Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 328
Filter
1.
J Nurs Adm ; 52(12): 634-635, 2022 Dec 01.
Article in English | MEDLINE | ID: covidwho-2135768

ABSTRACT

In this column, 2 recognized healthcare leaders discuss the stresses experienced by nurses in today's workforce and offer suggestions for the use of technology in improving nurse engagement as well as the quality of patient care.


Subject(s)
Workflow , Humans
2.
Medicine (Baltimore) ; 101(45): e31740, 2022 Nov 11.
Article in English | MEDLINE | ID: covidwho-2115861

ABSTRACT

This paper mainly discusses how to do a good job of daily biosafety protection measures in clinical microbiology laboratories during the epidemic of COVID-19, so as to ensure the safe development of routine clinical microbiology testing items. According to the microbiological and epidemiological characteristics of the novel coronavirus, this paper analyzed the potential risks of the laboratory from the perspective of personal protection before, during, and after testing. Combined with the actual work situation, the improved biosafety protection measures and optimized work flow are introduced to ensure the safety of medical staff and the smooth development of daily work. Danyang People's Hospital of Jiangsu Province, clinical microbiology laboratory of clinical laboratory in strict accordance with the relevant laws and regulations, technical specifications and the expert consensus, combined with their own conditions, the biosafety measures to perfect the working process was optimized, effectively prevent the laboratory exposure, and maintain strict working condition for a long time, continue to improve. We found that the biosafety protection measures of clinical microbiology laboratory have good prevention and control effect on preventing infection of medical staff, which will greatly reduce the risk of infection of medical staff, form good working habits, and provide reference for biosafety protection of microbiology laboratory during the epidemic of COVID-19.


Subject(s)
COVID-19 , Clinical Laboratory Services , Humans , Containment of Biohazards , Laboratories , Workflow
3.
BMC Health Serv Res ; 22(1): 1301, 2022 Oct 29.
Article in English | MEDLINE | ID: covidwho-2098340

ABSTRACT

BACKGROUND: Breast cancer clinics across the UK have long been struggling to cope with high demand. Novel risk prediction tools - such as the PinPoint test - could help to reduce unnecessary clinic referrals. Using early data on the expected accuracy of the test, we explore the potential impact of PinPoint on: (a) the percentage of patients meeting the two-week referral target, and (b) the number of clinic 'overspill' appointments generated (i.e. patients having to return to the clinic to complete their required investigations). METHODS: A simulation model was built to reflect the annual flow of patients through a single UK clinic. Due to current uncertainty around the exact impact of PinPoint testing on standard care, two primary scenarios were assessed. Scenario 1 assumed complete GP adherence to testing, with only non-referred cancerous cases returning for delayed referral. Scenario 2 assumed GPs would overrule 20% of low-risk results, and that 10% of non-referred non-cancerous cases would also return for delayed referral. A range of sensitivity analyses were conducted to explore the impact of key uncertainties on the model results. Service reconfiguration scenarios, removing individual weekly clinics from the clinic schedule, were also explored. RESULTS: Under standard care, 66.3% (95% CI: 66.0 to 66.5) of patients met the referral target, with 1,685 (1,648 to 1,722) overspill appointments. Under both PinPoint scenarios, > 98% of patients met the referral target, with overspill appointments reduced to between 727 (707 to 746) [Scenario 1] and 886 (861 to 911) [Scenario 2]. The reduced clinic demand was sufficient to allow removal of one weekly low-capacity clinic [N = 10], and the results were robust to sensitivity analyses. CONCLUSION: The findings from this early analysis indicate that risk prediction tools could have the potential to alleviate pressure on cancer clinics, and are expected to have increased utility in the wake of heightened pressures resulting from the COVID-19 pandemic. Further research is required to validate these findings with real world evidence; evaluate the broader clinical and economic impact of the test; and to determine outcomes and risks for patients deemed to be low-risk on the PinPoint test and therefore not initially referred.


Subject(s)
Breast Neoplasms , COVID-19 , Humans , Female , Waiting Lists , Breast Neoplasms/diagnosis , Pandemics , Workflow , COVID-19/epidemiology , Referral and Consultation , Risk Assessment
4.
Best Pract Res Clin Anaesthesiol ; 36(2): 299-310, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-2082760

ABSTRACT

Bottlenecks limit the maximum output of a system and indicate operational congestion points in process management. Bottlenecks also affect perioperative care and include dimensions such as infrastructure, architectural design and limitations, inefficient equipment and material supply chains, communication-related limitations on the flow of information, and patient- or staff-related factors. Improvement of workflow is, therefore, becoming a priority in most healthcare settings. We provide an overview of bottleneck management in the perioperative setting and introduce dimensions, including aligned strategic decision-making, tactical planning, and operational adjustments.


Subject(s)
Perioperative Care , Humans , Workflow
5.
J Laryngol Otol ; 136(12): 1314-1319, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2069839

ABSTRACT

OBJECTIVE: To document changes in evaluation protocols for acute invasive fungal sinusitis during the coronavirus disease 2019 pandemic, and to analyse concordance between clinical and histopathological diagnoses based on new practice guidelines. METHODS: Protocols for the evaluation of patients with suspected acute invasive fungal sinusitis both prior and during the coronavirus disease 2019 period are described. A retrospective analysis of patients presenting with suspected acute invasive fungal sinusitis from 1 May to 30 June 2021 was conducted, with assessment of the concordance between clinical and final diagnoses. RESULTS: Among 171 patients with high clinical suspicion, 160 (93.6 per cent) had a final histopathological diagnosis of invasive fungal sinusitis, concordant with the clinical diagnosis, with sensitivity of 100 per cent, positive predictive value of 93.6 per cent and negative predictive value of 100 per cent. CONCLUSION: The study highlights a valuable screening tool with good accuracy, involving emphasis on 'red flag' signs in high-risk populations. This could be valuable in situations demanding the avoidance of aerosol-generating procedures and in resource-limited settings facilitating early referral to higher level care centres.


Subject(s)
COVID-19 , Invasive Fungal Infections , Sinusitis , Humans , Retrospective Studies , Pandemics , Workflow , Sinusitis/diagnosis , Sinusitis/therapy , Sinusitis/microbiology , Invasive Fungal Infections/diagnosis , Acute Disease
6.
PLoS Comput Biol ; 18(10): e1010495, 2022 10.
Article in English | MEDLINE | ID: covidwho-2054249

ABSTRACT

COVID-19 patients display a wide range of disease severity, ranging from asymptomatic to critical symptoms with high mortality risk. Our ability to understand the interaction of SARS-CoV-2 infected cells within the lung, and of protective or dysfunctional immune responses to the virus, is critical to effectively treat these patients. Currently, our understanding of cell-cell interactions across different disease states, and how such interactions may drive pathogenic outcomes, is incomplete. Here, we developed a generalizable and scalable workflow for identifying cells that are differentially interacting across COVID-19 patients with distinct disease outcomes and use this to examine eight public single-cell RNA-seq datasets (six from peripheral blood mononuclear cells, one from bronchoalveolar lavage and one from nasopharyngeal), with a total of 211 individual samples. By characterizing the cell-cell interaction patterns across epithelial and immune cells in lung tissues for patients with varying disease severity, we illustrate diverse communication patterns across individuals, and discover heterogeneous communication patterns among moderate and severe patients. We further illustrate patterns derived from cell-cell interactions are potential signatures for discriminating between moderate and severe patients. Overall, this workflow can be generalized and scaled to combine multiple scRNA-seq datasets to uncover cell-cell interactions.


Subject(s)
COVID-19 , Cell Communication , Humans , Leukocytes, Mononuclear , SARS-CoV-2 , Workflow
7.
J Digit Imaging ; 35(4): 796-811, 2022 08.
Article in English | MEDLINE | ID: covidwho-2048330

ABSTRACT

Developing an enterprise approach to imaging technology rather than a radiology focus has recently increased. The communicator needs to be aware of this shift.The Middle East countries participated in the survey have confirmed the following major benefits of Medical Image Exchange: ✔ Fast access to both image and report ✔ Enable tele-services for second opinion, consulting and reporting ✔ Improve patient journey, workflow and diagnosis ✔ Allowed more patient engagement to be in place The Middle East countries that participated in this survey have agreed on the following shared challenges regarding Medical Imaging Exchange: ✔ Lack of enterprise imaging governance at the early stage of implementation. It will organize the who, when, and how. In addition, any fees and or payment involved for physicians ✔ Infrastructure availability to handle such large volume of data. Growing from mega-byte to petabyte per year is challenge for infrastructure. Cloud against On Premises-Installation implementation model ✔ Interoperability and integration to connect multi specialties from different systems. In addition, how far existing systems are ready for that. A standard-based framework is mature for image exchange, but what follows for other domains? There is a need to move beyond radiology images so as to include images from pathology, ophthalmology, and dermatology There are other countries in the region requiring guidance, support, and funding to move forward from the compact disc into internet-based interoperable image exchange. This should be considered part of the World Health Organization and the United Nation development to the region in the healthcare sector.


Subject(s)
Radiology Information Systems , Radiology , Diagnostic Imaging , Humans , Radiography , Workflow
8.
Int J Mol Sci ; 23(17)2022 Aug 30.
Article in English | MEDLINE | ID: covidwho-2023749

ABSTRACT

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.


Subject(s)
Metagenome , Metagenomics , Computational Biology , Humans , Whole Genome Sequencing , Workflow
9.
Stud Health Technol Inform ; 296: 58-65, 2022 Aug 17.
Article in English | MEDLINE | ID: covidwho-2022597

ABSTRACT

Within the scope of the two NUM projects CODEX and RACOON we developed a preliminary technical concept for documenting clinical and radiological COVID-19 data in a collaborative approach and its preceding findings of a requirement analysis. At first, we provide an overview of NUM and its two projects CODEX and RACOON including the GECCO data set. Furthermore, we demonstrate the foundation for the increased collaboration of both projects, which was additionally supported by a survey conducted at University Hospital Frankfurt. Based on the survey results mint Lesion™, developed by Mint Medical and used at all project sites within RACOON, was selected as the "Electronic Data Capture" (EDC) system for CODEX. Moreover, to avoid duplicate entry of GECCO data into both EDC systems, an early effort was made to consider a collaborative and efficient technical approach to reduce the workload for the medical documentalists. As a first effort we present a preliminary technical concept representing the current and possible future data workflow of CODEX and RACOON. This concept includes a software component to synchronize GECCO data sets between the two EDC systems using the HL7 FHIR standard. Our first approach of a collaborative use of an EDC system and its medical documentalists could be beneficial in combination with the presented synchronization component for all participating project sites of CODEX and RACOON with regard to an overall reduced documentation workload.


Subject(s)
COVID-19 , Animals , Documentation , Humans , Raccoons , Radiography , Workflow
10.
J Emerg Nurs ; 48(6): 666-677, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2007836

ABSTRACT

INTRODUCTION: The average length of stay of a fast-track area of a large urban hospital was excessively long, which affected the patient experience and the rate at which patients left without being seen. One approach to reducing average length of stay is to create nurse standard work. Nurse standard work was a defined set of process and procedures that reduce variability within a nurse's workflow. METHODS: Nurse standard work was created by a team of nurses assisted by management engineering using lean methodology and A3 problem solving. Data were gathered about average length of stay and left without being seen for patients in the emergency department fast-track area of an urban emergency department from October 2018 to June 2020. This period includes 5 months before the intervention start, 4 months during nurse standard work implementation, 9 months using nurse standard work before the unit was repurposed during COVID-19, and 3 months during COVID-19. RESULTS: Nurse standard work helped reduce average length of stay in the emergency department fast-track area from 205 minutes before project initiation to 150.4 minutes in the 7 months after implementing nurse standard work. The time spent walking for supplies was reduced from 422 and 272 seconds before nurse standard work to 25 and 30 seconds for the nurse technician and nurse, respectively, after nurse standard work. Left without being seen was decreased from 4.7% in October of 2018 to 0.7% by March of 2020. DISCUSSION: Nurse standard work reduced the amount of time that nurses spent performing support tasks and reduced delays in providing patient care, which then allowed more time for nurses to interact directly with patients. Nurse standard work provides a clear task sequence that eliminates delays in treating patients, but it also allows for fast identification of delays that do occur and simplifies problem solving to eliminate reoccurrence of delays. Therefore, nurse standard work is an essential component of efforts to reduce patient average length of stay in health care processes and reduce left without being seen to the national standard of less than 2%.


Subject(s)
COVID-19 , Quality Improvement , Humans , Length of Stay , Emergency Service, Hospital , Workflow
11.
BMC Med Inform Decis Mak ; 22(1): 217, 2022 08 13.
Article in English | MEDLINE | ID: covidwho-2002167

ABSTRACT

BACKGROUND: Primary care providers face challenges in recognizing and controlling hypertension in patients with chronic kidney disease (CKD). Clinical decision support (CDS) has the potential to aid clinicians in identifying patients who could benefit from medication changes. This study designed an alert to control hypertension in CKD patients using an iterative human-centered design process. METHODS: In this study, we present a human-centered design process employing multiple methods for gathering user requirements and feedback on design and usability. Initially, we conducted contextual inquiry sessions to gather user requirements for the CDS. This was followed by group design sessions and one-on-one formative think-aloud sessions to validate requirements, obtain feedback on the design and layout, uncover usability issues, and validate changes. RESULTS: This study included 20 participants. The contextual inquiry produced 10 user requirements which influenced the initial alert design. The group design sessions revealed issues related to several themes, including recommendations and clinical content that did not match providers' expectations and extraneous information on the alerts that did not provide value. Findings from the individual think-aloud sessions revealed that participants disagreed with some recommended clinical actions, requested additional information, and had concerns about the placement in their workflow. Following each step, iterative changes were made to the alert content and design. DISCUSSION: This study showed that participation from users throughout the design process can lead to a better understanding of user requirements and optimal design, even within the constraints of an EHR alerting system. While raising awareness of design needs, it also revealed concerns related to workflow, understandability, and relevance. CONCLUSION: The human-centered design framework using multiple methods for CDS development informed the creation of an alert to assist in the treatment and recognition of hypertension in patients with CKD.


Subject(s)
Decision Support Systems, Clinical , Hypertension , Renal Insufficiency, Chronic , Feedback , Humans , Hypertension/complications , Hypertension/therapy , Renal Insufficiency, Chronic/complications , Renal Insufficiency, Chronic/therapy , Workflow
12.
Philos Trans A Math Phys Eng Sci ; 380(2233): 20210300, 2022 Oct 03.
Article in English | MEDLINE | ID: covidwho-1992458

ABSTRACT

Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of 'following the science' are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline. Although developed during the COVID-19 pandemic, it allows easy annotation of any data as they are consumed by analyses, or conversely traces the provenance of scientific outputs back through the analytical or modelling source code to primary data. Such a tool provides a mechanism for the public, and fellow scientists, to better assess scientific evidence by inspecting its provenance, while allowing scientists to support policymakers in openly justifying their decisions. We believe that such tools should be promoted for use across all areas of policy-facing research. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.


Subject(s)
COVID-19 , Data Management , Humans , Pandemics , Software , Workflow
13.
Nat Commun ; 13(1): 4678, 2022 08 09.
Article in English | MEDLINE | ID: covidwho-1984385

ABSTRACT

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.


Subject(s)
COVID-19 , Neoplasms , COVID-19/genetics , Computational Biology , Humans , Neoplasms/genetics , Software , Transcriptome , Workflow
14.
J Appl Clin Med Phys ; 23(11): e13742, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-1976679

ABSTRACT

BACKGROUND: The Ottawa Hospital's Radiation Oncology program maintains the Incident Learning System (ILS)-a quality assurance program that consists of report submissions of errors and near misses arising from all major domains of radiation. In March 2020, the department adopted workflow changes to optimize patient and provider safety during the COVID-19 pandemic. PURPOSE: In this study, we analyzed the number and type of ILS submissions pre- and postpandemic precautions to assess the impact of COVID-19-related workflow changes. METHODS: ILS data was collected over six one-year time periods between March 2016 and March 2021. For all time periods, the number of ILS submissions were counted. Each ILS submission was analyzed for the specific treatment domain from which it arose and its root cause, explaining the impetus for the error or near miss. RESULTS: Since the onset of COVID-19-related workflow changes, the total number of ILS submissions have reduced by approximately 25%. Similarly, there were 30% fewer ILS submissions per number of treatment courses compared to prepandemic data. There was also an increase in the proportion of "treatment planning" ILS submissions and a 50% reduction in the proportion of "decision to treat" ILS submissions compared to previous years. Root cause analysis revealed there were more incidents attributable to "poor, incomplete, or unclear documentation" during the pandemic year. CONCLUSIONS: COVID-19 workflow changes were associated with fewer ILS submissions, but a relative increase in submissions stemming from poor documentation and communication. It is imperative to analyze ILS submission data, particularly in a changing work environment, as it highlights the potential and realized mistakes that impact patient and staff safety.


Subject(s)
COVID-19 , Radiation Oncology , Humans , Workflow , COVID-19/epidemiology , Pandemics , Risk Management
16.
BMC Emerg Med ; 22(1): 136, 2022 07 26.
Article in English | MEDLINE | ID: covidwho-1962739

ABSTRACT

OBJECTIVE: We aimed to evaluate door-to-puncture time (DPT) and door-to-recanalization time (DRT) without directing healthcare by neuro-interventionalist support in the emergency department (ED) by workflow optimization and improving patients' outcomes. METHODS: Records of 98 consecutive ischemic stroke patients who had undergone endovascular therapy (EVT) between 2018 to 2021 were retrospectively reviewed in a single-center study. Patients were divided into three groups: pre-intervention (2018-2019), interim-intervention (2020), and post-intervention (January 1st 2021 to August 16th, 2021). We compared door-to-puncture time, door-to-recanalization time (DRT), puncture-to-recanalization time (PRT), last known normal time to-puncture time (LKNPT), and patient outcomes (measured by 3 months modified Rankin Scale) between three groups using descriptive statistics. RESULTS: Our findings indicate that process optimization measures could shorten DPT, DRT, PRT, and LKNPT. Median LKNPT was shortened by 70 min from 325 to 255 min(P < 0.05), and DPT was shortened by 119 min from 237 to 118 min. DRT shortened by 132 min from 338 to 206 min, and PRT shortened by 33 min from 92 to 59 min from the pre-intervention to post-intervention groups (all P < 0.05). Only 21.4% of patients had a favorable outcome in the pre-intervention group as compared to 55.6% in the interventional group (P= 0.026). CONCLUSION: This study demonstrated that multidisciplinary cooperation was associated with shortened DPT, DRT, PRT, and LKNPT despite challenges posed to the healthcare system such as the COVID-19 pandemic. These practice paradigms may be transported to other stroke centers and healthcare providers to improve endovascular time metrics and patient outcomes.


Subject(s)
COVID-19 , Ischemic Stroke , Stroke , Humans , Ischemic Stroke/surgery , Pandemics , Punctures , Retrospective Studies , Stroke/therapy , Thrombectomy , Time-to-Treatment , Treatment Outcome , Workflow
17.
Methods Mol Biol ; 2453: 447-476, 2022.
Article in English | MEDLINE | ID: covidwho-1935747

ABSTRACT

High-throughput sequencing of adaptive immune receptor repertoires (AIRR, i.e., IG and TR ) has revolutionized the ability to study the adaptive immune response via large-scale experiments. Since 2009, AIRR sequencing (AIRR-seq) has been widely applied to survey the immune state of individuals (see "The AIRR Community Guide to Repertoire Analysis" chapter for details). One of the goals of the AIRR Community is to make the resulting AIRR-seq data FAIR (Findable, Accessible, Interoperable, and Reusable) (Wilkinson et al. Sci Data 3:1-9, 2016), with a primary goal of making it easy for the research community to reuse AIRR-seq data (Breden et al. Front Immunol 8:1418, 2017; Scott and Breden. Curr Opin Syst Biol 24:71-77, 2020). The basis for this is the MiAIRR data standard (Rubelt et al. Nat Immunol 18:1274-1278, 2017). For long-term preservation, it is recommended that researchers store their sequence read data in an INSDC repository. At the same time, the AIRR Community has established the AIRR Data Commons (Christley et al. Front Big Data 3:22, 2020), a distributed set of AIRR-compliant repositories that store the critically important annotated AIRR-seq data based on the MiAIRR standard, making the data findable, interoperable, and, because the data are annotated, more valuable in its reuse. Here, we build on the other AIRR Community chapters and illustrate how these principles and standards can be incorporated into AIRR-seq data analysis workflows. We discuss the importance of careful curation of metadata to ensure reproducibility and facilitate data sharing and reuse, and we illustrate how data can be shared via the AIRR Data Commons.


Subject(s)
Information Dissemination , Research Design , High-Throughput Nucleotide Sequencing , Humans , Information Dissemination/methods , Reproducibility of Results , Workflow
18.
Stud Health Technol Inform ; 290: 1136-1137, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1933599

ABSTRACT

In 2020, a pandemic forced the entire world to adapt to a new scenario. The objective of this study was to know how Health Information Systems were adapted driven by the pandemic of COVID. 12 CIOS of healthcare organizations were interviewed and the interviews were classified according to the dimensions of a sociotechnical model: Infrastructure, Clinical Content, Human Computer Interface, People, Workflow and Communication, Organizational Characteristics and Internal Policies, Regulations, and Measurement and Monitoring. Adaptation to the Pandemic involved social, organizational and cultural rather than merely technical aspects in private organizations with mature and stable Health Information Systems.


Subject(s)
COVID-19 , Health Information Systems , Humans , Pandemics , User-Computer Interface , Workflow
19.
Funct Integr Genomics ; 22(5): 1003-1029, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1919814

ABSTRACT

Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 2 , Computational Biology , Diabetes Mellitus, Type 2/genetics , Humans , Insulin , Meta-Analysis as Topic , Systematic Reviews as Topic , Workflow
20.
Health Econ ; 31(9): 2050-2071, 2022 09.
Article in English | MEDLINE | ID: covidwho-1905855

ABSTRACT

Governments worldwide have issued massive amounts of debt to inject fiscal stimulus during the COVID-19 pandemic. This paper analyzes fiscal responses to an epidemic, in which interactions at work increase the risk of disease and mortality. Fiscal policies, which are designed to borrow against the future and provide transfers to individuals suffering economic hardship, can facilitate consumption smoothing while reduce hours worked and hence mitigate infections. We examine the optimal fiscal policy and characterize the condition under which fiscal policy improves social welfare. We then extend the model analyzing the static and dynamic pecuniary externalities under scale economies-the decrease in labor supply during the epidemic lowers the contemporaneous average wage rate while enhances the post-epidemic workforce health and productivity. We suggest that fiscal policy may not work effectively unless the government coordinates working time, and the optimal size of public debt is affected by production technology and disease severity and transmissibility.


Subject(s)
COVID-19/economics , COVID-19/epidemiology , Fiscal Policy , Pandemics/economics , Social Welfare/economics , COVID-19/prevention & control , Efficiency , Humans , Pandemics/prevention & control , Poverty , Salaries and Fringe Benefits , Time Factors , Workflow , Workforce/economics , Workload/economics
SELECTION OF CITATIONS
SEARCH DETAIL