The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.

About Followers

Latest preprint reviews

  1. Modeling the Spatiotemporal Epidemic Spreading of COVID-19 and the Impact of Mobility and Social Distancing Interventions

    1. Alex Arenas
    2. Wesley Cota
    3. Jesús Gómez-Gardeñes
    4. Sergio Gómez
    5. Clara Granell
    6. Joan T. Matamalas
    7. David Soriano-Paños
    8. Benjamin Steinegger

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Disaggregating Asian Race Reveals COVID-19 Disparities Among Asian American Patients at New York City’s Public Hospital System

    1. Roopa Kalyanaraman Marcello
    2. Johanna Dolle
    3. Areeba Tariq
    4. Sharanjit Kaur
    5. Linda Wong
    6. Joan Curcio
    7. Rosy Thachil
    8. Stella S. Yi
    9. Nadia Islam

    Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

    4 evaluationsAppears in 2 listsLatest version Latest activity

  3. Effectiveness of quarantine measure on transmission dynamics of COVID-19 in Hong Kong

    1. Hsiang-Yu Yuan
    2. Axiu Mao
    3. Guiyuan Han
    4. Hsiangkuo Yuan
    5. Dirk Pfeiffer

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Community Memory of COVID-19 Infections Post Lockdown as a Surrogate for Incubation Time

    1. Meher K. Prakash

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Religious affiliation and COVID-19-related mortality: a retrospective cohort study of prelockdown and postlockdown risks in England and Wales

    1. Charlotte Hannah Gaughan
    2. Daniel Ayoubkhani
    3. Vahe Nafilyan
    4. Peter Goldblatt
    5. Chris White
    6. Karen TIngay
    7. Neil Bannister

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Modeling the relative risk of SARS-CoV-2 infection to inform risk-cost-benefit analyses of activities during the SARS-CoV-2 pandemic

    1. John E. McCarthy
    2. Barry D. Dewitt
    3. Bob A. Dumas
    4. Myles T. McCarthy

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. The Effect of GDP and Distance on Timing of COVID-19 Spread in Chinese Provinces in 2020

    1. Alice Kuan
    2. Mingxin Chen
    3. David Bishai

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. SARS-COV-2 THREE FORCING SEASONALITIES: POLICIES, ENVIRONMENT AND URBAN SPACES

    1. Charles Roberto Telles

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. The detection and stability of the SARS-CoV-2 RNA biomarkers in wastewater influent in Helsinki, Finland

    1. Anna-Maria Hokajärvi
    2. Annastiina Rytkönen
    3. Ananda Tiwari
    4. Ari Kauppinen
    5. Sami Oikarinen
    6. Kirsi-Maarit Lehto
    7. Aino Kankaanpää
    8. Teemu Gunnar
    9. Haider Al-Hello
    10. Soile Blomqvist
    11. Ilkka T. Miettinen
    12. Carita Savolainen-Kopra
    13. Tarja Pitkänen

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. The competing risk between in-hospital mortality and recovery: A pitfall in COVID-19 survival analysis research

    1. Abderrahim Oulhaj
    2. Luai A. Ahmed
    3. Juergen Prattes
    4. Abubaker Suliman
    5. Ahmed R. Alsuwaidi
    6. Rami H. Al-Rifai
    7. Harald Sourij
    8. Ingrid Van Keilegom

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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