Background: During the pandemic, countries utilized various forms of statistical estimations of coronavirus disease-2019 (COVID-19) impact. Differences between databases make direct comparisons and interpretations of data in different countries a challenge. We evaluated country-specific approaches to COVID-19 data and recommended changes that would improve future international collaborations.
Methods: We compared the COVID-19 reports presented on official UK (National Health System), Israeli (Department of Health), Latvian (Center for Disease Prevention and Control) and USA (Centers for Disease Control and Prevention) health authorities' websites.
Results: Our analysis demonstrated critical differences in the ways COVID-19 statistics were made available to the general and scientific communities. Specifically, the differences in approaches were found in the presentation of the number of infected cases and tests, and percentage of positive cases, the number of severe cases, the number of vaccinated, and the number and percent of deaths.
Conclusion: Findability, Accessibility, Interoperability and Reusability principles could guide the development of essential global standards that provide a basis for communication within and outside of the scientific community.
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http://dx.doi.org/10.1093/pubmed/fdad277 | DOI Listing |
Rheumatology (Oxford)
January 2025
Department of Cell Biology and Immunology, Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain.
Objectives: COVID-19 and systemic sclerosis (SSc) share multiple similarities in their clinical manifestations, alterations in immune response, and therapeutic options. These resemblances have also been identified in other immune-mediated inflammatory diseases where a common genetic component has been found. Thus, we decided to evaluate for the first time this shared genetic architecture with SSc.
View Article and Find Full Text PDFJ Epidemiol Glob Health
January 2025
Center of Clinical Laboratory, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, No.201-209 Hubinnan Road, Xiamen, 361004, China.
Background: During the COVID-19 outbreak in December 2022 in China, some laboratory workers in SARS-CoV-2 nucleic acid testing (NAT) laboratories remained uninfected.
Objectives: To evaluate if the incidence of SARS-CoV-2 infection was reduced in laboratory workers who performed SARS-CoV-2 NAT, and whether this reduction resulted from the healthy worker effect.
Methods: This retrospective cohort study included 423 laboratory workers from 14 SARS-CoV-2 NAT laboratories in Xiamen, China.
The COVID-19 pandemic instigated changes in almost all aspects of youth's life. While numerous studies have been implemented to understand how these changes are related to youth's development, few concerned large representative samples. This study introduces the methodology and initial results of the Quebec (Canada) Resilience Project (QRP), a representative longitudinal study.
View Article and Find Full Text PDFFuture Cardiol
January 2025
BridgeBio Pharma, Inc., San Francisco, CA, USA.
Introduction: The 6-minute walk test (6MWT) is used to assess submaximal exercise capacity in clinical trials. Conducting the 6MWT can be challenging when patients cannot visit the clinic due to physical/travel limitations. This pilot study assessed the feasibility of conducting the 6MWT using wearable sensors for patients with transthyretin amyloid cardiomyopathy.
View Article and Find Full Text PDFJ Virol
January 2025
MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, United Kingdom.
The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveillance to become a powerful tool for monitoring the evolution of circulating viruses. Herein, we discuss how a state-of-the-art artificial intelligence approach called protein language models (pLMs) can be used for effectively analyzing pathogen genomic data. We highlight examples of pLMs applied to predicting viral properties and evolution and lay out a framework for integrating pLMs into genomic surveillance pipelines.
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