COVID-19 (Coronavirus) Resources

Live automated evidence via PubMed/ Clinical Trials/ F1000/ BioMedCentral/ bioRxiv/ medRxiv

Digital Science is providing all relevant content on COVID-19 in Dimensions as a single export file, updated daily, to make sharing and distributing this research information easier.
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It includes a clean, ready-to-use data stream of case reports, compiled by Johns Hopkins University and including data from WHO and the CDC; a jumpstart workbook; and a curated gallery of the best visualizations created by Tableau users.

Resources include guidelines, reports, proceedings, trainings, fact sheets, etc., for a professional audience.

In order to ensure immediate access to Cochrane Reviews of potential relevance, this Cochrane Library Special Collection assembles Cochrane Reviews identified as most directly relevant to the prevention of infection. It includes reviews that evaluate the effects of interventions referenced in the WHO interim guidance for the 2019 coronavirus outbreak (28 January 2020), as well as other potentially relevant reviews from three Cochrane Networks.

Please note that the reviews included in this Special Collection summarize evidence, and their inclusion does not mean that the interventions reviewed have been shown to be an effective prevention measure.

This Special Collection includes Cochrane Reviews on the following topics: fluid and vasopressor therapy; respiratory support and mechanical ventilation; weaning mechanical ventilation; managing hypoxaemia; pharmacological treatment; and nutrition in intensive care. Many reviews in the collection have associated Cochrane Clinical Answers, with links provided.

It is important to note that the reviews included in this Collection summarise evidence; their inclusion does not mean that they are an effective treatment. A number of reviews presented here highlight the paucity of high-quality evidence to inform medical decision-making in the context of the severe acute respiratory infection (SARI) crisis.

LitCovid is a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus. It is the most comprehensive resource on the subject, providing a central access to 737 (and growing) peer-review articles. The articles are updated daily and are further categorized by different research topics and geographic locations for improved access.

In response to the COVID-19 pandemic, the Allen Institute for AI has partnered with leading research groups to prepare and distribute the COVID-19 Open Research Dataset (CORD-19), a free resource of over 29,000 scholarly articles, including over 13,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community. This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease. The corpus will be updated weekly as new research is published in peer-reviewed publications and archival services like bioRxiv, medRxiv, and others.

Live automated evidence via PubMed/ Clinical Trials/ F1000/ BioMedCentral/ bioRxiv/ medRxiv