bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rising Through the Pandemic: A scoping review of quality improvement in public health during the COVID-19 pandemic
Authors: Yin X. Cindy , Pang Michelle , Law Madelyn , Guerra Fiona , O’Sullivan Tracey , Laxer Rachel E. , Schwartz Brian , Khan Yasmin 
Published: June 2021

AbstractBackgroundThe COVID-19 pandemic generated a growing interest in and need for evidence-based tools to facilitate the implementation of emergency management strategies within public health practice. Quality improvement (QI) has been identified as a key framework and philosophy to guide organizational emergency response efforts; however, the nature and extent to which it has been used in public health settings during the COVID-19 pandemic remains unclear.MethodsWe conducted a scoping review of literature published January 2020 – February 2021 and focused on the topic of QI at public health agencies during the COVID-19 pandemic. The search was conducted on four bibliographic databases, in addition to a supplementary grey literature search using custom Google search engines and targeted website search methods. Of the 1,878 peer-reviewed articles assessed, 15 records met the inclusion criteria. An additional 11 relevant records were identified during the grey literature search, for a total of 26 records included in the scoping review.ResultsRecords were organized into five topics: 1) collaborative problem solving and analysis with stakeholders; 2) supporting learning and capacity building in QI; 3) learning from past emergencies; 4) implementing QI methods during COVID-19; and 5) evaluating performance using frameworks/indicators.ConclusionsThe literature indicates that QI-oriented activities are occurring at the organizational and program levels to enhance COVID-19 response. To optimize the benefits that QI approaches and methodologies may offer, it is important for public health agencies to focus on both widespread integration of QI as part of an organization’s management philosophy and culture, as well as project level activities at all stages of the emergency management cycle.
COVID 19, Consumption and Inequality: A Systematic Analysis of Rural Population of India
Authors: Kapoor Mudit , Ravi Shamika , Kumar A.K. Shiva 
Published: June 2021

SummaryBackgroundCOVID19 pandemic has had major impact on consumption levels and inequality within India. Government policy interventions have targeted poor households for cash and food transfers. It is important, however, to study the impact of the pandemic on consumption levels of non-poor in India, and in particular the middle class. In this paper, we aim to quantify the changes in consumption levels and inequality over time, across all groups of rural households in India.MethodsWe analyze three rounds of COVID 19-related shock surveys between May and September 2020. These surveys cover rural households of six large states in India and are representative of more than 442 million (52% of India’s rural population).FindingsIn the early phase of the pandemic, it was the bottom 40% of households that experienced the most severe decline in consumption. But as the pandemic deepened, consumption declined across all classes of households. Besides the poorest, it was particularly severe for the middle class (defined as 40%-80%). We also measure consumption inequality over time and find that the Gini coefficient of consumption distribution increased significantly.InterpretationIn addition to focusing on poor households, policy responses to alleviate people’s sufferings would have to consider a more comprehensive boost to consumption and compensate for the reduced consumption among middle class families as well.FundingNone.
The Impact of Face-Masks on Total Mortality Heterogenous Effects by Gender and Age
Authors: De Giorgi Giacomo , Speziali Maria Maddalena , Michalik Felix 
Published: June 2021

AbstractGovernments around the world have been implementing several non-pharmaceutical interventions (NPIs) to fight Covid-19 spread and its associated mortality. We estimate the causal impact of mandatory face-mask wearing policy in public places on (total) mortality in Switzerland. We exploit the staggered introduction of the policy across Swiss cantons using a Difference-in-Difference and an event study approach. We find that the extension of compulsory mask wearing to public places has an heterogeneous impact on mortality, with small positive effects on male mortality entirely driven by older age-cohorts (90+). Finally, we show that adding contact tracing and stricter distancing to compulsory face-mask policy does not lead to better results in terms of mortality.
Inequalities in healthcare disruptions during the Covid-19 pandemic: Evidence from 12 UK population-based longitudinal studies
Authors: Maddock Jane , Parsons Sam , Di Gessa Giorgio , Green Michael J. , Thompson Ellen J. , Stevenson Anna J. , Kwong Alex S.F. , McElroy Eoin , Santorelli Gillian , Silverwood Richard J. , Captur Gabriella , Chaturvedi Nish , Steves Claire J. , Steptoe Andrew , Patalay Praveetha , Ploubidis George B. , Katikireddi Srinivasa Vittal 
Published: June 2021

AbstractBackgroundHealth systems worldwide have faced major disruptions due to COVID-19 which could exacerbate health inequalities. The UK National Health Service (NHS) provides free healthcare and prioritises equity of delivery, but the pandemic may be hindering the achievement of these goals. We investigated associations between multiple social characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions in over 65,000 participants across twelve UK longitudinal studies.MethodsParticipants reported disruptions from March 2020 up to late January 2021. Associations between social characteristics and three types of self-reported healthcare disruption (medication access, procedures, appointments) and a composite of any of these were assessed in logistic regression models, adjusting for age, sex and ethnicity where relevant. Random-effects meta-analysis was conducted to obtain pooled estimates.ResultsPrevalence of disruption varied across studies; between 6.4% (TwinsUK) and 31.8 % (Understanding Society) of study participants reported any disruption. Females (Odd Ratio (OR): 1.27 [95%CI: 1.15,1.40]; I2=53%), older persons (e.g. OR: 1.39 [1.13,1.72]; I2=77% for 65-75y vs 45-54y), and Ethnic minorities (excluding White minorities) (OR: 1.19 [1.05,1.35]; I2=0% vs White) were more likely to report healthcare disruptions. Those in a more disadvantaged social class (e.g. OR: 1.17 [1.08, 1.27]; I2=0% for manual/routine vs managerial/professional) were also more likely to report healthcare disruptions, but no clear differences were observed by education levels.ConclusionThe COVID-19 pandemic has led to unequal healthcare disruptions, which, if unaddressed, could contribute to the maintenance or widening of existing health inequalities.
The impact of Covid-19 vaccination on the Italian healthcare system: a scenario analysis
Authors: Andrea Marcellusi , Gianluca Fabiano , Paolo Sciattella , Massimo Andreoni , Mennini Francesco S 
Published: June 2021

AbstractIntroductionThe objective of this study is to estimate the effects of the national immunisation strategy for Covid-19 in Italy on the national healthcare system.MethodsAn epidemiological scenario analysis was developed in order to simulate the impact of the Covid-19 pandemic on the Italian national healthcare system in 2021. Hospitalisations, ICU admissions and death rates were modelled based on 2020 data. We forecast the impact of the introduction of a primary prevention strategy on the national healthcare system by considering vaccine efficacy, availability of doses and potential population coverage over time.ResultsIn the absence of immunisation, between 57,000 and 63,000 additional deaths are forecast in 2021. Based on the assumptions underlying the two epidemiological scenarios from the 2020 data, our model predicts that cumulative hospital admissions in 2021 will range from 3.4 to 3.9 million. The deployment of vaccine immunisation has the potential to control the evolution of 2021 infections and avoid from 60 to 67 percent of deaths compared to not vaccinating.ConclusionsIn order to inform Italian policymakers on delivering a mass vaccination programme, this study highlights and detects some key factors that must be controlled to ensure that immunisation targets will be met in reasonable time.
Micro RNA-based regulation of genomics and transcriptomics of inflammatory cytokines in COVID-19
Authors: Khokhar Manoj , Tomo Sojit , Purohit Purvi 
Published: June 2021

AbstractBackgroundCoronavirus disease 2019 is characterized by the elevation of a wide spectrum of inflammatory mediators, which are associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future.MethodsThe cytokine regulating immune-expressed genes (CRIEG) was sorted from literature and the GEO microarray dataset. Their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, Gene Ontology, and pathways predicted by KEGG and Reactome pathways. Finally, the functional and regulatory features were analyzed and visualized through Cytoscape.ResultsSixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the MiRNA database yielded 10 (ten) miRNAs that are significantly involved in regulating these genes and their transcription factors.ConclusionAn in-silico representation of a network involving miRNAs, CRIEGs, and TF which take part in the inflammatory response in COVID-19 has been elucidated. These regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further to develop targeted therapeutic strategies and mechanistic validation.
Development and usability testing of two arts-based knowledge translation tools for parents about pediatric fever
Authors: Scott Shannon D. , Cunningham Chentel , Le Anne , Hartling Lisa 
Published: June 2021

AbstractFever is defined as an elevated body temperature greater or equal to 38 degrees celsius when measured via the ear canal. It is a common bodily response in children and is typically a benign process that is self-limiting. However, fever can be an anxiety provoking event for some parents because their child can look unwell and become irritable as a result. Past attempts at translating medical knowledge about fever and its management strategies into parent-friendly formats exist; however, parent misperceptions about definition and management persist despite these educational tools.Our research team employs patient engagement techniques to develop resources for parents to enhance the uptake of complex medical knowledge. First, our research group conducts qualitative interviews and knowledge synthesis of the literature. Following analysis, salient themes are used to develop a script and skeleton for our videos and infographics, respectively. Employing this same process, this paper discusses the development and usability testing of two digital tools for fever. Prototypes for the video and infographic were tested by parents in urban and remote emergency department (ED) waiting rooms. A total of 58 surveys were completed by parents. Overall, parents rated both the fever video and infographic favourably, suggesting that patient engaged research methods and digital formats are mediums that can facilitate knowledge transfer.
The effect of obesity-related traits on COVID-19 severe respiratory symptoms is mediated by socioeconomic status: a multivariable Mendelian randomization study
Authors: Cabrera-Mendoza Brenda , Wendt Frank R , Pathak Gita A , De Angelis Flavio , De Lillo Antonella , Koller Dora , Polimanti Renato 
Published: June 2021

AbstractBackgroundObesity has been associated with more severe clinical manifestations of coronavirus disease 2019 (COVID-19). However, this association can be affected by many correlates of these traits. Due to its large impact on human health, socioeconomic status (SES) could at least partially influence the association between obesity and COVID-19 severity. To estimate the independent effect of traits related to body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study analyzing the effect of obesity-related anthropometric traits on COVID-19 outcomes.MethodsApplying two-sample MR approaches, we evaluated the effects of body mass index (BMI), waist circumference (WC), hip circumference, (HIP) and waist-hip ratio (WHR) studied in up to 234,069 participants from the Genetic Investigation of ANthropometric Traits (GIANT) consortium with respect to three COVID-19 outcomes: severe respiratory COVID-19 (5,101 cases vs. 1,383,241 controls), hospitalized COVID-19 (9,986 cases vs. 1,877,672 controls), and COVID-19 infection (38,984 cases vs. 1,644,784 controls) obtained from the COVID-19 Host Genetics Initiative (HGI). Finally, to test the effect of SES using multivariable MR methods, we analyzed genetic data related to self-reported household income (HI) information from 286,301 UK Biobank (UKB) participants.ResultsBMI and WC were associated with severe respiratory COVID-19 (BMI: OR⍰=⍰1.68 p⍰=⍰0.0004; WC: OR⍰=⍰1.72, p⍰=⍰0.007) and COVID-19 hospitalization (BMI: OR=⍰1.62, p⍰=⍰1.35e-06; WC: OR⍰=⍰1.62, p⍰=⍰0.0001). Also, HIP influenced hospitalized COVID-19 (OR⍰=⍰1.31, p⍰=⍰0.012) and COVID-19 infection (OR⍰=⍰1.18, p⍰=⍰0.002). Conversely, HI was associated with lower odds of severe respiratory COVID-19 (OR⍰=⍰0.57, p⍰=⍰0.011) and hospitalized COVID-19 (OR⍰=⍰0.71, p⍰=⍰0.045). Testing these effects in multivariable MR models, we observed that the effect of these obesity-related anthropometric traits on COVID-19 outcomes is not independent of SES effect assessed as HI.ConclusionsOur findings indicate that low SES is a contributor to the observed association between body size and COVID-19 outcomes.
Spatial Accessibility Modeling of Vaccine Deserts as Barriers to Controlling SARS-CoV-2
Authors: Rader Benjamin , Astley Christina M. , Sewalk Kara , Delamater Paul L. , Cordiano Kathryn , Wronski Laura , Rivera Jessica Malaty , Hallberg Kai , Pera Megan F. , Cantor Jonathan , Whaley Christopher M. , Bravata Dena M. , Brownstein John S. 
Published: June 2021

AbstractSARS-CoV-2 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We identify vaccine deserts - US Census tracts with localized, geographic barriers to vaccine-associated herd immunity - using a comprehensive supply database (VaccineFinder) and an empirically parameterized model of spatial access to essential resources. Incorporating high-resolution COVID-19 burden and time-willing-to-travel for vaccination, we show that early (February – March 2021) vaccine allocation disadvantaged rural and medically vulnerable populations. Data-driven vaccine distribution to vaccine deserts may improve immunization in the hesitant and control SARS-CoV-2.
Vaccination history for diphtheria and tetanus is associated with less severe COVID-19
Authors: Monereo-Sánchez Jennifer , Luykx Jurjen J. , Pinzón-Espinosa Justo , Richard Geneviève , Motazedi Ehsan , Westlye Lars T. , Andreassen Ole A. , van der Meer Dennis 
Published: June 2021

ABSTRACTBackgroundCOVID-19 is characterized by strikingly large, mostly unexplained, interindividual variation in symptom severity. While some individuals remain nearly asymptomatic, others suffer from severe respiratory failure. It has been hypothesized that previous vaccinations for other pathogens, in particular tetanus, may provide protection against severe COVID-19.MethodsWe made use of data on COVID-19 testing from 103,049 participants of the UK Biobank (mean age 71.5 years, 54.2% female), coupled to immunization records of the last ten years. Using logistic regression, covarying for age, sex, respiratory disease diagnosis, and socioeconomic status, we tested whether individuals vaccinated for tetanus, diphtheria or pertussis, differed from individuals that had only received other vaccinations on 1) undergoing a COVID-19 test, 2) the outcome of this test, and 3) whether they developed severe COVID-19.ResultsWe found that individuals with registered diphtheria or tetanus vaccinations were less likely to develop severe COVID-19 than people who had only received other vaccinations (diphtheria OR=0.46, p=3.6×10−4; tetanus OR=0.50, p=5.8×10−4).DiscussionThese results indicate that a history of diphtheria or tetanus vaccinations is associated with less severe manifestations of COVID-19. These vaccinations may protect against severe COVID-19 symptoms by stimulating the immune system. We note the correlational nature of these results, yet the possibility that these vaccinations may influence the severity of COVID-19 warrants follow-up investigations.
REGEN-COV Antibody Combination in Outpatients With COVID-19 – Phase 1/2 Results
Authors: Norton Thomas , Ali Shazia , Sivapalasingam Sumathi , Gao Haitao , Bhore Rafia , Hooper Andrea T. , Hamilton Jennifer D. , Musser Bret J. , Rofail Diana , Im Joseph , Perry Christina , Pan Cynthia , Hosain Romana , Mahmood Adnan , Davis John D. , Turner Kenneth C. , Baum Alina , Kyratsous Christos A. , Kim Yunji , Cook Amanda , Kampman Wendy , Graber Ximena , Acloque Gerard , Sachdeva Yessica , Bocchini Joseph A. , Kohli Anita , Kowal Bari , DiCioccio A. Thomas , Soo Yuhwen , Geba Gregory P. , Stahl Neil , Lipsich Leah , Braunstein Ned , Herman Gary , Yancopoulos George D. , Weinreich David M. ,   the Trial Investigators
Published: June 2021

ABSTRACTBackgroundContinued SARS-CoV-2 infections and COVID-19-related hospitalizations highlight the need for effective anti-viral treatments in the outpatient setting. In a descriptive interim analysis of the phase 1/2 portion of a double-blind phase 1/2/3 trial in COVID-19 outpatients conducted between June 16, 2020 and September 4, 2020, REGEN-COV® (casirivimab plus imdevimab) antibody combination reduced SARS-CoV-2 viral load versus placebo.MethodsThis final phase 1/2 analysis comprises 799 outpatients, including 275 from the previous descriptive analysis (group-1) and 524 from phase 2 (group-2). Patients were randomized (1:1:1) to placebo, REGEN-COV 2400mg, or REGEN-COV 8000mg. Prespecified hierarchical analyses of virologic endpoints were performed in group-2. The proportion of patients with ≥1 COVID-19–related medically attended visit (MAV) through day 29 was assessed in group-1+2. Efficacy was assessed in patients confirmed SARS-CoV-2–positive by baseline nasopharyngeal RT-qPCR. Safety was assessed in all treated patients.ResultsData from 799 outpatients enrolled from June 16, 2020 to September 23, 2020 are reported. Time-weighted average daily reduction in viral load through day 7 was significantly greater in the REGEN-COV combined 2400mg+8000mg group versus placebo in patients with baseline viral load >107 copies/mL (prespecified primary endpoint): -0.68 log10 copies/ml (95% CI, -0.94 to -0.41; P<.0001). This reduction was - 0.73 (P<.0001) and -0.36 (P=.0003) log10 copies/mL in serum antibody–negative patients and in the overall population, respectively. REGEN-COV reduced the proportion of patients with ≥1 COVID-19–related MAV versus placebo (2.8% [12/434] REGEN-COV combined dose group versus 6.5% [15/231] placebo; P=.024; relative risk reduction [RRR]=57%); in patients with ≥1 risk factor for hospitalization, the treatment effect was more pronounced (RRR=71%). Adverse events were similar across groups.ConclusionsIn COVID-19 outpatients enrolled prior to the widespread circulation of delta and omicron variants, treatment with REGEN-COV significantly reduced viral load and COVID-19–related MAVs.
Moving from development to implementation of digital innovations within the NHS: myHealthE, a remote monitoring system for tracking patient outcomes in child and adolescent mental health services
Authors: Morris Anna C , Ibrahim Zina , Moghraby Omer S , Stringaris Argyris , Grant Ian M , Zalewski Lukasz , McClellan Stuart , Moriarty Garry , Simonoff Emily , Dobson Richard JB , Downs Johnny 
Published: June 2021

AbstractThis paper reports our experience of developing, implementing, and evaluating myHealthE (MHE); a digital innovation for Child and Adolescents Mental Health Services (CAMHS) which automates the remote collection and reporting of Patient Reported Outcome Measures (PROMs) into National Health Services (NHS) electronic health care records. We describe the logistical and governance issues encountered in developing the MHE interface with patient identifiable information, and the steps taken to overcome these development barriers. We describe the applications architecture and hosting environment to enable it to be operable within the NHS, as well the as the capabilities needed within the technical team to bridge the gap between academic developers and NHS operational teams. We present evidence on the feasibility and acceptability for this system within clinical services and describe the process of iterative development, highlighting additional functions which were incorporated to increase system utility. This article provides a framework with which to plan, develop and implement automated PROM collection from remote devices back to NHS infrastructure. The challenges and solutions described in this paper will be pertinent to other digital health innovation researchers aspiring to deploy interoperable systems within NHS clinical systems.
From Tabulated Data to Knowledge Graph: A Novel Way of Improving the Performance of the Classification Models in the Healthcare Data
Authors: Zaki Nazar , Mohamed Elfadil A , Habuza Tetiana 
Published: June 2021

AbstractIn sectors like healthcare, having classification models that are both reliable and accurate is vital. Regrettably, contemporary classification techniques employing machine learning disregard the correlations between instances within data. This research, to rectify this, introduces a basic but effective technique for converting tabulated data into data graphs, incorporating structural correlations. Graphs have a unique capacity to capture structural correlations between data, allowing us to gain a deeper insight in comparison to carrying out isolated data analysis. The suggested technique underwent testing once the integration of graph data structure-related elements had been carried out and returned superior results to testing solely employing original features. The suggested technique achieved validity by returning significantly improved levels of accuracy.DataThe extracted graph topological features datasets are available from: