Rapid Reviews Infectious Diseases
RR\ID (Rapid Reviews\Infectious Diseases) is an open-access overlay journal that accelerates peer review of important infectious disease-related research preprints.
Latest preprint reviews
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Recombinant SARS-CoV-2 genomes circulated at low levels over the first year of the pandemic
This article has 4 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Trends in and Factors Associated With Out-of-Pocket Spending for COVID-19 Hospitalizations From March 2020 to March 2021
This article has 3 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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SARS-CoV-2 variant evolution in the United States: High accumulation of viral mutations over time likely through serial Founder Events and mutational bursts
This article has 9 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Ultrapotent antibodies against diverse and highly transmissible SARS-CoV-2 variants
This article has 58 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Assessing the Mortality Impact of the COVID-19 Pandemic in Florida State Prisons
This article has 7 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Vitamin D and COVID-19 susceptibility and severity in the COVID-19 Host Genetics Initiative: A Mendelian randomization study
This article has 16 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Excess mortality associated with the COVID-19 pandemic among Californians 18–65 years of age, by occupational sector and occupation: March through November 2020
This article has 8 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave
This article has 12 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Viral Sequencing to Investigate Sources of SARS-CoV-2 Infection in US Healthcare Personnel
This article has 13 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Improved COVID-19 Serology Test Performance by Integrating Multiple Lateral Flow Assays using Machine Learning
This article has 4 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT