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1.
JMIR Public Health Surveill ; 7(6): e27917, 2021 06 02.
Article in English | MEDLINE | ID: covidwho-2197909

ABSTRACT

BACKGROUND: The United States of America has the highest global number of COVID-19 cases and deaths, which may be due in part to delays and inconsistencies in implementing public health and social measures (PHSMs). OBJECTIVE: In this descriptive analysis, we analyzed the epidemiological evidence for the impact of PHSMs on COVID-19 transmission in the United States and compared these data to those for 10 other countries of varying income levels, population sizes, and geographies. METHODS: We compared PHSM implementation timing and stringency against COVID-19 daily case counts in the United States and against those in Canada, China, Ethiopia, Japan, Kazakhstan, New Zealand, Singapore, South Korea, Vietnam, and Zimbabwe from January 1 to November 25, 2020. We descriptively analyzed the impact of border closures, contact tracing, household confinement, mandated face masks, quarantine and isolation, school closures, limited gatherings, and states of emergency on COVID-19 case counts. We also compared the relationship between global socioeconomic indicators and national pandemic trajectories across the 11 countries. PHSMs and case count data were derived from various surveillance systems, including the Health Intervention Tracking for COVID-19 database, the World Health Organization PHSM database, and the European Centre for Disease Prevention and Control. RESULTS: Implementing a specific package of 4 PHSMs (quarantine and isolation, school closures, household confinement, and the limiting of social gatherings) early and stringently was observed to coincide with lower case counts and transmission durations in Vietnam, Zimbabwe, New Zealand, South Korea, Ethiopia, and Kazakhstan. In contrast, the United States implemented few PHSMs stringently or early and did not use this successful package. Across the 11 countries, national income positively correlated (r=0.624) with cumulative COVID-19 incidence. CONCLUSIONS: Our findings suggest that early implementation, consistent execution, adequate duration, and high adherence to PHSMs represent key factors of reducing the spread of COVID-19. Although national income may be related to COVID-19 progression, a country's wealth appears to be less important in controlling the pandemic and more important in taking rapid, centralized, and consistent public health action.


Subject(s)
COVID-19/prevention & control , Global Health/statistics & numerical data , Public Health/legislation & jurisprudence , COVID-19/epidemiology , COVID-19/transmission , Databases, Factual , Humans , Physical Distancing , Quarantine , Schools/organization & administration , United States/epidemiology , Workplace/organization & administration
2.
Cancer Epidemiol Biomarkers Prev ; 30(10): 1884-1894, 2021 10.
Article in English | MEDLINE | ID: covidwho-2194255

ABSTRACT

BACKGROUND: We described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. METHODS: We conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. RESULTS: We included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events. CONCLUSIONS: Patients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent. IMPACT: This study provides epidemiologic characteristics that can inform clinical care and etiologic studies.


Subject(s)
COVID-19/mortality , Neoplasms/epidemiology , Outcome Assessment, Health Care/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Child , Cohort Studies , Comorbidity , Databases, Factual , Female , Hospitalization/statistics & numerical data , Humans , Influenza, Human/epidemiology , Male , Middle Aged , Pandemics , Prevalence , Risk Factors , SARS-CoV-2 , Spain/epidemiology , United States/epidemiology , Young Adult
5.
Inj Prev ; 28(5): 440-445, 2022 10.
Article in English | MEDLINE | ID: covidwho-2193893

ABSTRACT

CONTEXT: No evidence-based review has compared injury risks sustained on trampolines at home and in trampoline centres. OBJECTIVE: To present pooled results for injury type, site and treatment from studies reporting injuries that occurred on trampolines at home and in trampoline centres. DATA SOURCES: MEDLINE, Scopus, Google Scholar and Embase databases were searched to 31 December 2021. STUDY SELECTION: Inclusion criteria: (1) assessment of trampoline injuries (home and trampoline centres); (2) children and adolescents; (3) the point estimate was reported as an odds ratio (OR); and (4) an internal comparison was used. DATA EXTRACTION: Data were reported according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. A random-effects model was used to estimate effect. RESULTS: There were 1 386 843 injuries (n=11 studies). There was an increased likelihood of musculoskeletal and/or orthopaedic injuries (OR 2.45, 95% CI 1.66 to 3.61, p<0.001), lower extremity injury (OR 2.81, 95% CI 1.99 to 3.97, p<0.001), sprains (OR 1.64, 95% CI 1.36 to 1.97, p<0.001) and a need for surgery (OR 1.89, 95% CI 1.37 to 2.60, p<0.001) at trampoline centres compared with home trampolines. Conversely, upper extremity injury (OR 0.49, 95% CI 0.25 to 0.95, p=0.03), concussion (OR 0.48, 95% CI 0.35 to 0.65, p<0.001) and lacerations (OR 0.46, 95% CI 0.35 to 0.59, p<0.001) were less likely to occur at trampoline centres than at home. CONCLUSIONS: Children using trampoline centres are more likely to suffer severe trauma and require surgical intervention than children using home trampolines. Development and implementation of preventative strategies, public awareness, and mandatory safety standards are urgently required for trampoline centres.


Subject(s)
Athletic Injuries , Leg Injuries , Sprains and Strains , Adolescent , Athletic Injuries/epidemiology , Child , Databases, Factual , Humans
6.
Int J Environ Res Public Health ; 19(14)2022 07 21.
Article in English | MEDLINE | ID: covidwho-1958591

ABSTRACT

In response to global efforts to control and exterminate infectious diseases, this study aims to provide insight into the productivity of remdesivir research and highlight future directions. To achieve this, there is a need to summarize and curate evidence from the literature. As a result, this study carried out comprehensive scientific research to detect trends in published articles related to remdesivir using a bibliometric analysis. Keywords associated with remdesivir were used to access pertinent published articles using the Scopus database. A total of 5321 research documents were retrieved, primarily as novel research articles (n = 2440; 46%). The number of publications increased exponentially from 2020 up to the present. The papers published by the top 12 institutions focusing on remdesivir accounted for 25.69% of the overall number of articles. The USA ranked as the most productive country, with 906 documents (37.1%), equivalent to one-third of the global publications in this field. The most productive institution was Icahn School of Medicine, Mount Sinai, in the USA (103 publications). The New England Journal of Medicine was the most cited, with an h-index of 13. The publication of research on remdesivir has gained momentum in the past year. The importance of remdesivir suggests that it needs continued research to help global health organizations detect areas requiring instant action to implement suitable measures. Furthermore, this study offers evolving hotspots and valuable insights into the scientific advances in this field and provides scaling-up analysis and evidence diffusion on remdesivir.


Subject(s)
Adenosine Monophosphate , Alanine , Bibliometrics , Adenosine Monophosphate/analogs & derivatives , Alanine/analogs & derivatives , Databases, Factual , Efficiency , Global Health , Publications/trends
7.
JMIR Public Health Surveill ; 7(1): e22794, 2021 01 12.
Article in English | MEDLINE | ID: covidwho-2141286

ABSTRACT

BACKGROUND: COVID-19, a viral respiratory disease first reported in December 2019, quickly became a threat to global public health. Further understanding of the epidemiology of the SARS-CoV-2 virus and the risk perception of the community may better inform targeted interventions to reduce the impact and spread of COVID-19. OBJECTIVE: In this study, we aimed to examine the association between chronic diseases and serious outcomes following COVID-19 infection, and to explore its influence on people's self-perception of risk for worse COVID-19 outcomes. METHODS: This study draws data from two databases: (1) the nationwide database of all confirmed COVID-19 cases in Portugal, extracted on April 28, 2020 (n=20,293); and (2) the community-based COVID-19 Barometer survey, which contains data on health status, perceptions, and behaviors during the first wave of COVID-19 (n=171,087). We assessed the association between relevant chronic diseases (ie, respiratory, cardiovascular, and renal diseases; diabetes; and cancer) and death and intensive care unit (ICU) admission following COVID-19 infection. We identified determinants of self-perception of risk for severe COVID-19 outcomes using logistic regression models. RESULTS: Respiratory, cardiovascular, and renal diseases were associated with mortality and ICU admission among patients hospitalized due to COVID-19 infection (odds ratio [OR] 1.48, 95% CI 1.11-1.98; OR 3.39, 95% CI 1.80-6.40; and OR 2.25, 95% CI 1.66-3.06, respectively). Diabetes and cancer were associated with serious outcomes only when considering the full sample of COVID-19-infected cases in the country (OR 1.30, 95% CI 1.03-1.64; and OR 1.40, 95% CI 1.03-1.89, respectively). Older age and male sex were both associated with mortality and ICU admission. The perception of risk for severe COVID-19 disease in the study population was 23.9% (n=40,890). This was markedly higher for older adults (n=5235, 46.4%), those with at least one chronic disease (n=17,647, 51.6%), or those in both of these categories (n=3212, 67.7%). All included diseases were associated with self-perceptions of high risk in this population. CONCLUSIONS: Our results demonstrate the association between some prevalent chronic diseases and increased risk of worse COVID-19 outcomes. It also brings forth a greater understanding of the community's risk perceptions of serious COVID-19 disease. Hence, this study may aid health authorities to better adapt measures to the real needs of the population and to identify vulnerable individuals requiring further education and awareness of preventive measures.


Subject(s)
COVID-19/therapy , Chronic Disease/epidemiology , Health Knowledge, Attitudes, Practice , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/mortality , Comorbidity , Databases, Factual , Female , Hospitalization/statistics & numerical data , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Portugal/epidemiology , Risk Assessment , Surveys and Questionnaires , Treatment Outcome
8.
An Acad Bras Cienc ; 94(suppl 3): e20201428, 2022.
Article in English | MEDLINE | ID: covidwho-2140908

ABSTRACT

Based on an extensive analysis of public databases, we provide an overview of the global scientific output and describe the dynamics of the profound changes in the scientific enterprise during the last decades. The analysis included the scientific production of 53 countries over the 1996-2018 period. During this period, the production of articles per year has tripled. There was a strong correlation between the growth of the global gross domestic product and the increase in the number of articles (R2 = 0.973, P<0.001). Six countries showed a robust increment of their scientific production and are currently among the top 20 in the ranking of world scientific production (China, India, South Korea, Brazil, Turkey, and Iran). The mean annual growth rate was about 12.7% for these six countries. The share of the global scientific production of these countries increased from 7% in 1996 to 27.8% in 2018. Conversely, the participation of the 10 most traditional countries has dropped from 73% to 45% during the same period. In conclusion, we believe that our findings may contribute to further studies aiming to evaluate the impact and changes of the scientific endeavor over the next years in light of the forthcoming new world framework.


Subject(s)
COVID-19 , Humans , Brazil , China , Databases, Factual , India
9.
Int J Equity Health ; 21(Suppl 3): 167, 2022 Nov 23.
Article in English | MEDLINE | ID: covidwho-2139306

ABSTRACT

In January 2020, SARS-CoV-2 virus was identified as a cause of an outbreak in China. The disease quickly spread worldwide, and the World Health Organization (WHO) declared the pandemic in March 2020.From the first notifications of spread of the disease, the WHO's Emergency Programme implemented a global COVID-19 surveillance system in coordination with all WHO regional offices. The system aimed to monitor the spread of the epidemic over countries and across population groups, severity of the disease and risk factors, and the impact of control measures. COVID-19 surveillance data reported to WHO is a combination of case-based data and weekly aggregated data, focusing on a minimum global dataset for cases and deaths including disaggregation by age, sex, occupation as a Health Care Worker, as well as number of cases tested, and number of cases newly admitted for hospitalization. These disaggregations aim to monitor inequities in COVID-19 distribution and risk factors among population groups.SARS-CoV-2 epidemic waves continue to sweep the world; as of March 2022, over 445 million cases and 6 million deaths have been reported worldwide. Of these, over 327 million cases (74%) have been reported in the WHO surveillance database, of which 255 million cases (57%) are disaggregated by age and sex. A public dashboard has been made available to visualize trends, age distributions, sex ratios, along with testing and hospitalization rates. It includes a feature to download the underlying dataset.This paper will describe the data flows, database, and frontend public dashboard, as well as the challenges experienced in data acquisition, curation and compilation and the lessons learnt in overcoming these. Two years after the pandemic was declared, COVID-19 continues to spread and is still considered a Public Health Emergency of International Concern (PHEIC). While WHO regional and country offices have demonstrated tremendous adaptability and commitment to process COVID-19 surveillance data, lessons learnt from this major event will serve to enhance capacity and preparedness at every level, as well as institutional empowerment that may lead to greater sharing of public health evidence during a PHEIC, with a focus on equity.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , World Health Organization , Databases, Factual , Pandemics
10.
Br J Dermatol ; 187(5): 638, 2022 11.
Article in English | MEDLINE | ID: covidwho-2136694

Subject(s)
Databases, Factual , Humans
11.
Database (Oxford) ; 20222022 Nov 25.
Article in English | MEDLINE | ID: covidwho-2135127

ABSTRACT

The Coronavirus Disease 2019 (COVID-19) pandemic has shifted the focus of research worldwide, and more than 10 000 new articles per month have concentrated on COVID-19-related topics. Considering this rapidly growing literature, the efficient and precise extraction of the main topics of COVID-19-relevant articles is of great importance. The manual curation of this information for biomedical literature is labor-intensive and time-consuming, and as such the procedure is insufficient and difficult to maintain. In response to these complications, the BioCreative VII community has proposed a challenging task, LitCovid Track, calling for a global effort to automatically extract semantic topics for COVID-19 literature. This article describes our work on the BioCreative VII LitCovid Track. We proposed the LitCovid Ensemble Learning (LCEL) method for the tasks and integrated multiple biomedical pretrained models to address the COVID-19 multi-label classification problem. Specifically, seven different transformer-based pretrained models were ensembled for the initialization and fine-tuning processes independently. To enhance the representation abilities of the deep neural models, diverse additional biomedical knowledge was utilized to facilitate the fruitfulness of the semantic expressions. Simple yet effective data augmentation was also leveraged to address the learning deficiency during the training phase. In addition, given the imbalanced label distribution of the challenging task, a novel asymmetric loss function was applied to the LCEL model, which explicitly adjusted the negative-positive importance by assigning different exponential decay factors and helped the model focus on the positive samples. After the training phase, an ensemble bagging strategy was adopted to merge the outputs from each model for final predictions. The experimental results show the effectiveness of our proposed approach, as LCEL obtains the state-of-the-art performance on the LitCovid dataset. Database URL: https://github.com/JHnlp/LCEL.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Databases, Factual , Semantics , Machine Learning
12.
Medicine (Baltimore) ; 101(45): e31474, 2022 Nov 11.
Article in English | MEDLINE | ID: covidwho-2115704

ABSTRACT

BACKGROUND: There is growing evidence that coronavirus disease 2019 (COVID-19) can trigger acute episodes of mood disorders or psychotic symptoms. Reports on the treatment of COVID-19-related bipolar disorder (BD) are limited. Our study aimed to investigate the potential for new or recurrent BD due to COVID-19. We qualitatively evaluate clinical treatments (acupuncture combined with medication) and any potential pathophysiological links between infection and BD. METHODS: We searched Embase, PubMed, Cochrane Library, Web of Science and MEDLINE (via Web of Science), Scopus, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure Database, and the Wanfang Database from December 1, 2019, to September 15, 2022, to identify all articles on acupuncture combined with drugs used to treat COVID-19 complicated with bipolar disorders. Two researchers will screen the articles and extract the relevant information. RESULTS: The results will provide a systematic overview of the current evidence on the use of acupuncture combined with drug therapy to treat COVID-19 complicated with bipolar disorder. CONCLUSION: The conclusions of this study will help clarify the effects of acupuncture combined with drug therapy on patients with COVID-19-related BD.


Subject(s)
Acupuncture Therapy , Bipolar Disorder , COVID-19 , Humans , Bipolar Disorder/complications , Bipolar Disorder/therapy , COVID-19/complications , COVID-19/therapy , Acupuncture Therapy/methods , Publications , Databases, Factual , Meta-Analysis as Topic , Systematic Reviews as Topic
13.
Bull World Health Organ ; 100(11): 699-708, 2022 Nov 01.
Article in English | MEDLINE | ID: covidwho-2113057

ABSTRACT

The demographic transition towards an ageing population and the epidemiological transition from communicable to noncommunicable diseases have increased the demand for rehabilitation services globally. The aims of this paper were to describe the integration of rehabilitation into the Japanese health system and to illustrate how health information systems containing real-world data can be used to improve rehabilitation services, especially for the ageing population of Japan. In addition, there is an overview of how evidence-informed rehabilitation policy is guided by the analysis of large Japanese health databases, such as: (i) the National Database of Health Insurance Claims and Specific Health Checkups; (ii) the long-term care insurance comprehensive database; and (iii) the Long-Term Care Information System for Evidence database. Especially since the 1990s, the integration of rehabilitation into the Japanese health system has been driven by the country's ageing population and rehabilitation is today provided widely to an increasing number of older adults. General medical insurance in Japan covers acute and post-acute (or recovery) intensive rehabilitation. Long-term care insurance covers rehabilitation at long-term care institutions and community facilities for older adults with the goal of helping to maintain independence in an ageing population. The analysis of large health databases can be used to improve the management of rehabilitation care services and increase scientific knowledge as well as guide rehabilitation policy and practice. In particular, such analyses could help solve the current challenges of overtreatment and undertreatment by identifying strict criteria for determining who should receive long-term rehabilitation services.


Tant la transition démographique vers un vieillissement de la population que la transition épidémiologique des maladies transmissibles vers les maladies non transmissibles ont entraîné une augmentation de la demande en services de réadaptation dans le monde. Le présent document poursuit plusieurs objectifs: décrire l'intégration de la réadaptation dans le système de santé au Japon, et illustrer comment les systèmes de santé contenant des données réelles peuvent être utilisés en vue d'améliorer de tels services, en particulier pour une population nipponne vieillissante. En outre, il offre un aperçu de la manière dont la politique de réadaptation étayée par des faits s'inspire de l'analyse de vastes bases de données sanitaires japonaises, parmi lesquelles: (i) la base de données nationale des demandes de remboursement au titre de l'assurance-maladie et des bilans de santé spécifiques; (ii) la base de données complète de l'assurance pour les soins longue durée; et enfin, (iii) la base de données du système d'information relatif aux attestations de soins longue durée. Le vieillissement de la population a poussé le Japon à inclure la réadaptation dans son système de santé, surtout depuis les années 1990; aujourd'hui, un nombre croissant de personnes âgées ont aisément accès à des services de réadaptation. Au Japon, l'assurance-maladie globale prend en charge la réadaptation intensive aiguë et post-aiguë (ou de rétablissement). De son côté, l'assurance pour les soins longue durée couvre la réadaptation dans les établissements dédiés et les infrastructures collectives accueillant des personnes âgées, avec pour but de contribuer à préserver l'autonomie au sein d'une population vieillissante. L'analyse de vastes bases de données sanitaires peut favoriser une meilleure gestion des services de réadaptation et accroître les connaissances scientifiques, mais aussi orienter les politiques et pratiques en la matière. Ce type d'analyse peut surtout aider à s'attaquer aux enjeux actuels que représentent les traitements excessifs ou insuffisants, en identifiant des critères stricts permettant de déterminer qui doit faire l'objet d'une réadaptation sur le long terme.


La transición demográfica hacia el envejecimiento de la población y la transición epidemiológica de las enfermedades transmisibles a las no transmisibles han aumentado la demanda de servicios de rehabilitación en todo el mundo. Los objetivos de este artículo son describir la integración de la rehabilitación en el sistema sanitario japonés e ilustrar cómo los sistemas de información sanitaria que contienen datos del mundo real se pueden utilizar para mejorar los servicios de rehabilitación, en especial para la población que envejece en Japón. Además, se ofrece una visión general de cómo la política de rehabilitación fundamentada en la evidencia se guía por el análisis de las grandes bases de datos sanitarias japonesas, como: (i) la Base de Datos Nacional de Reclamaciones al Seguro de Enfermedad y Chequeos Médicos Específicos; (ii) la base de datos integral del seguro de cuidados de larga duración; y (iii) la base de datos del Sistema de Información de Cuidados de Larga Duración para la Evidencia. En particular, desde la década de 1990, la integración de la rehabilitación en el sistema sanitario japonés se ha visto impulsada por el envejecimiento de la población del país y, en la actualidad, la rehabilitación se ofrece de forma generalizada a una cantidad cada vez mayor de adultos mayores. El seguro médico general de Japón cubre la rehabilitación intensiva aguda y posaguda (o de recuperación). El seguro de cuidados de larga duración cubre la rehabilitación en instituciones de larga estancia y centros comunitarios para adultos mayores con el objetivo de ayudar a mantener la independencia en una población que envejece. El análisis de las grandes bases de datos sanitarias puede servir para mejorar la gestión de los servicios de atención a la rehabilitación y aumentar los conocimientos científicos, así como para orientar la política y la práctica de la rehabilitación. En concreto, estos análisis podrían ayudar a resolver los problemas actuales de sobretratamiento y subtratamiento, al identificar criterios estrictos para determinar quién debe recibir servicios de rehabilitación de larga duración.


Subject(s)
Insurance, Long-Term Care , Long-Term Care , Humans , Aged , Japan , Insurance, Health , Databases, Factual
14.
Front Public Health ; 10: 925475, 2022.
Article in English | MEDLINE | ID: covidwho-2121936

ABSTRACT

Background: Autism spectrum disorders (ASD) are heterogeneous neurodevelopmental conditions that affect people worldwide. Early diagnosis and clinical support help achieve good outcomes. However, medical system structure and restricted resource availability create challenges that increase the risk of poor outcomes. Understanding the research progress of childhood ASD in recent years, based on clinical literature reports, can give relevant researchers and rehabilitation therapists more resonable research guides. Objective: This bibliometric study aimed to summarize themes and trends in research on childhood ASD and to suggest directions for future enquiry. Methods: Citations were downloaded from the Web of Science Core Collection database on childhood ASD published from 1 January 2012, to 31 December 2021. The retrieved information was analyzed using CiteSpace.5.8. R3, and VOS viewer. Results: A total of 7,611 papers were published across 103 areas. The United States was the leading source of publications. The clusters that have continued into 2020 include coronavirus disease 2019, gut microbiota, and physical activity, which represent key research topics. Keywords with frequency spikes during 2018-2021 were "disabilities monitoring network," "United States," and "caregiver." Conclusions: The Autism and Developmental Disabilities Monitoring Network in the United States can be used as a reference for relevant workers worldwide. An intelligent medical assistant system is being developed. Further studies are required to elucidate challenges associated with caring for a child with ASD.


Subject(s)
Autism Spectrum Disorder , COVID-19 , Gastrointestinal Microbiome , Bibliometrics , COVID-19/epidemiology , Child , Databases, Factual , Humans , United States
15.
BMC Res Notes ; 15(1): 340, 2022 Nov 05.
Article in English | MEDLINE | ID: covidwho-2108894

ABSTRACT

OBJECTIVE: Preprints have had a prominent role in the swift scientific response to COVID-19. Two years into the pandemic, we investigated how much preprints had contributed to timely data sharing by analyzing the lag time from preprint posting to journal publication. RESULTS: To estimate the median number of days between the date a manuscript was posted as a preprint and the date of its publication in a scientific journal, we analyzed preprints posted from January 1, 2020, to December 31, 2021 in the NIH iSearch COVID-19 Portfolio database and performed a Kaplan-Meier (KM) survival analysis using a non-mixture parametric cure model. Of the 39,243 preprints in our analysis, 7712 (20%) were published in a journal, after a median lag of 178 days (95% CI: 175-181). Most of the published preprints were posted on the bioRxiv (29%) or medRxiv (65%) servers, which allow authors to choose a subject category when posting. Of the 20,698 preprints posted on these two servers, 7358 (36%) were published, including approximately half of those categorized as biochemistry, biophysics, and genomics, which became published articles within the study interval, compared with 29% categorized as epidemiology and 26% as bioinformatics.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , Databases, Factual
16.
Sci Rep ; 12(1): 18710, 2022 Nov 04.
Article in English | MEDLINE | ID: covidwho-2106460

ABSTRACT

The purpose of this study is to manually and semi-automatically curate a database and develop an R package that will act as a comprehensive resource to understand how biological processes are dysregulated due to interactions with environmental factors. The initial database search run on the Gene Expression Omnibus and the Molecular Signature Database retrieved a total of 90,018 articles. After title and abstract screening against pre-set criteria, a total of 237 datasets were selected and 522 gene modules were manually annotated. We then curated a database containing four environmental factors, cigarette smoking, diet, infections and toxic chemicals, along with a total of 25,789 genes that had an association with one or more of gene modules. The database and statistical analysis package was then tested with the differentially expressed genes obtained from the published literature related to type 1 diabetes, rheumatoid arthritis, small cell lung cancer, COVID-19, cobalt exposure and smoking. On testing, we uncovered statistically enriched biological processes, which revealed pathways associated with environmental factors and the genes. The curated database and enrichment tool are available as R packages at https://github.com/AhmedMehdiLab/E.PATH and https://github.com/AhmedMehdiLab/E.PAGE respectively.


Subject(s)
COVID-19 , Gene Expression Profiling , Humans , Gene Regulatory Networks , Databases, Factual , Gene Expression
17.
Sci Data ; 9(1): 654, 2022 10 26.
Article in English | MEDLINE | ID: covidwho-2087255

ABSTRACT

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), a virus causing severe acute respiratory disease in humans, emerged in late 2019. This respiratory virus can spread via aerosols, fomites, contaminated hands or surfaces as for other coronaviruses. Studying their persistence under different environmental conditions represents a key step for better understanding the virus transmission. This work aimed to present a reproducible procedure for collecting data of stability and inactivation kinetics from the scientific literature. The aim was to identify data useful for characterizing the persistence of viruses in the food production plants. As a result, a large dataset related to persistence on matrices or in liquid media under different environmental conditions is presented. This procedure, combining bibliographic survey, data digitalization techniques and predictive microbiological modelling, identified 65 research articles providing 455 coronaviruses kinetics. A ranking step as well as a technical validation with a Gage Repeatability & Reproducibility process were performed to check the quality of the kinetics. All data were deposited in public repositories for future uses by other researchers.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Food Handling , Kinetics , Plants, Edible , Reproducibility of Results , Databases, Factual
18.
Sensors (Basel) ; 22(21)2022 Oct 23.
Article in English | MEDLINE | ID: covidwho-2081831

ABSTRACT

A systematic review on the topic of automatic detection of COVID-19 using audio signals was performed. A total of 48 papers were obtained after screening 659 records identified in the PubMed, IEEE Xplore, Embase, and Google Scholar databases. The reviewed studies employ a mixture of open-access and self-collected datasets. Because COVID-19 has only recently been investigated, there is a limited amount of available data. Most of the data are crowdsourced, which motivated a detailed study of the various pre-processing techniques used by the reviewed studies. Although 13 of the 48 identified papers show promising results, several have been performed with small-scale datasets (<200). Among those papers, convolutional neural networks and support vector machine algorithms were the best-performing methods. The analysis of the extracted features showed that Mel-frequency cepstral coefficients and zero-crossing rate continue to be the most popular choices. Less common alternatives, such as non-linear features, have also been proven to be effective. The reported values for sensitivity range from 65.0% to 99.8% and those for accuracy from 59.0% to 99.8%.


Subject(s)
COVID-19 , Humans , COVID-19/diagnosis , Neural Networks, Computer , Algorithms , Support Vector Machine , Databases, Factual
19.
Sensors (Basel) ; 22(20)2022 Oct 17.
Article in English | MEDLINE | ID: covidwho-2071712

ABSTRACT

Research on face recognition with masked faces has been increasingly important due to the prolonged COVID-19 pandemic. To make face recognition practical and robust, a large amount of face image data should be acquired for training purposes. However, it is difficult to obtain masked face images for each human subject. To cope with this difficulty, this paper proposes a simple yet practical method to synthesize a realistic masked face for an unseen face image. For this, a cascade of two convolutional auto-encoders (CAEs) has been designed. The former CAE generates a pose-alike face wearing a mask pattern, which is expected to fit the input face in terms of pose view. The output of the former CAE is readily fed into the secondary CAE for extracting a segmentation map that localizes the mask region on the face. Using the segmentation map, the mask pattern can be successfully fused with the input face by means of simple image processing techniques. The proposed method relies on face appearance reconstruction without any facial landmark detection or localization techniques. Extensive experiments with the GTAV Face database and Labeled Faces in the Wild (LFW) database show that the two complementary generators could rapidly and accurately produce synthetic faces even for challenging input faces (e.g., low-resolution face of 25 × 25 pixels with out-of-plane rotations).


Subject(s)
COVID-19 , Facial Recognition , Humans , Pandemics , Image Processing, Computer-Assisted/methods , Databases, Factual
20.
Nucleic Acids Res ; 50(D1): D1255-D1261, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-2062939

ABSTRACT

The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO's 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on available resource statistics, terms from the DO have been annotated to over 1.5 million biomedical data elements and citations, a 10× increase in the past 5 years. The DO, funded as a NHGRI Genomic Resource, plays a key role in disease knowledge organization, representation, and standardization, serving as a reference framework for multiscale biomedical data integration and analysis across thousands of clinical, biomedical and computational research projects and genomic resources around the world. This update reports on the addition of 1,793 new disease terms, a 14% increase of textual definitions and the integration of 22 137 new SubClassOf axioms defining disease to disease connections representing the DO's complex disease classification. The DO's updated website provides multifaceted etiology searching, enhanced documentation and educational resources.


Subject(s)
Biological Ontologies , Databases, Factual , Databases, Genetic , Genetic Diseases, Inborn/classification , Genetic Diseases, Inborn/genetics , Genomics/classification , Humans
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