Unsupervised Clustering and Binary Classification Analysis for Predicting COVID Syndrome (LONG COVID) in US Adults

Objectives: This study investigated the risk factors of developing COVID Syndrome and identified potential disease profiles that may exist among those who have contracted COVID-19. Method(s): Data on 13,953 adults who had experienced COVID-19 at any time were analyzed from the 2022 US National Health and Wellness Survey. XGBoost binary classification with 10-fold cross-validation was used to predict long COVID among those who reported experiencing COVID-19 and to extract feature importance. Synthetic minority oversampling technique (SMOTE) was used to address class imbalance in the outcome variable. Variable selection was conducted based on SHAP values. Fifty variables including demographic characteristics, COVID-19 symptoms, comorbidities, and health characteristics were used in the final model. Parameters were tuned using AUC. Among the 2,665 respondents who were diagnosed with long COVID, k-medoids clustering with t-SNE dimensionality reduction was implemented to determine whether distinct symptom profiles exist. Average silhouette score was used to determine the optimal number of clusters. Result(s): The XGBoost binary classification for predicting long COVID among those with COVID-19 had an AUC of 0.9145, accuracy of 0.9072, sensitivity of 0.9630, specificity of 0.8328, and Brier score of 0.0928. The most important features in predicting long COVID were age, smoking habits, COVID-19 vaccination status, certain COVID-19 symptoms experienced, and certain comorbidities. Among those diagnosed with long COVID, the clustering analysis found nine unique clusters of symptoms. The cluster that experienced the most severe symptoms was older, female, lower income, lower vaccination rate, and had more comorbidities like asthma, chronic bronchitis, and allergies. Conclusion(s): In a broadly representative US adult population, XGBoost model identified a selection of risk factors for developing long COVID. K-medoids clustering identified clusters of patients that were at risk for developing severe symptoms.Copyright © 2023

Exploring Health Outcomes By Occupation: Using the National Health and Wellness Survey to Describe Differences in Self-Reported Occupation Profiles

Objectives: Health is distributed unequally by occupation (Ravesteijn,2013). This research aims to explore patient-reported outcomes by occupation profiles using the National Health and Wellness Survey (NHWS). Method(s): Data from the 2022 US NHWS included employed respondents at least 18 years of age with information on occupation profile, defined as 22 categories from the Bureau of Labor Statistics. Descriptive statistics were used to analyze respondent characteristics and outcomes such as COVID-19 diagnoses, healthcare resource use over the past six months, and work impairment as measured by the Work Productivity and Activity Impairment Questionnaire (WPAI). Result(s): A total of 35,789 respondents were employed and had occupation information. Respondents were predominantly white (62.0%) and male (53.9%). Sales and Related occupations had the greatest proportion of respondents reporting a COVID-19 diagnosis (16.1%) while Building and Grounds Cleaning and Maintenance had the lowest proportion (3.8%). Educational Instruction and Library had the most respondents reporting that they had received at least one dose of the COVID-19 vaccine (79.2%) while Farming, Fishing, and Forestry had the least respondents (52.9%). Life, Physical, and Social Science had the greatest COVID-19 vaccination rate over the past year (66.5%) while Farming, Fishing, and Forestry had the lowest (45.0%). Office and Administrative Support had the greatest proportion of respondents with a traditional healthcare provider visit (79.8%), but the lowest proportion with an emergency room (ER) visit (12.7%) or a hospitalization (8.1%). Farming, Fishing, and Forestry had the greatest proportion of respondents with an ER visit (41.6%) or hospitalization (41.6%). The greatest proportion of respondents with any overall work impairment or activity impairment was in Farming, Fishing, and Forestry (work: 91.1%, activity: 87.4%) while the lowest proportion was in Office and Administrative Support (work: 50.0%, activity: 53.3%). Conclusion(s): Certain occupation profiles consistently show higher impairment while others consistently show lower impairment.Copyright © 2023

Erratum: Increasing Resilience via the Use of Personal Data: Lessons from COVID-19 Dashboards on Data Governance for the Public Good (Data & Policy (2021) 3 (E29) DOI: 10.1017/dap.2021.27)

The authors apologise that Panel C of Figure 1, which refers to the highest level of education of the total sample population, was inadvertently excluded from the final published version of this article (Li, V and Yarime M., 2021). We include Figure 1 in its entirety here to correct the scholarly record, with legend below. © The Author(s), 2023. Published by Cambridge University Press on behalf of Applied Probability Trust.

A two-ward acute care hospital outbreak of SARS-CoV-2 delta variant including a point-source outbreak associated with the use of a mobile vital signs cart and sub-optimal doffing of personal protective equipment.

BACKGROUND: The arrival of the Delta variant of SARS-CoV-2 was associated with increased transmissibility and illness of greater severity. Reports of nosocomial outbreaks of Delta variant COVID-19 in acute care hospitals have been described but control measures varied widely. AIM: Epidemiological investigation of a linked two-ward COVID-19 Delta variant outbreak was conducted to elucidate its source, risk factors, and control measures. METHODS: Investigations included epidemiologic analysis, detailed case review serial SARS-CoV-2 reverse transcriptase-polymerase chain reaction (RT-PCR) testing of patients and healthcare workers (HCWs), viral culture, environmental swabbing, HCW-unaware personal protective equipment (PPE) audits, ventilation assessments, and the use of whole genome sequencing (WGS). FINDINGS: This linked two-ward outbreak resulted in 17 patient and 12 HCW cases, despite an 83% vaccination rate. In this setting, suboptimal adherence and compliance to PPE protocols, suboptimal hand hygiene, multi-bedded rooms, and a contaminated vital signs cart with potential fomite or spread via the hands of HCWs were identified as significant risk factors for nosocomial COVID-19 infection. Sudden onset of symptoms, within 72 h, was observed in 79% of all Ward 2 patients, and 93% of all cases (patients and HCWs) on Ward 2 occurred within one incubation period, consistent with a point-source outbreak. RT-PCR assays showed low cycle threshold (CT) values, indicating high viral load from environmental swabs including the vital signs cart. WGS results with ≤3 SNP differences between specimens were observed. CONCLUSION: Outbreaks on both wards settled rapidly, within 3 weeks, using a `back-to-basics' approach without extraordinary measures or changes to standard PPE requirements. Strict adherence to recommended PPE, hand hygiene, education, co-operation from HCWs, including testing and interviews, and additional measures such as limiting movement of patients and staff temporarily were all deemed to have contributed to prompt resolution of the outbreak.

The COVID-19 Pandemic and U.S. Aviation: System Adaptation and Performance Impact

The COVID-19 pandemic drastically impacted nearly all aspects of life throughout the world during 2020. It had a particularly severe impact on air transportation with U.S. demand initially dropping by over 90%. In this paper, we investigate the impact on the performance of the U.S. domestic air transportation system. We analyze both the changes in the volume and characteristics of flight operations and also changes in system performance metrics. We also discuss various adjustments made by the Federal Aviation Administration (FAA) both to take advantage of reduced system congestions and also to cope with COVID-19 infections among controllers. © ATM 2021. All rights reserved.

COVID-19, policy change, and post-pandemic data governance: a case analysis of contact tracing applications in East Asia

In an era of digitalization, governments often turn to digital solutions for pressing policy issues, and the use of digital contact tracing and quarantine enforcement for COVID-19 is no exception. The long-term impacts of the digital solutions, however, cannot be taken for granted. The development and use of data tools for pandemic control, for example, may have potentially detrimental and irreversible impacts on data governance and, more broadly, society, in the long run. In this paper, we aim to explore the extent to which COVID-19 and digital contact tracing have led to policy change in data governance, if at all, and what the implications of such change would be for a post-COVID world. We compare the use of contact tracing and monitoring applications across mainland China, Hong Kong, and Singapore to illustrate both the enormous benefits and potential risks arising from the design of contact tracing applications and the involvement of stakeholders in the various stages of the policy cycle to combat the COVID-19 pandemic. We argue that, while COVID-19 has not changed the nature of issues, such as public trust in data governance, the increasing involvement of big tech in data policies, and data privacy risks, it has exacerbated those issues through the accelerated adoption of data technologies.

Can GPR4 Be a Potential Therapeutic Target for COVID-19?

Coronavirus disease 19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first emerged in late 2019 and has since rapidly become a global pandemic. SARS-CoV-2 infection causes damages to the lung and other organs. The clinical manifestations of COVID-19 range widely from asymptomatic infection, mild respiratory illness to severe pneumonia with respiratory failure and death. Autopsy studies demonstrate that diffuse alveolar damage, inflammatory cell infiltration, edema, proteinaceous exudates, and vascular thromboembolism in the lung as well as extrapulmonary injuries in other organs represent key pathological findings. Herein, we hypothesize that GPR4 plays an integral role in COVID-19 pathophysiology and is a potential therapeutic target for the treatment of COVID-19. GPR4 is a pro-inflammatory G protein-coupled receptor (GPCR) highly expressed in vascular endothelial cells and serves as a "gatekeeper" to regulate endothelium-blood cell interaction and leukocyte infiltration. GPR4 also regulates vascular permeability and tissue edema under inflammatory conditions. Therefore, we hypothesize that GPR4 antagonism can potentially be exploited to mitigate the hyper-inflammatory response, vessel hyper-permeability, pulmonary edema, exudate formation, vascular thromboembolism and tissue injury associated with COVID-19.