Introduction: There is uncertainty surrounding the diagnosis, prevalence, phenotype, duration and treatment of Long COVID. This study aims to (A) describe the clinical phenotype of post-COVID symptomatology in children and young people (CYP) with laboratory-confirmed SARS-CoV-2 infection compared with test-negative controls, (B) produce an operational definition of Long COVID in CYP, and (C) establish its prevalence in CYP.
Methods And Analysis: A cohort study of SARS-CoV-2-positive CYP aged 11-17 years compared with age, sex and geographically matched SARS-CoV-2 test-negative CYP. CYP aged 11-17 testing positive and negative for SARS-CoV-2 infection will be identified and contacted 3, 6, 12 and 24 months after the test date. Consenting CYP will complete an online questionnaire. We initially planned to recruit 3000 test positives and 3000 test negatives but have since extended our target. Data visualisation techniques will be used to examine trajectories over time for symptoms and variables measured repeatedly, separately by original test status. Summary measures of fatigue and mental health dimensions will be generated using dimension reduction methods such as latent variables/latent class/principal component analysis methods. Cross-tabulation of collected and derived variables against test status and discriminant analysis will help operationalise preliminary definitions of Long COVID.
Ethics And Dissemination: Research Ethics Committee approval granted. Data will be stored in secure Public Health England servers or University College London's Data Safe Haven. Risks of harm will be minimised by providing information on where to seek support. Results will be published on a preprint server followed by journal publication, with reuse of articles under a CC BY licence. Data will be published with protection against identification when there are small frequencies involved.
Trial Registration Number: ISRCTN34804192; Pre-results.
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http://dx.doi.org/10.1136/bmjopen-2021-052838 | DOI Listing |
Hum Immunol
January 2025
Medical University - Sofia, Medical Faculty, Department of Clinical Immunology, Bulgaria; University Hospital Alexandrovska, Clinic of Clinical Immunology and Stem Cell Bank, Bulgaria.
The SARS-CoV-2 outbreak represents a global health problem. The different infection rates are heavily influenced by host genetic factors, such as variability in the HLA region. The aim of our study was to investigate whether certain HLA alleles in the Bulgarian population contribute to COVID-19 progression and their role in anti-SARS-CoV-2 immunity.
View Article and Find Full Text PDFComput Biol Med
January 2025
LMA Laboratory, University of Bejaia, Bejaia 06000, Algeria. Electronic address:
Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM)-based hybrid model for health monitoring and health crisis forecasting. It consists of efficiently retrieving safe content from multiple social media sources.
View Article and Find Full Text PDFNeuropsychopharmacol Rep
March 2025
Molecular Psychoneuroimmunology, Institute for Genetic Medicine, Hokkaido University, Sapporo, Hokkaido, Japan.
COVID-19 exhibits not only respiratory symptoms but also neurological/psychiatric symptoms rarely including delirium/psychosis. Pathological studies on COVID-19 provide evidence that the cytokine storm, in particular (epidermal growth factor) EGF receptor (EGFR, ErbB1, Her1) activation, plays a central role in the progression of viral replication and lung fibrosis. Of note, SARS-CoV-2 virus (specifically, S1 spike domain) mimics EGF and directly transactivates EGFR, preceding the inflammatory process.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Systems Engineering & Operations Research, George Mason University, Fairfax, VA, 22030, USA.
Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.
View Article and Find Full Text PDFNat Genet
January 2025
Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Aberrant immune responses to viral pathogens contribute to pathogenesis, but our understanding of pathological immune responses caused by viruses within the human virome, especially at a population scale, remains limited. We analyzed whole-genome sequencing datasets of 6,321 Japanese individuals, including patients with autoimmune diseases (psoriasis vulgaris, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), pulmonary alveolar proteinosis (PAP) or multiple sclerosis) and coronavirus disease 2019 (COVID-19), or healthy controls. We systematically quantified two constituents of the blood DNA virome, endogenous HHV-6 (eHHV-6) and anellovirus.
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