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COVID-19 Volunteer Scientist Database, looking for public health and health equity expertise.

Dr. Tayab Waseem, PhD, an immunologist and an expert in machine learning (and also currently a medical student) is looking for public health and health equity expertise

He is part of a research project to help scientists synthesize, in real-time, the more than 136,000 scientific articles that have been published with respect to COVID-19. The project aims to evaluate the use of an AI tool to aid in producing rapid scoping evidence reviews.

They have an interdisciplinary, cross-institutional team developing an AI to help conduct literature reviews by scouring the web for papers and collating them into tables to help facilitate the synthesis of information. This AI will help answer important clinical questions. You can read about the work in NEJM, Nature, and Science.

The objective is to develop an AI tool that can scan the published, peer-reviewed literature to help answer specific research questions. This tool will create summary tables providing a comprehensive list of literature and relevant metrics for each COVID-19 research question. Ideally, these tables will help aggregate all relevant data needed to provide a meaningful overview of pertinent evidence. This might then aid rapid production of systematic literature reviews, ultimately yielding a systematic literature review in a fraction of the time it would take without aid of AI technology.

OPPORTUNITIES: Please feel free to forward widely!

1) The AI development team needs to know what questions you'd like answered, related to COVID-19.

To submit your questions to the project - fill out this survey

2) To take it one step further, a research team is recruiting participants (you!) for an IRB-approved research project. The purpose would be twofold: provide information on the utility of this technology and also to publish your review in the peer-reviewed literature. They are looking for groups that are interested in writing up a rapid review on any COVID-19 related topics. A PI for a specific research question will split the research team into two "arms”: one will use the AI system, and the other will not (serving as the “control”). Each member of the control team will individually conduct the steps needed to complete their study type keeping track of specific time metrics, including: time spent searching for sources, time spent extracting information from sources, time spent synthesizing and writing up the study. Members of the “AI” group will perform the same steps but will be provided an automatically generated table as a starting point. Once complete, every member of the study will submit a compiled evidence review to the PI, who will evaluate these for completeness. All study members will complete a post-study utility survey (3 questions). The PI at this point may aggregate all of the studies and submit to an appropriate journal of their choosing (no need to sit on valuable data).

To learn more about participating in this study, please send an email to

For further details on any of this, please contact: Dr. Tayab Waseem at

Thank you for helping bring a public health / health equity focus to the rapidly developing COVID-19 evidence base!

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