19 and were seropositive to spike, 40% had IgG to RBD. Conclusions Our study provides insights into the seroprevalence of antibodies to COVID-19 in a healthy cohort in Karachi. The differential dynamics of IgG to spike and RBD likely represent both exposure to SARS-CoV-2 and associate with protective immunity in the population.
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Idoko OT, Usuf E, Okomo U, Wonodi C, Jambo K, Kampmann B, Madhi S, Adetifa I. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Africa: Current Considerations and Future Projections. Clin Infect Dis 2022; 75:S136-S140. [PMID: 35749696 PMCID: PMC9376270 DOI: 10.1093/cid/ciac401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Indexed: 01/19/2023] Open
Abstract
The burden of severe Covid-19 has been relatively low in sib-Saharan Africa compared to Europe and the Americas. However, SARS-CoV-2 sero-prevalence data has demonstrated that there has been more widespread transmission than can be deduced from reported cases. This could be attributed to under reporting due to low testing capacity or high numbers of asymptomatic SARS-CoV-2 infection in communities. Recent data indicates that prior SARS-CoV-2 exposure is protective against reinfection and that vaccination of previously SARS-CoV-2 infected individuals induces robust cross-reactive antibody responses. Considering these data, calls for a need for a re-think of the COVID-19 vaccination strategy in sub-Saharan African settings with high SARSCoV-2 population exposure but limited available vaccine doses. A potential recommendation would be to prioritize rapid and widespread vaccination of the first dose, while waiting for more vaccines to become available.
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Affiliation(s)
- Olubukola T Idoko
- Faculty of Infectious and Tropical disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Effua Usuf
- Faculty of Infectious and Tropical disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Uduak Okomo
- Faculty of Infectious and Tropical disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Chizoba Wonodi
- International Health, Health Systems Center, John Hopkins University, Baltimore, USA
| | - Kondwani Jambo
- Viral Immunology Research Group, Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
| | - Beate Kampmann
- Faculty of Infectious and Tropical disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Shabir Madhi
- South African Medical Research Council Vaccines and Infectious Diseases Analytics Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ifedayo Adetifa
- Faculty of Infectious and Tropical disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
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Isnaini N, Mardian Y, Lokida D, Budiono F, Butar-Butar DP, Arlinda D, Salim G, Kosasih H, Wulan WN, Perodin J, Neal A, Lane HC, Karyana M. Mild reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant: First case report from Indonesia. Front Med (Lausanne) 2022; 9:906469. [PMID: 35935779 PMCID: PMC9355687 DOI: 10.3389/fmed.2022.906469] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/27/2022] [Indexed: 12/21/2022] Open
Abstract
Background Reinfection with SARS-CoV-2 has been well documented, yet little is known about the degree of protection a previous infection provides against reinfection, especially against Variants of Concern (VOC). Case presentation Here we describe a case of an unvaccinated 49-year-old man who experienced two sequential SARS-CoV-2 infections with two different variants, as evidenced by genomic sequencing. The first episode was caused by the Pango lineage B.1.466.2 and resulted in severe COVID-19 with 5 days in an intensive care unit (ICU). The second episode occurred approximately 6 months later, during the Delta surge in Indonesia. Genomic analysis showed that the second infection was caused by the Delta variant (Pango lineage B.1.617.2) and resulted in mild disease that did not require hospitalization. No SARS-CoV-2 nucleic acid was detected between the two episodes, but both binding and neutralizing antibodies to SARS-CoV-2 were detected prior to the reinfection, with the second infection leading to an increase in the levels of antibody. Conclusion We confirmed that the patient experienced a reinfection instead of persistent viral shedding from the first infection based on epidemiological, clinical, serological, and genomic analyses. Our case supports the hypothesis that SARS-CoV-2 reinfection may occur once antibody titers decrease or following the emergence of a new variant. The milder presentation in the patient’s second infection deserves further investigation to provide a clear picture of the role of post-infection immunity in altering the course of subsequent disease.
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Affiliation(s)
| | - Yan Mardian
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Dewi Lokida
- Tangerang District Hospital, Tangerang, Indonesia.,Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | | | - Deni P Butar-Butar
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Dona Arlinda
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia.,National Institute of Health Research and Development, Ministry of Health, Jakarta, Indonesia
| | - Gustiani Salim
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Herman Kosasih
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Wahyu Nawang Wulan
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | | | - Aaron Neal
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - H Clifford Lane
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Muhammad Karyana
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia.,National Institute of Health Research and Development, Ministry of Health, Jakarta, Indonesia
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44
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Protection of Omicron sub-lineage infection against reinfection with another Omicron sub-lineage. Nat Commun 2022; 13:4675. [PMID: 35945213 PMCID: PMC9362989 DOI: 10.1038/s41467-022-32363-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/26/2022] [Indexed: 12/22/2022] Open
Abstract
There is significant genetic distance between SARS-CoV-2 Omicron (B.1.1.529) variant BA.1 and BA.2 sub-lineages. This study investigates immune protection of infection with one sub-lineage against reinfection with the other sub-lineage in Qatar during a large BA.1 and BA.2 Omicron wave, from December 19, 2021 to March 21, 2022. Two national matched, retrospective cohort studies are conducted to estimate effectiveness of BA.1 infection against reinfection with BA.2 (N = 20,994; BA.1-against-BA.2 study), and effectiveness of BA.2 infection against reinfection with BA.1 (N = 110,315; BA.2-against-BA.1 study). Associations are estimated using Cox proportional-hazards regression models after multiple imputation to assign a sub-lineage status for cases with no sub-lineage status (using probabilities based on the test date). Effectiveness of BA.1 infection against reinfection with BA.2 is estimated at 94.2% (95% CI: 89.2-96.9%). Effectiveness of BA.2 infection against reinfection with BA.1 is estimated at 80.9% (95% CI: 73.1-86.4%). Infection with the BA.1 sub-lineage appears to induce strong, but not full immune protection against reinfection with the BA.2 sub-lineage, and vice versa, for at least several weeks after the initial infection.
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45
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Nguyen DC, Lamothe PA, Woodruff MC, Saini AS, Faliti CE, Sanz I, Lee FE. COVID-19 and plasma cells: Is there long-lived protection? Immunol Rev 2022; 309:40-63. [PMID: 35801537 PMCID: PMC9350162 DOI: 10.1111/imr.13115] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Infection with SARS-CoV-2, the etiology of the ongoing COVID-19 pandemic, has resulted in over 450 million cases with more than 6 million deaths worldwide, causing global disruptions since early 2020. Memory B cells and durable antibody protection from long-lived plasma cells (LLPC) are the mainstay of most effective vaccines. However, ending the pandemic has been hampered by the lack of long-lived immunity after infection or vaccination. Although immunizations offer protection from severe disease and hospitalization, breakthrough infections still occur, most likely due to new mutant viruses and the overall decline of neutralizing antibodies after 6 months. Here, we review the current knowledge of B cells, from extrafollicular to memory populations, with a focus on distinct plasma cell subsets, such as early-minted blood antibody-secreting cells and the bone marrow LLPC, and how these humoral compartments contribute to protection after SARS-CoV-2 infection and immunization.
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Affiliation(s)
- Doan C. Nguyen
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
| | - Pedro A. Lamothe
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
| | - Matthew C. Woodruff
- Division of Rheumatology, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
- Emory Autoimmunity Center of ExcellenceEmory UniversityAtlantaGeorgiaUSA
- Lowance Center for Human ImmunologyEmory UniversityAtlantaGeorgiaUSA
| | - Ankur S. Saini
- Division of Rheumatology, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
- Emory Autoimmunity Center of ExcellenceEmory UniversityAtlantaGeorgiaUSA
- Lowance Center for Human ImmunologyEmory UniversityAtlantaGeorgiaUSA
| | - Caterina E. Faliti
- Division of Rheumatology, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
- Lowance Center for Human ImmunologyEmory UniversityAtlantaGeorgiaUSA
| | - Ignacio Sanz
- Division of Rheumatology, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
- Emory Autoimmunity Center of ExcellenceEmory UniversityAtlantaGeorgiaUSA
- Lowance Center for Human ImmunologyEmory UniversityAtlantaGeorgiaUSA
| | - Frances Eun‐Hyung Lee
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of MedicineEmory UniversityAtlantaGeorgiaUSA
- Lowance Center for Human ImmunologyEmory UniversityAtlantaGeorgiaUSA
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46
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Abu-Raddad LJ, Dargham S, Chemaitelly H, Coyle P, Al Kanaani Z, Al Kuwari E, Butt AA, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Abdul Rahim HF, Nasrallah GK, Yassine HM, Al Kuwari MG, Al Romaihi HE, Al-Thani MH, Al Khal A, Bertollini R. COVID-19 risk score as a public health tool to guide targeted testing: A demonstration study in Qatar. PLoS One 2022; 17:e0271324. [PMID: 35853026 PMCID: PMC9295939 DOI: 10.1371/journal.pone.0271324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 06/28/2022] [Indexed: 11/18/2022] Open
Abstract
We developed a Coronavirus Disease 2019 (COVID-19) risk score to guide targeted RT-PCR testing in Qatar. The Qatar national COVID-19 testing database, encompassing a total of 2,688,232 RT-PCR tests conducted between February 5, 2020-January 27, 2021, was analyzed. Logistic regression analyses were implemented to derive the COVID-19 risk score, as a tool to identify those at highest risk of having the infection. Score cut-off was determined using the ROC curve based on maximum sum of sensitivity and specificity. The score’s performance diagnostics were assessed. Logistic regression analysis identified age, sex, and nationality as significant predictors of infection and were included in the risk score. The ROC curve was generated and the area under the curve was estimated at 0.63 (95% CI: 0.63–0.63). The score had a sensitivity of 59.4% (95% CI: 59.1%-59.7%), specificity of 61.1% (95% CI: 61.1%-61.2%), a positive predictive value of 10.9% (95% CI: 10.8%-10.9%), and a negative predictive value of 94.9% (94.9%-95.0%). The concept and utility of a COVID-19 risk score were demonstrated in Qatar. Such a public health tool can have considerable utility in optimizing testing and suppressing infection transmission, while maximizing efficiency and use of available resources.
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Affiliation(s)
- Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, United States of America
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Soha Dargham
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, United States of America
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar
- Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
| | | | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, United States of America
- Hamad Medical Corporation, Doha, Qatar
| | | | | | | | | | | | - Gheyath K Nasrallah
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hadi M Yassine
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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47
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Rosenberg M, Chen C, Golzarri-Arroyo L, Carroll A, Menachemi N, Ludema C. SARS-CoV-2 reinfections in a US university setting, Fall 2020 to Spring 2021. BMC Infect Dis 2022; 22:592. [PMID: 35787250 PMCID: PMC9252534 DOI: 10.1186/s12879-022-07578-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 06/23/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND SARS-CoV-2 reinfections are a public health concern because of the potential for transmission and clinical disease, and because of our limited understanding of whether and how well an infection confers protection against subsequent infections. Despite the public health importance, few studies have reported rigorous estimates of reinfection risk. METHODS Leveraging Indiana University's comprehensive testing program to identify both asymptomatic and symptomatic SARS-CoV-2 cases, we estimated the incidence of SARS-CoV-2 reinfection among students, faculty, and staff across the 2020-2021 academic year. We contextualized the reinfection data with information on key covariates: age, sex, Greek organization membership, student vs faculty/staff affiliation, and testing type. RESULTS Among 12,272 people with primary infections, we found a low level of SARS-CoV-2 reinfections (0.6%; 0.4 per 10,000 person-days). We observed higher risk for SARS-CoV-2 reinfections in Greek-affiliated students. CONCLUSIONS We found evidence for low levels of SARS-CoV-2 reinfection in a large multi-campus university population during a time-period prior to widespread COVID-19 vaccination.
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Affiliation(s)
- Molly Rosenberg
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E. 7th St., Bloomington, IN, 47405, USA.
| | - Chen Chen
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E. 7th St., Bloomington, IN, 47405, USA
| | - Lilian Golzarri-Arroyo
- Biostatistics Consulting Center, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
| | - Aaron Carroll
- Pediatric and Adolescent Comparative Effectiveness Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Nir Menachemi
- Department of Health Policy and Management, Indiana University Fairbanks School of Public Health at IUPUI, Indianapolis, IN, USA
| | - Christina Ludema
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, 1025 E. 7th St., Bloomington, IN, 47405, USA
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Chivese T, Matizanadzo JT, Musa OAH, Hindy G, Furuya-Kanamori L, Islam N, Al-Shebly R, Shalaby R, Habibullah M, Al-Marwani TA, Hourani RF, Nawaz AD, Haider MZ, Emara MM, Cyprian F, Doi SAR. The prevalence of adaptive immunity to COVID-19 and reinfection after recovery - a comprehensive systematic review and meta-analysis. Pathog Glob Health 2022; 116:269-281. [PMID: 35099367 PMCID: PMC9248963 DOI: 10.1080/20477724.2022.2029301] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
This study aims to estimate the prevalence and longevity of detectable SARS-CoV-2 antibodies and T and B memory cells after recovery. In addition, the prevalence of COVID-19 reinfection and the preventive efficacy of previous infection with SARS-CoV-2 were investigated. A synthesis of existing research was conducted. The Cochrane Library, the China Academic Journals Full Text Database, PubMed, and Scopus, and preprint servers were searched for studies conducted between 1 January 2020 to 1 April 2021. Included studies were assessed for methodological quality and pooled estimates of relevant outcomes were obtained in a meta-analysis using a bias adjusted synthesis method. Proportions were synthesized with the Freeman-Tukey double arcsine transformation and binary outcomes using the odds ratio (OR). Heterogeneity was assessed using the I2 and Cochran's Q statistics and publication bias was assessed using Doi plots. Fifty-four studies from 18 countries, with around 12,000,000 individuals, followed up to 8 months after recovery, were included. At 6-8 months after recovery, the prevalence of SARS-CoV-2 specific immunological memory remained high; IgG - 90.4% (95%CI 72.2-99.9, I2 = 89.0%), CD4+ - 91.7% (95%CI 78.2-97.1y), and memory B cells 80.6% (95%CI 65.0-90.2) and the pooled prevalence of reinfection was 0.2% (95%CI 0.0-0.7, I2 = 98.8). Individuals previously infected with SARS-CoV-2 had an 81% reduction in odds of a reinfection (OR 0.19, 95% CI 0.1-0.3, I2 = 90.5%). Around 90% of recovered individuals had evidence of immunological memory to SARS-CoV-2, at 6-8 months after recovery and had a low risk of reinfection.RegistrationPROSPERO: CRD42020201234.
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Affiliation(s)
- Tawanda Chivese
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar,CONTACT Tawanda Chivese ; Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Joshua T. Matizanadzo
- Department of Public Health and Primary Care, Brighton and Sussex Medical School, UK
| | - Omran A. H. Musa
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - George Hindy
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Luis Furuya-Kanamori
- UQ Centre for Clinical Research, The University of Queensland, Herston, Australia
| | - Nazmul Islam
- Department of Public Health, Qu Health, Qatar University, Doha, Qatar
| | - Rafal Al-Shebly
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Rana Shalaby
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Mohammad Habibullah
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Talal A. Al-Marwani
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Rizeq F. Hourani
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Ahmed D. Nawaz
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Mohammad Z. Haider
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Mohamed M. Emara
- Immunology Section, Basic Medical Sciences Department, College of Medicine, Qu Health, Qatar University, Doha, Qatar,Microbiology Section, Biomedical and Pharmaceutical Research Unit, Qu Health, Qatar University, Doha, Qatar
| | - Farhan Cyprian
- Immunology Section, Basic Medical Sciences Department, College of Medicine, Qu Health, Qatar University, Doha, Qatar
| | - Suhail A. R. Doi
- Department of Population Medicine, College of Medicine, Qu Health, Qatar University, Doha, Qatar
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49
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van der Vegt SA, Dai L, Bouros I, Farm HJ, Creswell R, Dimdore-Miles O, Cazimoglu I, Bajaj S, Hopkins L, Seiferth D, Cooper F, Lei CL, Gavaghan D, Lambert B. Learning transmission dynamics modelling of COVID-19 using comomodels. Math Biosci 2022; 349:108824. [PMID: 35537550 PMCID: PMC9077823 DOI: 10.1016/j.mbs.2022.108824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 04/11/2022] [Accepted: 04/11/2022] [Indexed: 01/12/2023]
Abstract
The COVID-19 epidemic continues to rage in many parts of the world. In the UK alone, an array of mathematical models have played a prominent role in guiding policymaking. Whilst considerable pedagogical material exists for understanding the basics of transmission dynamics modelling, there is a substantial gap between the relatively simple models used for exposition of the theory and those used in practice to model the transmission dynamics of COVID-19. Understanding these models requires considerable prerequisite knowledge and presents challenges to those new to the field of epidemiological modelling. In this paper, we introduce an open-source R package, comomodels, which can be used to understand the complexities of modelling the transmission dynamics of COVID-19 through a series of differential equation models. Alongside the base package, we describe a host of learning resources, including detailed tutorials and an interactive web-based interface allowing dynamic investigation of the model properties. We then use comomodels to illustrate three key lessons in the transmission of COVID-19 within R Markdown vignettes.
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Affiliation(s)
- Solveig A. van der Vegt
- Doctoral Training Centre, University of Oxford, Oxford, UK,Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK
| | - Liangti Dai
- Doctoral Training Centre, University of Oxford, Oxford, UK,MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Ioana Bouros
- Doctoral Training Centre, University of Oxford, Oxford, UK,Department of Computer Science, University of Oxford, Oxford, UK
| | - Hui Jia Farm
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Richard Creswell
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Oscar Dimdore-Miles
- Atmospheric, Oceanic and Planetary Physics Department, University of Oxford, Oxford, UK
| | - Idil Cazimoglu
- Doctoral Training Centre, University of Oxford, Oxford, UK
| | - Sumali Bajaj
- Doctoral Training Centre, University of Oxford, Oxford, UK
| | - Lyle Hopkins
- Doctoral Training Centre, University of Oxford, Oxford, UK,Department of Computer Science, University of Oxford, Oxford, UK
| | - David Seiferth
- Doctoral Training Centre, University of Oxford, Oxford, UK
| | - Fergus Cooper
- Doctoral Training Centre, University of Oxford, Oxford, UK,Department of Computer Science, University of Oxford, Oxford, UK
| | - Chon Lok Lei
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao Special Administrative Region of China,Department of Biomedical Sciences, Faculty of Health Sciences, University of Macau, Macao Special Administrative Region of China
| | - David Gavaghan
- Doctoral Training Centre, University of Oxford, Oxford, UK,Department of Computer Science, University of Oxford, Oxford, UK
| | - Ben Lambert
- Doctoral Training Centre, University of Oxford, Oxford, UK,Department of Mathematics, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK,Corresponding author
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50
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Wallace S, Hall V, Charlett A, Kirwan PD, Cole M, Gillson N, Atti A, Timeyin J, Foulkes S, Taylor-Kerr A, Andrews N, Shrotri M, Rokadiya S, Oguti B, Vusirikala A, Islam J, Zambon M, Brooks TJG, Ramsay M, Brown CS, Chand M, Hopkins S. Impact of prior SARS-CoV-2 infection and COVID-19 vaccination on the subsequent incidence of COVID-19: a multicentre prospective cohort study among UK healthcare workers - the SIREN (Sarscov2 Immunity & REinfection EvaluatioN) study protocol. BMJ Open 2022; 12:e054336. [PMID: 35768083 PMCID: PMC9240450 DOI: 10.1136/bmjopen-2021-054336] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
INTRODUCTION Understanding the effectiveness and durability of protection against SARS-CoV-2 infection conferred by previous infection and COVID-19 is essential to inform ongoing management of the pandemic. This study aims to determine whether prior SARS-CoV-2 infection or COVID-19 vaccination in healthcare workers protects against future infection. METHODS AND ANALYSIS This is a prospective cohort study design in staff members working in hospitals in the UK. At enrolment, participants are allocated into cohorts, positive or naïve, dependent on their prior SARS-CoV-2 infection status, as measured by standardised SARS-CoV-2 antibody testing on all baseline serum samples and previous SARS-CoV-2 test results. Participants undergo monthly antibody testing and fortnightly viral RNA testing during follow-up and based on these results may move between cohorts. Any results from testing undertaken for other reasons (eg, symptoms, contact tracing) or prior to study entry will also be captured. Individuals complete enrolment and fortnightly questionnaires on exposures, symptoms and vaccination. Follow-up is 12 months from study entry, with an option to extend follow-up to 24 months.The primary outcome of interest is infection with SARS-CoV-2 after previous SARS-CoV-2 infection or COVID-19 vaccination during the study period. Secondary outcomes include incidence and prevalence (both RNA and antibody) of SARS-CoV-2, viral genomics, viral culture, symptom history and antibody/neutralising antibody titres. ETHICS AND DISSEMINATION The study was approved by the Berkshire Research Ethics Committee, Health Research Authority (IRAS ID 284460, REC reference 20/SC/0230) on 22 May 2020; the vaccine amendment was approved on 12 January 2021. Participants gave informed consent before taking part in the study.Regular reports to national and international expert advisory groups and peer-reviewed publications ensure timely dissemination of findings to inform decision making. TRIAL REGISTRATION NUMBER ISRCTN11041050.
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Affiliation(s)
- Sarah Wallace
- National Infection Service, UK Health Security Agency, London, UK
| | - Victoria Hall
- National Infection Service, UK Health Security Agency, London, UK
| | - Andre Charlett
- Statistics, Modelling and Economics Unit, UK Health Security Agency, London, UK
| | - Peter D Kirwan
- National Infection Service, UK Health Security Agency, London, UK
- MRC Biostatistics Unit, Cambridge, UK
| | - Michele Cole
- National Infection Service, UK Health Security Agency, London, UK
| | - Natalie Gillson
- National Infection Service, UK Health Security Agency, London, UK
| | - Ana Atti
- National Infection Service, UK Health Security Agency, London, UK
| | - Jean Timeyin
- National Infection Service, UK Health Security Agency, London, UK
| | - Sarah Foulkes
- National Infection Service, UK Health Security Agency, London, UK
| | | | - Nick Andrews
- Statistics, Modelling and Economics Unit, UK Health Security Agency, London, UK
| | | | - Sakib Rokadiya
- National Infection Service, UK Health Security Agency, London, UK
| | - Blanche Oguti
- National Infection Service, UK Health Security Agency, London, UK
| | | | - Jasmin Islam
- National Infection Service, UK Health Security Agency, London, UK
| | - Maria Zambon
- National Infection Service, UK Health Security Agency, London, UK
| | - Tim J G Brooks
- National Infection Service, UK Health Security Agency, London, UK
| | - Mary Ramsay
- National Infection Service, UK Health Security Agency, London, UK
| | - Colin S Brown
- National Infection Service, UK Health Security Agency, London, UK
| | - Meera Chand
- National Infection Service, UK Health Security Agency, London, UK
| | - Susan Hopkins
- National Infection Service, UK Health Security Agency, London, UK
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