Hundreds of thousands of open source COVID-19 publications, preprints, clinical trials, protocols, and other resources have been published in the past year. With a high volume of new journal articles and preprints emerging every day, trying to keep up with new research is overwhelming. Moreover, it is a tremendous undertaking to simply reduce new publications to a specific research field, as the number of papers is growing rapidly across epidemiology, virology, sociology, pharmacology, science policy, biochemistry – the list goes on.
An overwhelming amount of publicly available research presents a problem for researchers attempting to access preprints and data regarding new variants of COVID-19. At such a crucial time in the evolution of the pandemic, how do researchers stay up-to-date with the high volume of information that is uncovered daily about B.1.1.7 or N501Y or P681H, etc.?
More than ever, it is essential that researchers have access to a searchable, centralized hub of all academic resources related to COVID-19 and SARS-CoV-2. Luckily, oubreak.info offers that solution.
Outbreak.info exists to help epidemiologists, biologists, geneticists, and anyone investigating new COVID-19 mutations answer important research questions. For example:
As preprints and datasets related to the COVID-19 variant emerge, how do I find new research?
Outbreak.info’s numerous user-friendly features provide multiple ways to narrow down the thousands of academic resources. The interface aggregates publications from LitCovid, PubMed, bioRixv, medRxiv, MRC Centre for Global Infection Disease Analysis, and COVID-19 Literature Surveillance Team in one place, standardizing metadata and applying NLP to make these sources searchable and more accessible. Read more about our data sources.
Multiple filters can be applied to search terms. Filters can be narrowed down using the predictive search feature. Results can also be sorted by best match, date, or name.
Search results can be filtered by:
- a date range,
- type – publications (journal articles, preprints), datasets, protocols, and more,
- source – litcovid, medRxiv, bioRxiv, Figshare, and more,
- funding – NIAID, etc.,
- keywords – D614G, ACE2, biomarkers, etc.
- trial intervention, measurement technique, or variable measured.
As the world turns it focus to the new COVID-19 variants and researchers are once again placed under tremendous pressure to pivot, adapt, and stay ahead of the high volume of developing information about these viral mutations, outbreak.info can ease some of the strain caused by the infodemic.
What has been discovered this week about the B.1.1.7 variant?
Since the detection of SARS-CoV-2 lineage B.1.1.7 in the United Kingdom, a growing number of preprints have been released daily that aim to help researchers solve more of the puzzle. In the past week, a few notable contributions include:
- UK and American researchers team up to show that bidirectional contact tracing can substantially slow the spread of B.1.1.7 even where large fractions of the population refuse to comply.
- Researchers from KU Leuven suggest B.1.1.7 most likely occurred by global dispersal rather than convergent evolution from multiple sources.
- Researchers at the Awadalla Lab use machine learning tools to map evolutionary fitness and show that different rates of positive selection are driving dispersal of SARS-CoV-2 globally.
- Swiss researchers detect the B.1.1.7 variant in wastewater samples two weeks before detection in clinical samples in Switzerland.