ABSTRACT
The impact of individual symptoms reported post-COVID-19 on subjective well-being (SWB) is unknown. We described associations between SWB and selected reported symptoms following SARS-CoV-2 infection. We analysed reported symptoms and subjective well being from 2295 participants (of which 576 reporting previous infection) in an ongoing longitudinal cohort study taking place in Israel. We estimated changes in SWB associated with reported selected symptoms at three follow-up time points (3-6, 6-12, and 12-18 months post infection) among participants reporting previous SARS-CoV-2 infection, adjusted for key demographic variables, using linear regression. Our results suggest that the biggest and most sustained changes in SWB stems from non-specific symptoms (fatigue -7.7 percentage points (pp), confusion/ lack of concentration -10.7 pp, and sleep disorders -11.5pp, p<0.005), whereas the effect of system-specific symptoms, such as musculoskeletal symptoms (weakness in muscles and muscle pain) on SWB, are less profound and more transient. Taking a similar approach for other symptoms and following individuals over time to describe trends in SWB changes attributable to specific symptoms will help understand the post-acute phase of COVID-19 and how it should be defined and better managed.
ABSTRACT
Vaccination is a key tool to mitigate impacts of the COVID-19 pandemic. In Israel, COVID-19 vaccines became available to adults in December 2020 and to 5-11-year-old children in November 2021. Ahead of the vaccine roll-out in children, we aimed to determine whether surveyed parents intended to vaccinate their children and describe reasons for their intentions. We collected information on parental socio-demographic characteristics, COVID-19 vaccine history, intention to vaccinate their children against COVID-19, and reasons for parental decisions using an anonymous online survey. We identified associations between parental characteristics and plans to vaccinate children using a logistic regression model and described reasons for intentions to vaccinate or not. Parental non-vaccination and having experienced major vaccination side effects were strongly associated with non-intention to vaccinate their children (OR 0.09 and 0.18 respectively, p<0.001). Parents who were younger, lived in the socio-economically deprived periphery, and belonged to the Arab population had lower intentions to vaccinate their children. Reasons for non-intention to vaccinate included concerns about vaccine safety and efficacy (53%, 95%CI 50-56) and the belief that COVID-19 is a mild disease (73%, 95%CI 73-79), while a frequent motive for vaccination was the return to normal social and educational life (89%, 95%CI 87-91). Understanding rationales for COVID-19 vaccine rejection or acceptance, as well as parental demographic data, can pave the way for intentional educational campaigns to encourage not only vaccination against COVID-19, but also regular childhood vaccine programming. HighlightsO_LIParental intention to vaccinate children aged 5-11 is much lower than vaccine coverage in parental age groups C_LIO_LIBeing unvaccinated and having experienced side effects following vaccination were the greatest negative predictors in parents of intention to vaccinate their children C_LIO_LIParents were more likely to accept a COVID-19 vaccine for their children to allow them to return to daily social life and to ensure economic security in the family C_LIO_LIParents were more likely to reject a COVID-19 vaccination for health reasons such as safety concerns or due the belief that COVID-19 was a mild disease in children C_LI
ABSTRACT
ObjectiveStudies have demonstrated a potential link between low vitamin D levels and both an increased risk of infection with SARS-CoV-2 and poorer clinical outcomes but have not established temporality. This retrospective study examined if, and to what degree, a relationship exists between pre-infection serum vitamin D levels and disease severity and mortality of SARS-CoV-19. Design and patientsThe records of individuals admitted between April 7th, 2020 and February 4th, 2021 to the Galilee Medical Center (GMC) in Nahariya, Israel with positive polymerase chain reaction (PCR) tests for SARS-CoV-2 were searched for vitamin D (VitD) levels measured 14 to 730 days prior to the positive PCR test. MeasurementsPatients admitted to GMC with COVID-19 were categorized according to disease severity and VitD level. Association between pre-infection VitD levels and COVID-19 severity was ascertained utilizing a multivariate regression analysis. ResultsOf 1176 patients admitted, 253 had VitD levels prior to COVID-19 infection. Compared with mildly or moderately diseased patients, those with severe or critical COVID-19 disease were more likely to have pre-infection vitamin D deficiency of less than 20 ng/mL (OR=14.30, 95%, 4.01-50.9; p < .001); be older (OR=1.039 for each year, 95% CI for OR, 1.017-1.061; p< .01), and have diabetes (OR=2.031, 95% CI for OR, 1.04-3.36; p= 0.038). Vitamin D deficiency was associated with higher rates of mortality (p<0.001) and comorbidities including COPD (p=0.006), diabetes (p=0.026), and hypertension (p=0.016). ConclusionsAmong hospitalized COVID-19 patients, pre-infection deficiency of vitamin D was associated with increased disease severity and mortality.
ABSTRACT
The COVID-19 pandemic raises the need for diverse diagnostic approaches to rapidly detect different stages of viral infection. The flexible and quantitative nature of single-molecule imaging technology renders it optimal for development of new diagnostic tools. Here we present a proof-of-concept for a single-molecule based, enzyme-free assay for detection of SARS-CoV-2. The unified platform we developed allows direct detection of the viral genetic material from patients samples, as well as their immune response consisting of IgG and IgM antibodies. Thus, it establishes a platform for diagnostics of COVID-19, which could also be adjusted to diagnose additional pathogens.
ABSTRACT
ObjectivesIn the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in diagnosis and monitoring of patients with COVID-19. Machine learning solutions have been shown to be useful for X-ray analysis and classification in a range of medical contexts. In this study, we propose a machine learning model for detection of patients tested positive for COVID-19 from CXRs that were collected from inpatients hospitalized in four different hospitals. We additionally present a tool for retrieving similar patients according to the models results on their CXRs. MethodsIn this retrospective study, 1384 frontal CXRs, of COVID-19 confirmed patients imaged between March-August 2020, and 1024 matching CXRs of non-COVID patients imaged before the pandemic, were collected and used to build a deep learning classifier for detecting patients positive for COVID-19. The classifier consists of an ensemble of pre-trained deep neural networks (DNNS), specifically, ReNet34, ReNet50, ReNet152, vgg16, and is enhanced by data augmentation and lung segmentation. We further implemented a nearest-neighbors algorithm that uses DNN-based image embeddings to retrieve the images most similar to a given image. ResultsOur model achieved accuracy of 90.3%, (95%CI: 86.3%-93.7%) specificity of 90% (95%CI: 84.3%-94%), and sensitivity of 90.5% (95%CI: 85%-94%) on a test dataset comprising 15% (350/2326) of the original images. The AUC of the ROC curve is 0.96 (95%CI: 0.93-0.97). ConclusionWe provide deep learning models, trained and evaluated on CXRs that can assist medical efforts and reduce medical staff workload in handling COVID-19. Key PointsO_LIA machine learning model was able to detect chest X-ray (CXR) images of patients tested positive for COVID-19 with accuracy and detection rate above 90%. C_LIO_LIA tool was created for finding existing CXR images with imaging characteristics most similar to a given CXR, according to the models image embeddings. C_LI
ABSTRACT
Many government websites and mobile content are inaccessible for people with vision, hearing, and cognitive disabilities. The COVID-19 pandemic highlighted these disparities when health authority website information, critical in providing resources for curbing the spread of the virus, remained inaccessible for disabled populations. The Web Content Accessibility Guidelines provide comparatively universally accepted guidelines for website accessibility. We utilized these parameters to examine the number of countries with or without accessible health authority websites. The resulting data indicate a dearth of countries with websites accessible for persons with disabilities. Methods of information dissemination must take into consideration individuals with disabilities, particularly in times of global health crises.
