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Comparison of ORs for swab positivity based on presence or absence of any of 26 symptoms surveyed in N = 1,542,510 participants across five variant-phases of REACT-1 ORs are derived from logistic regression models with swab positive (1/0) as the outcome variable, adjusted for age, sex and vaccination status. Error bars show 95% confidence intervals. ORs are higher for BA.2 than BA.1 for all symptoms. Fever and cough have the highest ORs for BA.2 and BA.1, while loss or change of smell or taste have the highest ORs in all previous variants.
Source publication
Infection with SARS-CoV-2 virus is associated with a wide range of symptoms. The REal-time Assessment of Community Transmission −1 (REACT-1) study monitored the spread and clinical manifestation of SARS-CoV-2 among random samples of the population in England from 1 May 2020 to 31 March 2022. We show changing symptom profiles associated with the dif...
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Background
There is limited information on the role of individuals in different age groups in the spread of infection during the Omicron epidemics, especially ones beyond the winter epidemic wave in 2021-2022. COVID-19 booster vaccination in England during the Autumn 2022 was restricted to persons aged over 50y, and persons in clinical risk groups....
Citations
... It may persist for two or three years, with symptom exacerbations over time, though determining the permanence of symptoms is difficult due to the lack of standardized research methods [6][7][8]. In general, types of LC are defined according to the severity and duration of symptoms [9,10]. Recovery from the acute phase is typically slow, but most symptoms decrease over time and stabilize around 6-8 months after onset. ...
Citation: de Melo, B.P.; da Silva, J.A.M.; Rodrigues, M.A.; Palmeira, J.d.F.; Saldanha de Araujo, F.; Argañaraz, G.A.; Argañaraz, E.R. SARS-CoV-2 Spike Protein and Long COVID-Part 1: Impact of Spike Protein in Pathophysiological Mechanisms of Long COVID Syndrome. Viruses 2025, 17, 617. Abstract: SARS-CoV-2 infection has resulted in more than 700 million cases and nearly 7 million deaths worldwide. Although vaccination efforts have effectively reduced mortality and transmission rates, a significant proportion of recovered patients-up to 40%-develop long COVID syndrome (LC) or post-acute sequelae of COVID-19 infection (PASC). LC is characterized by the persistence or emergence of new symptoms following initial SARS-CoV-2 infection, affecting the cardiovascular, neurological, respiratory, gastrointesti-nal, reproductive, and immune systems. Despite the broad range of clinical symptoms that have been described, the risk factors and pathogenic mechanisms behind LC remain unclear. This review, the first of a two-part series, is distinguished by the discussion of the role of the SARS-CoV-2 spike protein in the primary mechanisms underlying the pathophysiology of LC.
... Delta variant, a more complex disorder was first identified as B.1.617.2 in India in December 2020, quickly became the largely transmissible strain, showing a 66% higher occurrence compared to the Alpha variant in England and exceeding 79% in certain parts of France [27]. The study [28] [29] consisted of 14,296 images accumulated from 120 CT scans for pneumonia, cancer and tuberculosis patients. The model that was distinctive from other models like VGGNet or LeNet was termed as AlexNet and consisted of 5 layers. ...
Pneumonia is an example of a past pandemic and continues to be a serious health concern. In the USA, more than one million people are admitted in hospital with pneumonia every year, leading to about 500,000 deaths. Chest X-ray imaging is an effective and widely utilised method for diagnosing pneumonia and is essential in both healthcare and epidemiological studies. COVID-19, a viral infection initiated in Wuhan, China towards the end of 2019, quickly spread across the globe. It is caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and has influenced millions globally. Analyzing X-ray images is regarded as the fastest and simplest methods for discovery, available at a minimal cost in many places. CT scans, on the other way, are a mere advanced imaging technique that can identify small changes in the composition of internal organs. This method uses 3-D computer technology along with X-rays for a more detailed examination. While both CT scans and X-rays provide images of internal body compositions, traditional X-ray images can sometimes occlude, making it difficult to see fine details. The proposed model outlines a framework for classifying COVID-19 variants and predicting new ones. As per the results, the proposed ResNet_Seg achieved an F1 score of 99.96%, which is higher than the CNN and other models tested. The performance of these models is assessed using datasets from SARS and MERS, resulting in accurate predictions. Future work will focus on validating these models using statistical methods. A relative analysis of deep learning models, including CNN, ResNet, and Darknet, is conducted, with performance enhancements achieved through the novel segmentation algorithm and hyperparameter fine-tuning. The results offer insights into developing more effective and reliable diagnostic methodologies for pneumonia and COVID-19 using deep learning and machine learning techniques.
... Of the sites tested in 2022 (sites 1-3), the strongest wastewater detections at each site were all found during weeks with the most reported COVID-19 cases. At site 1 (the office, Fig 1A), samples were analysed during a period of declining COVID-19 case numbers, after the Omicron BA.1 peak [56]. At this site, employees undertook SARS-CoV-2 tests each day using lateral flow devices. ...
... The exception occurred on a day when a group of external visitors, who were not asked to undergo LFD testing upon arrival, included COVID-19 positive individuals. At site 2 (the charity centre, Fig 1B) samples were analysed during the Omicron BA.2 peak [56] and the three positive wastewater detections are clustered around the same time as the national surveillance peak. Site 3 (the museum, Fig 1C) was sampled during the BA.4 and BA.5 variant outbreak [57] and shows a wastewater SARS-CoV-2 RNA peak with the same timing as national surveillance COVID-19 case numbers. ...
By tracking infectious diseases through sewage, municipal-scale wastewater surveillance has provided early warnings of future COVID-19 hospitalisations, identified biases in diagnostic testing, and is rapidly expanding to a broader array of pathogens. Despite applications in the targeted delivery of local interventions, near-source wastewater surveillance has received less attention and we know little about the near-source time series dynamics of contrasting pathogens. To address this, we conducted wastewater surveillance at five sites for SARS-CoV-2 and two sites for norovirus GI, norovirus GII, influenza A virus, influenza B virus, and human respiratory syncytial virus (RSV A and RSV B). Sites were selected for contrasting functions: an office, charity centre, museum, university, and care home. The key findings are (1) near-source wastewater detections were linked to local events (staff sickness, enhanced cleaning, changing populations); (2) wastewater detections decreased in the order norovirus GII > norovirus GI > SARS-CoV-2 ≈ influenza A ≈ RSV A > influenza B ≈ RSV B; (3) correlation between near-source wastewater data and national surveillance data increases as a function of catchment size and viral prevalence (examples include the SARS-CoV-2 BA.4/BA.5 variant peak at a museum and wastewater tracking the winter norovirus season); (4) strong weekday periodicity in near-source wastewater SARS-CoV-2 detections, with the correlation against COVID-19 case numbers increasing when modelling variable lag times between faecal shedding onset and clinical diagnosis (R² = 0.45 increases to 0.84-0.86); (5) a log-linear relationship between the frequency of wastewater SARS-CoV-2 detection and log(catchment size⋅viral prevalence) (R² = 0.6914-0.9066). Finally, we propose two use cases. Firstly, for rare or high-risk pathogens, near-source wastewater sentinel systems provide early warning of outbreaks, achieving high frequency community coverage without behaviour change and at low cost versus diagnostic testing. Secondly, for endemic pathogens, near-source wastewater reveals long-term patterns and trends, the effectiveness of local policies, and community vulnerabilities.
... Simulation studies showed that these stability approaches generate a substantial increase in selection or clustering performance compared to a single run of the algorithm, and that our consensus score is relevant for the calibration of hyper-parameters (Bodinier et al. 2023a,b). Real-world applications also provided novel and interpretable results in different settings (Elliott et al. 2021;Whitaker et al. 2022;Petrovic et al. 2022;Dagnino et al. 2021). ...
The R package sharp (Stability-enHanced Approaches using Resampling Procedures) provides an integrated framework for stability-enhanced variable selection, graphical modeling and clustering. In stability selection, a feature selection algorithm is combined with a resampling technique to estimate feature selection probabilities. Features with selection proportions above a threshold are considered stably selected. Similarly, a clustering algorithm is applied on multiple subsamples of items to compute co-membership proportions in consensus clustering. The consensus clusters are obtained by clustering using comembership proportions as a measure of similarity. We calibrate the hyper-parameters of stability selection (or consensus clustering) jointly by maximizing a consensus score calculated under the null hypothesis of equiprobability of selection (or co-membership), which characterizes instability. The package offers flexibility in the modeling, includes diagnostic and visualization tools, and allows for parallelization.
... Moreover, our study did not account for potential variations in SARS-CoV-2 strains, which could influence transmission and outcome patterns. Recent study by Whitaker et al. has highlighted the importance of considering variant-specific effects in COVID-19 research (56). Additionally, we did not have data on the timing of SARS-CoV-2 infection during pregnancy, which could potentially influence neonatal outcomes, as suggested by Movahedi et al. and Sahin et al. who found that third-trimester infections were associated with higher rates of certain complications (57, 58). ...
Background
The COVID-19 pandemic has posed unprecedented challenges to global public health, especially for pregnant women and their offspring. However, little is known about the impact of maternal SARS-CoV-2 infection on neonatal outcomes, particularly in the context of coexisting gestational diabetes mellitus (GDM).
Methods
Hospitalized pregnant women with SARS-CoV-2 infection were retrospectively enrolled between November 2022 and January 2023, and matched with pregnant subjects free of SARS-CoV-2 infection based on their propensity scores. All women were tested for SARS-CoV-2 upon admission as part of routine procedures, then divided into groups of pregnant women with SARS-CoV-2 infection and GDM (SARS2+GDM), pregnant women with SARS-CoV-2 infection but without GDM (SARS2+noGDM), and pregnant women without SARS-CoV-2 infection or GDM (Normal group). A logistic regression model was used to study the risk of GDM, perinatal SARS-CoV-2 infection, and their interaction on neonatal SARS-CoV-2 infection.
Results
Of 378 pregnant women with SARS-CoV-2 infection, the neonatal infection rate was higher in the GDM group as compared to the SARS-CoV-2 infection only group, but both SARS-CoV-2 infection rates were lower than that of the normal control group. Logistic regression analysis identified an interaction between maternal SARS-CoV-2 infection and GDM on neonatal infection, where maternal SARS-CoV-2 infection (odds ratio [OR] = 0.31, 95%CI: 0.22-0.44) and vaccination for anti-SARS-CoV-2 (OR = 0.70, 95%CI: 0.50-0.98) were associated with lower odds of neonatal infection, while higher pre-pregnancy body mass index (BMI) (OR = 1.06, 95% CI: 1.02-1.10) and GDM (OR = 1.97, 95%CI: 1.21-3.21) were associated with higher odds of neonatal infection.
Conclusions
We demonstrate that the coexistence of GDM and perinatal SARS-CoV-2 infection was associated with an increased probability of neonatal SARS-CoV-2 infection.
... We analyzed the dynamic evolution patterns and compared them with real-world symptom patterns reported in relevant papers (Whitaker et al., 2022;Vihta et al., 2023;Looi, 2023). The results showed that the main symptom combinations were closely related to the pandemic stages. ...
Social media is recognized as an important source for deriving insights into public opinion dynamics and social impacts due to the vast textual data generated daily and the 'un-constrained' behavior of people interacting on these platforms. However, such analyses prove challenging due to the semantic shift phenomenon , where word meanings evolve over time. This paper proposes an unsupervised dynamic word embedding method to capture longitudinal semantic shifts in social media data without predefined anchor words. The method leverages word co-occurrence statistics and dynamic updating to adapt embed-dings over time, addressing the challenges of data sparseness, imbalanced distributions, and synergistic semantic effects. Evaluated on a large COVID-19 Twitter dataset, the method reveals semantic evolution patterns of vaccine-and symptom-related entities across different pandemic stages, and their potential correlations with real-world statistics. Our key contributions include the dynamic embedding technique , empirical analysis of COVID-19 semantic shifts, and discussions on enhancing semantic shift modeling for computational social science research. This study enables capturing longitudinal semantic dynamics on social media to understand public discourse and collective phenomena.
... We analyzed the dynamic evolution patterns and compared them with real-world symptom patterns reported in relevant papers (Whitaker et al., 2022;Vihta et al., 2023;Looi, 2023). The results showed that the main symptom combinations were closely related to the pandemic stages. ...
Social media is recognized as an important source for deriving insights into public opinion dynamics and social impacts due to the vast textual data generated daily and the 'unconstrained' behavior of people interacting on these platforms. However, such analyses prove challenging due to the semantic shift phenomenon, where word meanings evolve over time. This paper proposes an unsupervised dynamic word embedding method to capture longitudinal semantic shifts in social media data without predefined anchor words. The method leverages word co-occurrence statistics and dynamic updating to adapt embeddings over time, addressing the challenges of data sparseness, imbalanced distributions, and synergistic semantic effects. Evaluated on a large COVID-19 Twitter dataset, the method reveals semantic evolution patterns of vaccine- and symptom-related entities across different pandemic stages, and their potential correlations with real-world statistics. Our key contributions include the dynamic embedding technique, empirical analysis of COVID-19 semantic shifts, and discussions on enhancing semantic shift modeling for computational social science research. This study enables capturing longitudinal semantic dynamics on social media to understand public discourse and collective phenomena.
... Rapid virus clearance mediated by SARS-CoV-2-specific T cells prevents severe symptoms of COVID-19 [140]. Moreover, various studies have indicated that symptom profiles may differ between variants of SARS-CoV-2 [141][142][143]. Ultimately, lifestyle factors like diet, exercise, and stress levels can also impact immune function, and thus affect symptomatology [144,145]. ...
COVID-19 remains a significant threat, particularly to vulnerable populations. The emergence of new variants necessitates the development of treatments and vaccines that induce both humoral and cellular immunity. This study aimed to identify potentially immunogenic SARS-CoV-2 peptides and to explore the intricate host–pathogen interactions involving peripheral immune responses, memory profiles, and various demographic, clinical, and lifestyle factors. Using in silico and experimental methods, we identified several CD8-restricted SARS-CoV-2 peptides that are either poorly studied or have previously unreported immunogenicity: fifteen from the Spike and three each from non-structural proteins Nsp1-2-3-16. A Spike peptide, LA-9, demonstrated a 57% response rate in ELISpot assays using PBMCs from 14 HLA-A*02:01 positive, vaccinated, and mild-COVID-19 recovered subjects, indicating its potential for diagnostics, research, and multi-epitope vaccine platforms. We also found that younger individuals, with fewer vaccine doses and longer intervals since infection, showed lower anti-Spike (ELISA) and anti-Wuhan neutralizing antibodies (pseudovirus assay), higher naïve T cells, and lower central memory, effector memory, and CD4hiCD8low T cells (flow cytometry) compared to older subjects. In our cohort, a higher prevalence of Vδ2-γδ and DN T cells, and fewer naïve CD8 T cells, seemed to correlate with strong cellular and lower anti-NP antibody responses and to associate with Omicron infection, absence of confusional state, and habitual sporting activity.
... The symptoms of COVID-19 exhibit significant variability depending on the specific variants of SARS-CoV-2, the demographic characteristics of the patients, and the existence of underlying health issues [4][5][6]. Although many symptoms of this condition are associated with respiratory tract infections, such as fever and cough, there have also been reports of other systemic symptoms, including gastrointestinal and neurological manifestations [7]. ...
Background
Elevated blood glucose concentration, also known as hyperglycemia, has been identified as a significant factor influencing the prognosis of COVID-19, alongside the impact of the SARS-CoV-2 infection itself.
Methods
This research is a cross-sectional investigation that examined the relationship between COVID-19 and hyperglycemia in patients admitted to Afzalipour Hospital in Kerman, Iran, from July to September 2021. A standardized data sheet was used to capture demographic data (age, gender) and laboratory information (blood sugar, arterial blood oxygen saturation, and C-reactive protein (CRP)) upon admission.
Results
The present research evaluated a total of 300 individuals diagnosed with COVID-19, with an average age of 50.19 ± 15.55 years. Among these patients, the majority were male, accounting for 51.67% of the total. Hyperglycemia was seen in 21.67% of patients, but less than 20% had new-onset diabetes. Individuals exhibiting hyperglycemia were typical of advanced age (P < 0.001). Furthermore, there was a slight but statistically significant association between advanced age and elevated blood glucose concentration (R = 0.254, P < 0.001). Gender had no significant impact on the occurrence of hyperglycemia (P = 0.199). There was no significant association between CRP levels and blood glucose concentration (P = 0.524) or the incidence of hyperglycemia (P = 0.473). Although there was no significant disparity in blood oxygen saturation between individuals with or without hyperglycemia (P = 0.06), higher blood glucose concentration was correlated with lower blood oxygen saturation (R = -0.151, P < 0.001).
Conclusion
Considering the correlation between blood glucose concentration, advanced age, and disease severity, it is recommended to carefully screen and monitor all COVID-19 patients for hyperglycemia and new-onset diabetes. Effective management of these complications could enhance the control of patients’ overall prognosis and subsequent complications.
... Yet, with successive mutations of the virus, changes in the spectrum of symptoms have been observed (18). The study by Whitakera et al., published in Nature in 2022, highlighted a decrease in anosmia and an increase in flu-like and cold symptoms, including nasal congestion and rhinorrhea (19,20). This aligns with our findings that nasal congestion was less prevalent in COVID-19 patients compared to those with common cold or influenza. ...
Introduction
Upper respiratory tract infections (URTIs) are among the most common reasons for patients consulting a general practitioner (GP) during the infectious diseases season, with viruses being the predominant cause. The COVID-19 pandemic has significantly impacted GPs’ perception of these infections. The pandemic’s progression, especially with the emergence of the Omicron variant, has complicated the diagnosis and treatment of URTIs, with evolving symptoms.
Aim
The aim of this study was to assess the differences in symptoms reported by patients with various infections, such as COVID-19, influenza, common cold, and post-viral rhinosinusitis, during the infectious diseases season of November 2023 to March 2024.
Materials and methods
The study was conducted in a primary health care clinic, providing care for a population of approximately 10,000 people, among adult patients presenting with URTI symptoms during the 2023/2024 infectious diseases season. Patients qualified for the study were swabbed for SARS-CoV-2, influenza A and B and respiratory syncytial virus (RSV) antigens. Symptoms were assessed with the use of a semi-structured questionnaire.
Results
Of the 1810 patients presenting with symptoms of URTIs, 276 patients were included in the study. Among patients with COVID-19, symptoms of nasal obstruction (p = 0.005) and nasal discharge (p = 0.001) were less common than in those with influenza or common cold. However, these nasal symptoms were significantly more frequent among patients with COVID-19 who had confirmed previous immunization (COVID-19 history or vaccination) (p = 0.028).
Conclusion
The incidence of individual sinonasal symptoms varies significantly depending on the aetiological agent of the URTI. This observation may not only help clinicians make the correct diagnosis, but also suggests an inflammatory response in the nasal mucosa and paranasal sinuses that is dependent on the aetiological agent. The study also indicates that this response is altered within the same virus species following immunization.
Limitations
The study’s limitations include a small sample size (276 patients), focus on one season and one GP practice, and reliance on clinical signs and antigen tests. Nonetheless, the findings provide valuable insights. Further research with larger patient groups and extended follow-up periods is required to confirm these findings.
