Volatility and irregularity Capturing in stock price indices using time series Generative adversarial networks (TimeGAN) (preprint)

This paper captures irregularities in financial time series data, particularly stock prices, in the presence of COVID-19 shock. We conjectured that jumps and irregularities are embedded in stock data due to the pandemic shock, which brings forth irregular trends in the time series data. We put forward that efficient and robust forecasting methods are needed to predict stock closing prices in the presence of the pandemic shock. This piece of information is helpful to investors as far as confidence risk and return boost are concerned. Generative adversarial networks of a time series nature are used to provide new ways of modeling and learning the proper and suitable distribution for the financial time series data under complex setups. Ideally, these traditional models are liable to producing high forecasting errors, and they need to be more robust to capture dependency structures and other stylized facts like volatility in stock markets. The TimeGAN model is used, effectively dealing with this risk of poor forecasts. Using the DAX stock index from January 2010 to November 2022, we trained the LSTM, GRU, WGAN, and TimeGAN models as benchmarks and forecasting errors were noted, and our TimeGAN outperformed them all as indicated by a small forecasting error.

Medical Student Mentorship in the COVID-19 Era (preprint)

ObjectiveTo determine the perspective of then third- and fourth-year medical students regarding the impact of the COVID-19 pandemic on mentorship.MethodsThe authors distributed a modified Likert scale questionnaire (score: 1-10) to third- and fourth-year medical students at two large US allopathic medical schools from the class of 2021 and 2022. Responses to each survey item were analyzed to characterize the impact of the COVID-19 pandemic on mentorship relationships in medical school. A score of 1-5 was considered “disagree” and a score of 6-10 was considered “agree”. ResultsA total of 144 responses were collected with a response rate of 16.2%. Overall, 80.6% (n=116) of respondents agree that the COVID-19 pandemic had a negative impact on their medical school experience. Nearly half (41.0%, n=59) expressed concern over the lack of mentorship opportunities, and 66.0% (n=95) reported that the pandemic made it more difficult to form or maintain connections with their mentors. Importantly, 43.6% (n=61) of respondents reported that having close mentoring relationships reduced the impact of the pandemic on their medical training. While many respondents (79.9%, n=114) did not change career plans due to the pandemic, most students were concerned about evaluating prospective residency programs (88.9%, n=128). Notably, M3s had much lower confidence than M4s in their ability to choose a specialty (5.9 vs. 8.2, p = 6.43e-08).ConclusionsThis investigation illustrated the concerns that medical students had regarding access to mentorship opportunities during the COVID-19 pandemic. We hope that these findings encourage medical schools to evaluate and expand their current mentorship programs.

A high-resolution melt curve toolkit to identify lineage-defining SARS-CoV-2 mutations (preprint)

The emergence of severe acute respiratory syndrome 2 (SARS-CoV-2) variants of concern (VOCs), with mutations linked to increased transmissibility, vaccine escape and virulence, has necessitated the widespread genomic surveillance of SARS-CoV-2. This has placed a strain on global sequencing capacity, especially in areas lacking the resources for large scale sequencing activities. Here we have developed three separate multiplex high resolution melting (HRM) assays to enable the identification of Alpha, Beta, Delta and Omicron VOCs, assay based on HRM analysis, an endpoint RT-qPCR detection method. The assays were evaluated against whole genome sequencing on upper-respiratory swab samples collected at varying points of the UK pandemic. The sensitivities of the eight individual primer sets were all 100%, and specificity ranged from 94.6 to 100%. The multiplex HRM assays have potential as a tool for high throughput surveillance of SARS-CoV-2 VOCs, particularly in areas with limited genomics facilities.

Predicted Norovirus Resurgence in 2021-2022 Due to the Relaxation of Nonpharmaceutical Interventions Associated with COVID-19 Restrictions in England: A Mathematical Modelling Study (preprint)

Background: To reduce the coronavirus disease burden in England, along with many other countries, the Government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions. Methods: Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021. Results: We report that susceptibility to norovirus infection has likely increased between March 2020 to mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages. Conclusions: Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

Anosmia in SARS-CoV-2 Patients: a Retrospective Study (preprint)

BackgroundPost viral anosmia has been reported in human coronavirus infections. In this current pandemic, olfactory dysfunction (OD) has emerged as a common key presenting symptom of COVID-19 infection. In this study, we describe OD assessment in the inpatient setting of patients both suspected of and with confirmed COVID-19 infection via University of Pennsylvania Smell Identification Test (UPSIT) objective assessment and a simple self-reported 3-item questionnaire.MethodsThirty patients admitted to the isolation wards of the National University Hospital, Singapore for either suspected or confirmed COVID-19 infection from April to May 2020 were recruited to this study. 10 patients who tested negative for SARS-CoV-2 were recruited as control subjects. The 20 patients with COVID-19 infection were divided into two groups (10 had olfactory testing performed during the first week of illness, 10 in the second week of illness). A simple 3-question survey was administered to each participant - to rank the severity, state the onset and duration of their hyposmia. Olfactory testing was performed using an English version of the UPSIT.ResultsLoss of smell was reported in 2 participants from the control group, 6 participants from the in the first week of illness and 5 participants from the second week of illness. Two COVID-19 patients have anosmia on the UPSIT. COVID-19 patients were more likely to have severe hyposmia or anosmia by objective assessment, a difference that was statistically significant (P = 0.0485). The differences in degree of OD among COVID-19 patients in their first and second week of illness were not statistically significant (P= 0.6563).ConclusionSelf-reported anosmia was higher among COVID-19 patients compared to controls who were admitted to isolation wards for respiratory symptoms but were tested negative for SARS-CoV-2 infection. On objective assessment by the UPSIT, COVID-19 patients were found to have higher rates of severe hyposmia or anosmia, a difference that was statistically significant (P = 0.0485). A limitation of this study is the odorants used in UPSIT which may be less familiar to the primarily Asian participants in this study, owing to cultural differences. 

Depression, anxiety, and acute stress disorder among patients hospitalized with coronavirus disease 2019: A prospective cohort study

BACKGROUND: The epidemiology of psychiatric symptoms among patients with coronavirus disease 2019 is poorly characterized. OBJECTIVE: This article sought to identify the prevalence of anxiety, depression, and acute stress disorder among hospitalized patients with coronavirus disease 2019. METHODS: Adult patients recently admitted to nonintensive care unit medical ward settings with coronavirus disease 2019 were eligible for enrollment. Enrolled patients were screened for depression, anxiety, and delirium. Subsequently, patients were followed up by phone after 2 weeks and rescreened for depression, anxiety, and acute stress disorder symptoms. Subjects' medical records were abstracted for clinical data. RESULTS: A total of 58 subjects were enrolled;of whom, 44 completed the study. Initially, 36% of subjects had elevated anxiety symptoms and 29% had elevated depression symptoms. At 2-week follow-up, 9% had elevated anxiety symptoms, 20% had elevated depression symptoms, and 25% had mild-to-moderate acute stress disorder symptoms. Discharge to home was not associated with improvement in psychiatric symptoms. CONCLUSIONS: A significant number of patients hospitalized with coronavirus disease 2019 experienced symptoms of depression and anxiety. While anxiety improved after index admission, depression remained fairly stable. Furthermore, a significant minority of patients experienced acute stress disorder symptoms, though these were largely mild to moderate. (PsycInfo Database Record (c) 2021 APA, all rights reserved)