bluuebunny/crossref_metadata_2025_split huggingface dataset:
When lockdown policies amplify social inequalities in COVID-19 infections. Evidence from a cross-sectional population-based survey in France
Authors: Bajos Nathalie , Jusot Florence , Pailhé Ariane , Spire Alexis , Martin Claude , Meyer Laurence , Lydié Nathalie , Franck Jeanna-Eve , Zins Marie , Carrat Fabrice ,   for the SAPRIS study group
Published: October 2020

AbstractObjectivesTo assess social inequalities in the trends in COVID-19 infections following lockdownDesignA cross-sectional survey conducted among the general population in France in April 2020, during COVID-19 lockdown.Participants10 401 participants aged 18-64, from a national cohort who lived in the three metropolitan French regions most affected by the first wave of COVID-19.Main outcomeThe main outcome was occurrence of possible COVID-19 symptoms, defined as the occurrence of sudden onset of cough, fever, dyspnea, ageusia and/or anosmia, that lasted more than three days in the 15 days before the survey. We used multinomial regression models to identify social and health factors related to possible COVID-19 before and during the lockdown.ResultsIn all, 1,304 (13.0%; 95% CI: 12.0%-14.0%) reported cases of possible COVID-19. The effect of lockdown on the occurrence of possible COVID-19 was different across social hierarchies. The most privileged class individuals saw a significant decline in possible COVID-19 infections between the period prior to lockdown and during the lockdown (from 8.8% to 4.3%, P=0.0001) while the decline was less pronounced among working class individuals (6.9% before lockdown and 5.5% during lockdown, P=0.03). This differential effect of lockdown remained significant after adjusting for other factors including history of chronic disease. The odds of being contaminated during lockdown as opposed to the prior period increased by 57% among working class individuals (OR=1.57; 95% CI: 1.0-2.48). The same was true for those engaged in in-person professional activities during lockdown (OR=1.53; 95% CI: 1.03-2.29).InterpretationLockdown was associated with social inequalities in the decline in COVID-19 infections, calling for the adoption of preventive policies to account for living and working conditions. Such adoptions are critical to reduce social inequalities related to COVID-19, as working-class individuals also have the highest COVID-19 related mortality, due to higher prevalence of comorbidities.Section 1: What is already known on this topicSignificant differences in COVID-19 incidence by gender, class and race/ethnicity are recorded in many countries in the world. Lockdown measures implemented throughout the globe have been effective in reducing transmission risks.Section 2: What this study addsOur study shows that lockdown’s impact was socially differentiated and has benefited the working classes the least. Such results underline the need to design COVID-19 preventive policies that take into account living and working conditions, as working-class individuals also have the highest COVID-19 related mortality, due to higher prevalence of comorbidities.
Low zinc levels at clinical admission associates with poor outcomes in COVID-19
Authors: Vogel-González Marina , Talló-Parra Marc , Herrera-Fernández Víctor , Pérez-Vilaró Gemma , Chillón Miguel , Nogués Xavier , Gómez-Zorrilla Silvia , López-Montesinos Inmaculada , Villar Judit , Sorli-Redó Maria Luisa , Horcajada Juan Pablo , García-Giralt Natalia , Pascual Julio , Díez Juana , Vicente Rubén , Güerri-Fernández Robert 
Published: October 2020

AbstractBackgroundBiomarkers to predict Coronavirus disease-19 (COVID-19) outcome early at infection are urgently needed to improve prognosis and treatment. Zinc balances immune responses and also has a proven direct antiviral action against some viruses. Importantly, zinc deficiency (ZD) is a common condition in elderly and individuals with chronic diseases, two groups with more severe COVID-19 outcomes. We hypothesize that serum zinc content (SZC) influences COVID-19 disease progression and thus might represent a useful biomarker.MethodsWe run a retrospective observational study with 249 COVID-19 patients admitted in Hospital del Mar. We have studied COVID-19 severity and progression attending to SZC at admission. In parallel we have studied SARS-CoV2 replication in the Vero E6 cell line modifying zinc concentrations.FindingsOur study demonstrates a correlation between serum zinc levels and COVID-19 outcome. Serum zinc levels lower than 50 µg/dl at admission correlated with worse clinical presentation, longer time to reach stability and higher mortality. Our in vitro results indicate that low zinc levels favor viral expansion in SARS-CoV2 infected cells.InterpretationSZC is a novel biomarker to predict COVID-19 outcome. We encourage performing randomized clinical trials to study zinc supplementation as potential prophylaxis and treatment with people at risk of zinc deficiency.FundingSpanish Ministry of Science and Innovation, “Maria de Maeztu” Programme for Units of Excellence in R&D and Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement of the Generalitat de Catalunya. Instituto Carlos III Fondos de Investigaciones Sanitarias (FIS), CIBER on Frailty and Healthy Ageing and FEDER funds
Predicting multi-modal symptom trajectories across 7 years in veterans with chronic posttraumatic stress
Authors: Pierce Benjamin , Kirsh Thomas , Kummerfeld Erich , Ferguson Adam R. , Neylan Thomas C. , Cohen Beth E. , Ma Sisi , Nielson Jessica L. 
Published: October 2020

AbstractBackgroundVeterans are disproportionately affected by symptoms of post-traumatic stress (PTS) and associated poor health and psychosocial functioning. While most improve over time, others experience severe and persistent concerns. The ability to predict this latter group is critical for early intervention. Characterizing this subgroup has proven difficult, with most studies focusing on PTS and neglect a wider assessment of veterans’ wellbeing. Consequently, little is known about veterans who experience chronic symptoms and far-reaching impairment.MethodThe present study uses dimension reduction, growth mixture modeling, and clustering methods to identify veterans with the worst-faring trajectories of psychiatric symptoms, health, and psychosocial functioning, using data from the seven-year Mind Your Heart study (MYH) of people receiving Veterans Affairs services (n = 747). Random forest classification and feature selection were then used to examine predictors that distinguish the worst-fairing veteran group from others in the cohort.ResultsThe combined analyses revealed a subgroup of veterans with severe and diverse symptoms across psychiatric domains, impairment in multiple facets of living, and poor health with deterioration over seven years. This subgroup was distinguished by transdiagnostic symptom severity and greater social isolation, avoidance, anhedonia, cynicism, anger/hostility, and immune response and inflammation.ConclusionsVeterans whose distress spans multiple domains appear to be more broadly impaired, socially isolated, cynical or angry/hostile to others, and show elevated immunoreactivity and inflammation. Care for this population should be informed by a multidisciplinary approach that is conscious of veterans’ mental and physical health, and interpersonal needs.
Clinical characteristics and outcomes of adult patients admitted with COVID-19 in East London: a retrospective cohort analysis
Authors: Cheng Daryl Oswald , Calderwood Claire Jacqueline , Skyllberg Erik Wilhelm , Ainley Adam Denis Jeremy 
Published: October 2020

AbstractBackgroundDescriptions of clinical characteristics of patients hospitalised with coronavirus disease 2019 (COVID-19), their clinical course and short-term in- and outpatient outcomes in deprived urban populations in the United Kingdom are still relatively sparse. We describe the epidemiology, clinical course, experience of non-invasive ventilation and intensive care, mortality and short-term sequalae of patients admitted to two large District General Hospitals across a large East London NHS Trust during the first wave of the pandemic.MethodsA retrospective analysis was carried out on a cohort of 1,946 patients with a clinical or laboratory diagnosis of COVID-19, including descriptive statistics and survival analysis. A more detailed analysis was undertaken of a subset of patients admitted across three Respiratory Units in the trust.ResultsIncreasing age, male sex and Asian ethnicity were associated with worse outcomes. Increasing severity of chest X-ray abnormalities trended with mortality. Radiological changes persisted in over 50% of cases at early follow up (6 weeks). Ongoing symptoms including hair loss, memory impairment, breathlessness, cough and fatigue were reported in 67% of survivors, with 42% of patients unable to return to work due to ongoing symptoms.ConclusionsUnderstanding the acute clinical features, course of illness and outcomes of COVID-19 will be vital in preparing for further peaks of the pandemic. Our initial follow up data suggest there are ongoing sequalae of COVID-19 including persistent symptoms and radiological abnormalities. Further data, including longer term follow up data, are necessary to improve our understanding of this novel pathogen and associated disease.Section 1: What is already known on this topicPrevious studies have reported that increasing age, male sex, Black and Asian ethnicity increased risk of death for patients admitted to hospital with coronavirus disease 2019 (COVID-19). There is little published literature regarding the follow up of patients with COVID-19.Section 2: What this study addsOur study is one of the first with follow up data for patients admitted to hospital with COVID-19. We show that radiological abnormality persisted at 6 weeks in over 50% of patients, as well as significantly increased breathlessness in patients without baseline dyspnoea. Our study confirms that increasing age, male sex and Asian ethnicity increased risk of death for patients, but also in an ethnically and socioeconomically diverse population in East London.
Radiomic and clinical predictors of cachexia in non-small cell lung cancer patients treated with immunotherapy
Authors: Mu Wei , Katsoulakis Evangelia , Gage Kenneth L. , Whelan Chris J. , Schabath Matthew B. , Gillies Robert J. 
Published: October 2020

AbstractBackgroundCachexia is present in up to 50% of patients with cancer and may contribute to primary resistance to immunotherapy. Biomarkers to predict cachexia are urgently required for early intervention. Herein, we test the hypothesis that pre-treatment 18F-FDG-PET/CT-based radiomics can be used to predict cachexia and subsequently associated with clinical outcomes among patients with advanced non-small cell lung cancer (NSCLC) who are treated with immunotherapy.MethodsThis retrospective multi-institution study included 210 patients with histologically confirmed stage IIIB-IV NSCLC who were treated with immune checkpoint blockade between June 2011 and August 2019. Baseline (pre-immunotherapy) PET/CT images of 175 patients from Moffitt Cancer Center were used to train (N=123) and test (N=52) a radiomics signature to predict cachexia, which was also used to predict durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) subsequently. An external cohort that enrolled 35 patients from James A. Haley Veterans’ Hospital (VA) was used to further validate the predictive and prognostic value of this signature.ResultsA radiomics signature demonstrated cachexia prediction ability with areas under receiver operating characteristics curves (AUC) of 0.77 (95%CI:0.68-0.85), 0.75 (95%CI:0.60-0.86) and of 0.73 (95%CI:0.53-0.92) in the training, test and external VA cohorts, respectively. For the further investigation of prognostic value, this signature could identify the patients with DCB with AUC of 0.67 (95%CI:0.57-0.77), 0.66 (95%CI:0.51-0.81), and 0.72 (95%CI:0.54-0.89) in these three cohorts. Additionally, the PFS and OS were significantly shorter among patients with higher radiomics signature in all the three cohorts (p<0.05).ConclusionUsing PET/CT radiomics analysis, cachexia could be predicted before the start of the immunotherapy, making it possible to monitor the patients with a higher risk of cachexia and identify patients most likely to benefit from immunotherapy.
Age-targeted dose allocation can halve COVID-19 vaccine requirements
Authors: Meehan Michael T. , Cocks Daniel G. , Caldwell Jamie M. , Trauer James M. , Adekunle Adeshina I. , Ragonnet Romain R. , McBryde Emma S. 
Published: October 2020

ABSTRACTIn anticipation of COVID-19 vaccine deployment, we use an age-structured mathematical model to investigate the benefits of optimizing age-specific dose allocation to suppress the transmission, morbidity and mortality of SARS-CoV-2 and the associated disease, COVID-19. To minimize transmission, we find that the highest priority individuals across 179 countries are typically those between 30 and 59 years of age because of their high contact rates and higher risk of infection and disease. Conversely, morbidity and mortality are initially most effectively reduced by targeting 60+ year olds who are more likely to experience severe disease. However, when population-level coverage is sufficient — such that herd immunity can be achieved through targeted dose allocation — prioritizing middle-aged individuals becomes the most effective strategy to minimize hospitalizations and deaths. For each metric considered, we show that optimizing the allocation of vaccine doses can more than double their effectiveness.
District level correlates of COVID-19 pandemic in India
Authors: Tamrakar Vandana , Srivastava Ankita , Parmar Mukesh C. , Shukla Sudheer Kumar , Shabnam Shewli , Boro Bandita , Saha Apala , Debbarma Benjamin , Saikia Nandita 
Published: October 2020

AbstractBackgroundThe number of patients with coronavirus infection (COVID-19) has amplified in India. Understanding the district level correlates of the COVID-19 infection ratio (IR) is therefore essential for formulating policies and intervention.ObjectivesThe present study examines the association between socio-economic and demographic characteristics of India’s population and the COVID-19 infection ratio at district level…Data and MethodsUsing crowdsourced data on the COVID-19 prevalence rate, we analyzed state and district level variation in India from March 14 to July 31 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out a regression analysis to highlight the district level demographic, socio-economic, infrastructure, and health-related correlates of the COVID-19 infection ratio.ResultsThe results showed that the IR is 42.38 per one hundred thousand population in India. The highest IR was observed in Andhra Pradesh (145.0), followed by Maharashtra (123.6), and was the lowest in Chhattisgarh (10.1). About 80 per cent of infected cases, and 90 per cent of deaths were observed in nine Indian states (Tamil Nadu, Andhra Pradesh, Telangana, Karnataka, Maharashtra, Delhi, Uttar Pradesh, West Bengal, and Gujarat). Moreover, we observed COVID-19 cold-spots in central, northern, western, and north-eastern regions of India. Out of 736 districts, six metropolitan cities (Mumbai, Chennai, Thane, Pune, Bengaluru, and Hyderabad) emerged as the major hotspots in India, containing around 30 per cent of confirmed total COVID-19 cases in the country. Simultaneously, parts of the Konkan coast in Maharashtra, parts of Delhi, the southern part of Tamil Nadu, the northern part of Jammu & Kashmir were identified as hotspots of COVID-19 infection. Moran’s-I value of 0.333showed a positive spatial clusteringlevel in the COVID-19 IR case over neighboring districts. Our regression analysis found that district-level population density (β: 0.05, CI:004-0.06), the percent of urban population (β:3.08, CI: 1.05-5.11), percent of Scheduled Caste Population (β: 3.92, CI: 0.12-7.72),and district-level testing ratio (β: 0.03, CI: 0.01-0.04) are positively associated with the prevalence of COVID-19.ConclusionCOVID-19 cases were heavily concentrated in 9 states of India. Several demographic, socio-economic, and health-related variables are correlated with COVID-19 prevalence rate. However, after adjusting the role of socio-economic and health-related factors, the COVID-19 infection rate was found to be more rampant in districts with a higher population density, a higher percentage of the urban population, and a higher percentage of deprived castes and with a higher level of testing ratio. The identified hotspots and correlates in this study give crucial information for policy discourse.
SARS-CoV-2 genomic characterization and clinical manifestation of the COVID-19 outbreak in Uruguay
Authors: Elizondo Victoria , Harkins Gordon W. , Mabvakure Batsirai , Smidt Sabine , Zappile Paul , Marier Christian , Maurano Matthew , Perez Victoria , Mazza Natalia , Beloso Carolina , Ifran Silvana , Fernandez Mariana , Santini Andrea , Perez Veronica , Estevez Veronica , Nin Matilde , Manrique Gonzalo , Perez Leticia , Ross Fabiana , Boschi Susana , Zubillaga Maria Noel , Balleste Raquel , Dellicour Simon , Heguy Adriana , Duerr Ralf 
Published: October 2020

AbstractCOVID-19 is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and declared by the World Health Organization a global public health emergency. Among the severe outbreaks across South America, Uruguay has become known for curtailing SARS-CoV-2 exceptionally well. To understand the SARS-CoV-2 introductions, local transmissions, and associations with genomic and clinical parameters in Uruguay, we sequenced the viral genomes of 44 outpatients and inpatients in a private healthcare system in its capital, Montevideo, from March to May 2020. We performed a phylogeographic analysis using sequences from our cohort and other studies that indicate a minimum of 23 independent introductions into Uruguay, resulting in five major transmission clusters. Our data suggest that most introductions resulting in chains of transmission originate from other South American countries, with the earliest seeding of the virus in late February 2020, weeks before the borders were closed to all non-citizens and a partial lockdown implemented. Genetic analyses suggest a dominance of S and G clades (G, GH, GR) that make up >90% of the viral strains in our study. In our cohort, lethal outcome of SARS-CoV-2 infection significantly correlated with arterial hypertension, kidney failure, and ICU admission (FDR < 0.01), but not with any mutation in a structural or non-structural protein, such as the spike D614G mutation. Our study contributes genetic, phylodynamic, and clinical correlation data about the exceptionally well-curbed SARS-CoV-2 outbreak in Uruguay, which furthers the understanding of disease patterns and regional aspects of the pandemic in Latin America.
Epidemiology of sleep disorders during COVID-19 pandemic: A systematic scoping review
Authors: Tasnim Samia , Rahman Mariya , Pawar Priyanka , Chi Xinli , Yu Qian , Zou Liye , Sultana Abida , McKyer E. Lisako J. , Ma Ping , Hossain Md Mahbub 
Published: October 2020

AbstractBackgroundA growing burden of mental health problems has become a global concern amid the coronavirus disease (COVID-19) pandemic. Sleep disorders are major mental health problems associated with increased psychosocial stressors; however, no research synthesis is available on the epidemiology of it. In this systematic scoping review, we aimed to assess the current evidence on the epidemiological burden, associated factors, and interventions from the existing literature.MethodSeven major health databases and additional sources were searched to identify, evaluate, and synthesize empirical studies on the prevalence and correlates of sleep disorders and available interventions. The Joanna Briggs Institute Methodology for Scoping Review were used, and the findings were reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist.ResultsA total of 78 articles were retrieved, the prevalence of sleeping disorders ranged from 2.3% to 76.6%. Age, sex, level of education, physical and mental health, COVID-19 related factors, occupation especially being health care workers (HCW) were the main associated factors. Only two intentions were identified to address the issue.ConclusionThe finding of this review indicated a high burden of sleep disorder with limited interventions that necessitate informing policymakers and practitioners to facilitate future research and implementations.Brief summaryCurrent Knowledge/Study RationaleDespite the paramount importance of sleep for the physical and mental wellbeing of individuals, sleep hygiene is often neglected which resulted in a high prevalence of sleep disorders across the globe. This condition is likely to worsen amid this pandemic. This is the first systematic scoping review of sleep disorders during the COVID-19 pandemic.Study ImpactThe findings of our study suggest a high prevalence of sleep disorder and highlight a wide range of socio-demographic factors to identify population groups vulnerable to the adverse outcomes of sleep disorder with limited interventions. These pieces of evidence will guide clinicians to make informed choices for better management of patients and aid public health professionals to prevent sleep disorder epidemic concurring with the current pandemic.