Rapid Reviews: COVID-19 (RR:C19), an open-access overlay journal published by the MIT Press that accelerates peer review of COVID-19-related research preprints, is currently soliciting reviews of the following COVID-19 preprints. The preprints have been selected for review because they have been flagged as potentially misleading. Preprints with two finished reviews should be published within 10-14 days.
Highlights from Rapid Reviews editorial team: ‘Measuring the missing: greater racial and ethnic disparities in COVID-19 burden after accounting for missing race/ethnicity data’ by Katie Labgold, et al; ‘Seroprevalence of SARS-COV-2 antibodies in Scottish healthcare workers’ by Hani Abo-Leyah, et al; and ‘Quantifying the impact of quarantine duration on COVID-19 transmission’ by Peter Ashcroft, et al; ‘Ultrasensitive and selective detection of SARS-CoV-2 using thermotropic liquid crystals and image-based machine learning’ by Yang Xu, et al; ‘A sew-free origami mask for improvised respiratory protection’ by Jonathan Realmuto, et al; ‘Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer’ by Naveen Singh, et al; ‘SARS-CoV-2 viral budding and entry can be modeled using virus-like particles’ by Caroline Plescia, et al; ‘SARS-CoV-2 cell entry gene ACE2 expression in immune cells that infiltrate the placenta in infection-associated preterm birth’ by Phatcharawan Lye, et al; and so on.
RR:C19 is published by the MIT Press and the editorial offices are located at UC Berkeley, headed by editor-in-chief Stefano M. Bertozzi, Professor of Health Policy and Management and Dean Emeritus of the School of Public Health at University of California Berkeley. The journal is funded by a grant from the Patrick J. McGovern Foundation and hosted on PubPub, an open-source publishing platform from the Knowledge Futures Group.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.