COVID-19 Pandemic Period Research Articles

Data architectures and the prevalent cyberattacks encountered by West African higher educational institutions in the COVID-19 era

The growing interconnectedness of the world has led to a rise in cybersecurity risks. Although it is increasingly conventional to use technology to assist business transactions, exposure to these risks must be minimised to allow business owners to do transactions in a secure manner. While a wide range of studies have been undertaken regarding the effects of cyberattacks on several industries and sectors, However, very few studies have focused on the effects of cyberattacks on the educational sector, specifically higher educational institutions (HEIs) in West Africa. Consequently, this study developed a survey and distributed it to HEIs particularly universities in West Africa to examine the data architectures they employed, the cyberattacks they encountered during the COVID-19 pandemic period, and the role of data analysis in decision-making, as well as the countermeasures employed in identifying and preventing cyberattacks. A total of one thousand, one hundred and sixty-four (1164) responses were received from ninety-three (93) HEIs and analysed. According to the study’s findings, data-informed architecture was adopted by 71.8% of HEIs, data-driven architecture by 24.1%, and data-centric architecture by 4.1%, all of which were vulnerable to cyberattacks. In addition, there are further concerns around data analysis techniques, staff training gaps, and countermeasures for cyberattacks. The study’s conclusion includes suggestions for future research topics and recommendations for repelling cyberattacks in HEIs.

Using a Smartphone-Based Chatbot for Postoperative Care After Intravitreal Injection During the COVID-19 Pandemic: Retrospective Cohort Study.

During the COVID-19 pandemic period, it was difficult to carry out regular and scheduled follow-up of patients in the outpatient department, especially during lockdown periods. However, early detection of initial infection or other serious conditions is vital for patients after ocular surgery, such as intravitreal injection (IVI) for age-related macular degeneration (AMD). We evaluated the use of a smartphone-based postoperative care chatbot system (PCCS) with an instant bidirectional feedback system for patients to self-report postoperative symptoms and signs. During the COVID-19 level 3 epidemic alert in July 2021 in Taiwan, the PCCS alerted the patients to report and grade 6 ocular symptoms and signs associated with ocular inflammation or retinal detachment. Patients used the PCCS for 7 days post surgery to assess their symptoms and signs each day after receiving an alert. Data were automatically collected using a cloud computer system, including symptom grades and messages sent to medical staff for further medical assistance. A user satisfaction questionnaire was administered to the patients on the seventh day post surgery. In total, 185 patients participated in this study. There were 26 (3.03%) reports of symptom grade deterioration (including increased blurred vision, eye swelling, nausea, and floaters or flashes) from 12 (6.5%) patients. We found no difference in the gender of patients who received an early medical consultation. One case of endophthalmitis was reported, wherein an improvement was observed after prompt administration of IVI antibiotics twice. Overall, 87% (n=185) of patients were satisfied or very satisfied with communicating their symptoms instantly through the app; they were willing to use it again and believed that it could improve the quality of care. Seven of the 185 (3.8%) patients had an earlier medical consultation and 1 (0.5%) had endophthalmitis. The chatbot system, designed for self-reporting postoperative symptoms and providing instant bidirectional feedback on smartphones, could be beneficial for enhancing the quality of care in early medical consultations without gender differences among patients with AMD receiving IVI, and achieved satisfactory responses from patients.

Empirical Analysis of Portfolio Allocation During Market Turbulence Based on Efficient Frontier

The global financial markets have experienced considerable turmoil due to the COVID-19 pandemic, in this context, portfolio management becomes critically important. This paper employs Monte Carlo Simulation to determine Efficient Frontier of a portfolio comprising fourteen US technology stocks in the period of COVID-19 pandemic by python, which also allocates portfolios for Minimum Volatility and Maximum Sharpe Ratio, along with their key parameters. According to this study, Maximum Sharpe Ratio portfolio outperforms Minimum Volatility portfolio in terms of cumulative return. However, its important to note that Maximum Sharpe Ratio portfolio also experiences a greater maximum drawdown. Additionally, this paper visually depicts the optimal allocation of asset weights across different levels of risk aversion using a chart. Furthermore, it identifies NVDA as the optimal choice for investors who have low degree of risk-aversion due to its high volatility and expected return. Conversely, IBM and CSCO emerge as the preferred choices for risk-averse investors, as they effectively mitigate the portfolios entire risk.

Analysis of Change in Marriage and Divorce and Associated Socioeconomic Variables during the COVID-19 Pandemic Period

Due to the COVID-19 pandemic, people have contended with health, economic, and social issues on a global scale. Therefore, the study aimed to investigate the effect of the COVID-19 epidemic on marriage-divorce, (Crude marriage rate, divorce rate, birth rate, male and female first marriage age) and their socioeconomic related indicators (The ratio of female high school and undergraduate school graduates, man and women employment rates, unemployment rate, GDP per capita,suicide rate). The regions had the highest female employment rate were differentiated by lowest crude marriage and crude birth rates. In addition to this, the regions had the highest divorce rate were differentiated by the highest educated women rate and GDP per capita. As a result, the regional differences were high in the country in terms of study indicators.

The Legacy of the COVID-19 Pandemic: Impact on Infant and Maternal and Health from an Appalachian Academic Medical Center.

The COVID-19 pandemic period from 2020 to 2022 had a significant impact on maternal infant health with mothers impacted more than their infants. We questioned whether there have been any lingering effects from the pandemic. We examined intermediate and long-term pandemic effects on maternal and neonatal outcomes before, during, and after the COVID-19 pandemic period. We reviewed mother-infant pairs from the following three epochs: (1) the pre-COVID-19 period, (2) the COVID-19 pandemic period, and (3) the post-pandemic period. The Case Mix Index (CMI) for the neonates from all three epochs were detailed. Post-pandemic, we noted a rising trend of LGA infants (10%) and an increase in SGA infants (13%). For women in 2023, we noted an increase in hypertension, preeclampsia, diabetes, and a higher BMI than in the pre-pandemic period. There have also been more congenital anomalies (9%), and neonatal CMI increased in the post-pandemic period. Well after the pandemic period, maternal-infant health continues to be affected. For women, the increase in hypertension and diabetes during pregnancy is concerning. For infants, being LGA or SGA may have long-term consequences. The post-pandemic increase in infants with congenital anomalies compared to the pre-pandemic era is an area that needs ongoing review.

Hazardous Elements in the Edible Portion of Perna perna Mussels: Relation with the COVID-19 Pandemic Period and Assessment of the Risk to Human Health.

In this work, the concentrations of hazardous elements (As, Cd and Pb) in the edible portion of the Perna perna mussel from Southeast Brazil were analyzed to understand the effects of the COVID-19 pandemic on the coastal environment and to evaluate the quality of this fishery resource. Decreases in anthropogenic chemical outputs to the environment were expected to occur during the COVID-19 pandemic, with decreases in element concentrations in mussels. The ranges of median concentrations (µgg-1dw) in the pre- and pandemic periods were 5.4-16.1 and 2.2-10.6 for As; 0.2-0.6 and 0.1-0.5 for Cd; and 1.2-3.2 and 0.7-1.8 for Pb, respectively. Temporal variations (prepandemic x pandemic) were more significant than spatial variations (five sampling sites). The relationships between the concentrations of hazardous elements and isotopic ratios (δ15N and δ13C) suggested that food sources were more diverse across the sampling sites during the pandemic period, when individuals exhibited less efficient trophic transfer. The concentrations of Cd and Pb were below the tolerable maximum limit, whereas for As, they were above the limit; however, these concentrations are not a risk to human health, as most As was present in the least toxic organic form. The intake estimates were below the tolerable intake limits, and only Pb concentrations are at risk of causing concern if the intake of mussels increases. This is the first study in Brazil that presents a spatial-temporal comparison of hazardous elements in marine fauna considering COVID-19 as a temporal landmark. The results are of interest for both public health and environmental health management in a post-COVID-19 scenario.

Classification of supervised deep learning models for COVID-19 tweets sentiment analysis

Social media provided a successful management of human societies in light of global crises. Social media platforms have been considered the central authority in guiding society, receiving information and conducting business in many countries during the COVID-19 pandemic period in March 2020. The social platform has seen an increase in use of 45% for public platforms and 35% for the use of messages. This study suggests An AI-based model for predicting the likelihood of infection with COVID-19 through sentiment analysis and early detection using a Natural Language Processing library with deep learning techniques CNN. The model performed improved the distinction between patients who are 'positive' and patients who are 'natural' and unaffected are 'negative'. The performance of the model was tested using publicly available databases on Twitter for the period from March 16, 2020 to April 14, 2020.The achieved accuracy percentage was (~99.8% )) and based on the four measures Accuracy, Recall, Precision and F1-score.

Perceptions and Difficulties of Distance Learning Among Beginning Teachers and Kindergarteners During the Covid-19 Pandemic Period

Exploring the perceptions and challenges faced by beginning teachers and kindergarten teachers in the realm of distance learning reveals critical insights into the evolving landscape of early education in a digital age. The present study explored the challenges and difficulties experienced by beginning teachers and kindergarteners in the context of distance learning. Qualitative research was conducted through semi-structured interviews involving 254 novice teachers and kindergarten educators. The findings revealed a range of difficulties new teachers face in the distance learning environment. These included challenges in conveying educational content, issues with Wi-Fi and internet connectivity, a lack of resources and technological tools, difficulties in engaging students in Zoom meetings, poor communication between teachers and students, insufficient preparation and training for distance teaching, inadequate digital skills, and a lack of experience among parents with the new method of learning. Understanding the challenges and difficulties that novice teachers encounter, particularly during their initial professional years and in exceptional circumstances like the COVID-19 pandemic, is crucial. This understanding not only aids in addressing and surmounting these challenges but also contributes to the enhancement and development of current distance teaching models. Such improvements should consider the specific needs and challenges of new teachers. L'étude des perceptions et des difficultés rencontrées par les enseignants débutants et les enseignants de maternelle dans le domaine de l'enseignement à distance révèle des informations essentielles sur l'évolution du paysage de l'éducation préscolaire à l'ère numérique. La présente étude a exploré les défis et les difficultés rencontrés par les enseignants débutants et les enseignants de maternelle dans le contexte de l'enseignement à distance. La recherche qualitative a été menée par le biais d'entrevues semi-structurées auxquelles ont participé 254 enseignants débutants et éducateurs de maternelle. Les résultats ont révélé une série de difficultés auxquelles les nouveaux enseignants sont confrontés dans le milieu de l'enseignement à distance. Il s'agit notamment des difficultés à transmettre le contenu éducatif, des problèmes de connexion Wi-Fi et Internet, du manque de ressources et d'outils technologiques, des difficultés à faire participer les élèves aux réunions Zoom, de la mauvaise communication entre les enseignants et les élèves, du manque de préparation et de formation à l'enseignement à distance, des compétences numériques inadéquates et du manque d'expérience des parents en ce qui concerne cette nouvelle méthode d'apprentissage. Il est essentiel de comprendre les défis et les difficultés que rencontrent les enseignants débutants, en particulier au cours de leurs premières années professionnelles et dans des circonstances exceptionnelles telles que la pandémie de COVID-19. Cette compréhension permet non seulement d'aborder et de surmonter ces défis, mais aussi de contribuer à l'amélioration et au développement des modèles actuels d'enseignement à distance. Ces améliorations devraient prendre en compte les besoins et les défis spécifiques des nouveaux enseignants.

Improvement of Air Quality During Lockdown Period of COVID-19 Pandemic in Kathmandu Valley, Nepal

The Kathmandu Valley is currently Nepal's most hazardous region for human health and environmental sustainability because of increased air pollution and high particulate matter levels. According to multiple studies and observations, Nepal's urban districts saw an improvement in air quality during the COVID-19 lockdown. The Air Quality Index (AQI) is a standard method of informing the public about air pollution levels. The AQI is based on the quantitative value of pollutants' constituent parts, such as particulate matter (PM). Thus, the focus of this study was on how the AQI values change in the Ratna Park suburb of the Kathmandu district in the Kathmandu Valley and how those fluctuations are related to lockdown and non-lockdown times during the COVID-19 pandemic and comparing them to identify crucial information’s. This study shows that during the lockdown, the air quality in the Kathmandu Valley dramatically improved, with average AQI values for PM2.5 and PM10 rising to 21.34 and 64.42 from 50.74 and 106.51, respectively. Furthermore, we investigate the positive correlation between relative humidity, a meteorological component, and air quality.

Tourism forecasting by mixed-frequency machine learning

This study aims to establish the nonlinear relationship between high frequency Baidu search volumes, low frequency tourist arrivals and dummy variables and proposes a mixed-frequency machine learning model: the Bidirectional Long Short-Term Memory Mixed Frequency Data Sampling (BiLSTM-MIDAS) model. The empirical results of forecasting weekly tourist arrivals to Kulangsu and Jiuzhaigou Valley in China demonstrate that (1) BiLSTM-MIDAS can outperform benchmark models, which is also confirmed during the COVID-19 pandemic period; (2) Compared with the MIDAS model, establishing the nonlinear relationship between high frequency Baidu search volumes, low frequency tourist arrivals and dummy variables using BiLSTM-MIDAS can improve the roles of high-frequency search engines in forecasting tourism demand. This study represents the first attempt to apply machine learning methods for tourism demand forecasting with mixed-frequency data.

Opioid-related deaths in Northern Ontario in the early COVID-19 pandemic period.

In the first year of pandemic measures, opioid-related deaths across Ontario's (ON) 34 public health units (PHUs) increased by 60%. Death rates for all seven Northern ON PHUs were above the provincial average. This study describes and compares factors surrounding opioid-related deaths before and after pandemic measures were introduced, for Northern ON compared to the rest of ON. Aggregate data were provided for Northern ON and the rest of the province by the Office of the Chief Coroner/Ontario Forensic Pathology Services. Opioid-related deaths were cohorted by date of death for the year before and after pandemic measures were introduced on March 16, 2020. Chi-square tests were used to compare between cohorts and geographies to determine significant differences for each variable, and for dichotomized levels within variables. P-values < 0.05 were considered statistically significant a priori. In Northern ON, the number of opioid-related deaths approximately doubled from the pre-pandemic cohort (n = 185) to the early pandemic cohort (n = 365). Compared to the rest of ON, higher proportions of deaths occurred in Northern ON among individuals who lived and died in private residences, among women (although the majority of decedents were male) and among individuals employed in mining, quarrying, and oil and gas industries. Compared to the pre-pandemic year, in Northern ON, higher proportions of opioid-related deaths involved fentanyl and stimulants as direct contributors, and the majority involved evidence of inhaled drugs. Differences between the circumstances of death in Northern ON andin the rest of ON suggest opportunities to tailor interventions.

Trends and cycles during the COVID-19 pandemic period

We perform several trend-cycle decompositions through the lens of two unobserved components models, herein estimated for Portugal and the euro area. Our procedure copes with the COVID-19’s consequences by explicitly considering potentially larger second moments during that period. This is achieved through a set of pandemic-specific shocks affecting only the 2020–21 period and embedded into estimation through a piecewise linear Kalman filter. Our methodology generates negligible historical revisions in key smoothed variables when the sample period is expanded until 2021:4, since pandemic shocks absorb a great deal of data volatility with minimal impacts on filtered data revisions or estimated parameters. Furthermore, non-pandemic shock volatility remains largely unaffected by the pandemic period. Innovations affecting the cycle in our preferred model are the key propellers of GDP developments during the COVID-19 pandemic period.

Mental disorders in children and adolescents with type 1 diabetes before and during the COVID-19 pandemic: results from the DPV registry.

The COVID-19 pandemic affected the mental health of children and adolescents in the general population, yet its impact on those with chronic conditions is relatively unknown. This study aimed to compare the incidences of comorbid mental disorders and substance misuse in children and adolescents with type 1 diabetes before and during the pandemic. A total of 42,975 patients aged 6-18 years from the multicentre DPV (Diabetes Prospective Follow-up) registry were included. Multivariable regression models were applied to compare newly diagnosed comorbid mental disorders, adjusted for demographic and clinical variables, among them the number of medical visits, during the pre-pandemic period (09/2017-02/2020) and the COVID-19 pandemic period (03/2020-08/2022). Analysing both sexes together, there were no differences in the incidence rates of overall mental disorders between the pandemic and the pre-pandemic period. However, girls showed an increased incidence rate (odds ratio 1.2, CI 1.1-1.3) during the pandemic. Adolescent girls also displayed higher incidence rates of depression, eating disorders, and self-harm. Substance misuse declined overall during the pandemic (odds ratio 0.8, CI 0.7-0.9). During the COVID-19 pandemic, we found higher incidence rates of overall mental disorders in girls, but not in boys and not in the total study population of children and adolescents with type 1 diabetes. Adolescent girls displayed increased incidence rates of depression, eating disorders, and self-harm. Substance misuse declined substantially. Clinicians should be aware of the high-risk group of adolescent girls during times of increased strain.

Decreased Positive Fecal Occult Blood Tests and Delayed Medical Presentation for Colorectal Cancer during the Initial COVID-19 Pandemic Period: A Single-center Experience.

This study aimed to investigate the impact of the COVID-19 pandemic on the examination and treatment of colorectal cancer (CRC) and on the behaviors of patients and practitioners. This is a retrospective analysis of the CRC patients who presented to our department between April 2019 and March 2021 and underwent surgery. Clinical presentation of CRC and time from symptom onset to medical presentation were compared between the control (April 2019 to March 2020, n=124) and COVID-19 pandemic periods (April 2020 to March 2021, n=111). Two hundred and thirty-five patients were reviewed. The rate of positive fecal occult blood tests was significantly lower during the COVID-19 pandemic period (13.5 vs. 25.0%, P = 0.027). Among the symptomatic patients who had melena and abdominal symptoms, the time from symptom onset to medical presentation was significantly longer during the COVID-19 period (115 vs. 31 days, P < 0.001). In addition, the interval between presenting to a practitioner and being referred to our department was similar between the two periods (19 vs. 13 days, P = 0.092). There were no significant differences in the stage of cancer between the two periods. The rate of preoperative sub-obstruction was significantly higher during the COVID-19 period (41.4 vs 23.4%, P = 0.003). There was no significant difference in overall survival and recurrence-free survival between two periods. Hesitation to seek examination and treatment for CRC was observed in patients but not in practitioners during the COVID-19 pandemic period. The prognosis did not change.

Exploring the antecedent factors of continuous intention to use mobile money: insights from emerging markets

Purpose The purpose of this study is to examine the factors that may have an influence on the continuous intention to use mobile money as one of the Financial Technology (FinTech) products beyond the COVID-19 pandemic lockdown period. Design/methodology/approach This study has empirically tested the expanded post-acceptance model (Extend-PAM) and the expectation-confirmation model (ECM) to explain the mobile money adoption in Jordan. Data collected were analyzed through partial least squares–structural equation modeling (PLS-SEM). Findings The results mainly showed that the quality of administrative services and trust significantly impact confirmation and perceived usefulness. In addition, perceived security and knowledge of mobile money as one of the FinTech services significantly influence users’ confirmation and perceived usefulness. Also, usefulness and satisfaction influence continuous intention. Significant relationships were noted among confirmation, perceived usefulness, satisfaction and continuous intention to use mobile money. Originality/value This paper integrates two key theories: the expanded post-acceptance model (Extend-PAM) and the expectation-confirmation model (ECM) in the post-adoption behavior of mobile money. Therefore, this study attempts to fill a literature gap by examining the antecedent factors that influence the continuous intention to use mobile money services in the post-consumption stage.

Anti-HNA testing of allo-exposed COVID-19 convalescent plasma donors including genetic human neutrophil antigen screening to prevent anti-HNA antibody-mediated transfusion-related acute lung injury.

Transfusion-related acute lung injury caused by antibodies against human neutrophil antigens (HNA) is a serious but rare complication associated with blood transfusion. The presence of such antibodies is most probable in donors with a transfusion/pregnancy history. During the COVID-19 pandemic period convalescent plasma (CP) containing neutralizing antibodies against SARS-CoV-2 was widely used for COVID-19 patients as a therapy in the absence of any treatment. The aim of the study was to work out a simple diagnostic algorithm of anti-HNA testing of allo-exposed CP donors including genetic HNA screening. A total of 457 anti-HLA-negative allo-exposed CP donors were genotyped for HNA-1a/1b, HNA-3a/3b, and HNA-2, and only donors with homozygous HNA-1a/1a; HNA-3b/3b; or HNA-2null genotypes were tested for anti-HNA antibody using LabScreenMulti (One Lambda) and homozygous HNA-1b/1b using the granulocyte immunofluorescence test (GIFT) but verified using LabScreenMulti. Testing of 83 homozygous HNA-3b/3b; HNA-2null; or HNA-1a/1a donors revealed anti-HNA-3a antibody in one case. Testing of 181 HNA-1b/1b donors using GIFT gave 10 ambiguous results verified using LabScreenMulti which confirmed anti-HNA-1a antibody in one case. The frequency of FCGR3B*01 and *04 encoding HNA-1a was 0.34; FCGR3B*02, *03, and *05 encoding HNA-1b-0.66; SLC44A2*01 encoding HNA-3a-0.80; and SLC44A2*02 encoding HNA-3b-0.20. In 3.7% cases the HNA-2null genotype was revealed. Due to applying HNA genotyping as a primary test before anti-HNA antibody testing the serological work was limited only to HNA-homozygous donors revealing two anti-HNA immunized donors. The distribution of HNA genotypes in the cohort was similar to other Caucasian populations.

Changes in the epidemiological characteristics of influenza in children in Zhengzhou, China, in the post-COVID-19 era

BackgroundInfluenza is a contagious respiratory disease posing a huge burden of disease for children around the world. The purpose of this study was to investigate the epidemiologic changes in childhood influenza in Zhengzhou, China, before, during, and after the COVID-19 outbreak. The aim of this study was to determine the impact of the COVID-19 outbreak and related prevention and control policies on the children’s influenza epidemiological trend.MethodsAll influenza report card data from the Children’s Hospital Affiliated with Zhengzhou University’s Disease Surveillance Reporting Management System were collected and analyzed monthly from January 2018 to December 2023. The period of the study was divided into three phases for comparison: the pre-pandemic period, the pandemic period, and the post-pandemic period.ResultsBetween January 2018 and December 2023, a total of 82,030 children with influenza were diagnosed at our hospital, including 46,453 males and 35,577 females. A total of 11,833 of them had to be hospitalized for influenza, and 321 of them were brought to the ICU. Influenza showed low-level epidemiologic status during the COVID-19 pandemic, and there was a substantial rise in influenza and a surge in the number of cases after the COVID-19 pandemic period. The year 2023 will had the most influenza cases (40,785). The peak incidence of influenza changes in 2022, from July to October, and in 2023, from February to April and from October to December. During the post-pandemic period, the proportion of new-borns and young children among influenza patients decreased, while the proportion of school-age children increased significantly, and the proportion of influenza patients hospitalized and the proportion of ICU admissions decreased.ConclusionInfluenza showed low-level epidemiologic status during the COVID-19 pandemic. In the post-pandemic period, there is a large increase in influenza incidence, with a double peak in influenza incidence. The proportion of school-age children with influenza has also increased. As a result, we recommend that influenza vaccination for key populations, particularly school-age children, be completed by October of each year in Henan Province, and that the government and schools increase education about nonpharmacological influenza prevention approaches.

Bioethical and Human Right Considerations during COVID-19 Pandemic Period: Reflections of Integrated Oncology Clinical Services from India

AbstractEver since the outbreak of COVID-19, the global health care systems are overwhelmed to cope up with the rapidly evolving disease paradigm through implementation of action plans at societal and medical domains. As per the directives from the World Health Organization and learned professional organizations, the international governments and states have formulated different protocols to prevent disease spread, for diagnosis and treatment of the disease and associated comorbidities, and to educate citizens during this crisis phase. Health care services across the world followed a “prioritizing strategy” for hospital population wherein the non-COVID cases were given less focus. Many hospitals opted for a conscious staff-sparing strategy to minimize exposure and protection of clinically valuable staff. Oncology services across the world reported a decline in the provision of clinical services to patients. There were medical concerns such as missed diagnosis, delayed diagnosis, delayed treatment, stoppage of screening programs, and differed follow-ups during the last 2 years of pandemic. The multidisciplinary oncology teams aim to ensure that cancer patients in the continuum of integrated cancer care pathway get globally accepted standards of optimum care. However, Beauchamp's ethical principles of autonomy, beneficence, nonmaleficence, and distributive justice were arguably compromised during the pandemic period. The articles of UNESCO Universal Declaration on Bioethics and Human Rights (UDBHR) declaration were possibly violated in cancer patients as a vulnerable population. This article analyses the bioethical and human right concerns with respect to medical and societal domains in oncology during the COVID-19 pandemic period.

COVID-19 Across Pandemic Variant Periods: The Severe Acute Respiratory Infection-Preparedness (SARI-PREP) Study.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has evolved through multiple phases in the United States, with significant differences in patient centered outcomes with improvements in hospital strain, medical countermeasures, and overall understanding of the disease. We describe how patient characteristics changed and care progressed over the various pandemic phases; we also emphasize the need for an ongoing clinical network to improve the understanding of known and novel respiratory viral diseases. To describe how patient characteristics and care evolved across the various COVID-19 pandemic periods in those hospitalized with viral severe acute respiratory infection (SARI). Severe Acute Respiratory Infection-Preparedness (SARI-PREP) is a Centers for Disease Control and Prevention Foundation-funded, Society of Critical Care Medicine Discovery-housed, longitudinal multicenter cohort study of viral pneumonia. We defined SARI patients as those hospitalized with laboratory-confirmed respiratory viral infection and an acute syndrome of fever, cough, and radiographic infiltrates or hypoxemia. We collected patient-level data including demographic characteristics, comorbidities, acute physiologic measures, serum and respiratory specimens, therapeutics, and outcomes. Outcomes were described across four pandemic variant periods based on a SARS-CoV-2 sequenced subsample: pre-Delta, Delta, Omicron BA.1, and Omicron post-BA.1. Multicenter cohort of adult patients admitted to an acute care ward or ICU from seven hospitals representing diverse geographic regions across the United States. Patients with SARI caused by infection with respiratory viruses. Eight hundred seventy-four adult patients with SARI were enrolled at seven study hospitals between March 2020 and April 2023. Most patients (780, 89%) had SARS-CoV-2 infection. Across the COVID-19 cohort, median age was 60 years (interquartile range, 48.0-71.0 yr) and 66% were male. Almost half (430, 49%) of the study population belonged to underserved communities. Most patients (76.5%) were admitted to the ICU, 52.5% received mechanical ventilation, and observed hospital mortality was 25.5%. As the pandemic progressed, we observed decreases in ICU utilization (94% to 58%), hospital length of stay (median, 26.0 to 8.5 d), and hospital mortality (32% to 12%), while the number of comorbid conditions increased. We describe increasing comorbidities but improved outcomes across pandemic variant periods, in the setting of multiple factors, including evolving care delivery, countermeasures, and viral variants. An understanding of patient-level factors may inform treatment options for subsequent variants and future novel pathogens.

Investigation of social isolation and depression in female employees with urinary incontinence during the COVID-19 pandemic period.

Urinary incontinence (UI) affects almost one-third of adult women. This is often taken as a section of the aging process and incurable In general, women perceive UI as more of a social issue and a taboo rather than a medical problem; they are reluctant to discuss the matter or seek assistance. This research was conducted to investigate the level of social isolation and depression in female employees with UI during the COVID-19 pandemic period. The study was done with 533 paticipant. The study data were done using the Nottingham Health Profile Social Isolation Scale (NHPSIS), and Beck Depression Inventory (BDI). The total scores of the NHPSIS and BDI were found to be 18.55±3.3 (minimum = 5, maximum = 25) and 49.22±11.4 (minimum = 12, maximum = 60), respectively. In the Pearson correlation analysis, a strong, statistically significant, and positive correlation was discovered between NHPSIS and the average BDI total scores among women. The level of depression and social isolation were obtained to be high among UI women who had a mix UI, high frequencies of UI, belong to higher age groups, singles, and high body mass index. It was showed that the levels of depression and social isolation scores were showed to be high in women had UI.