Lessons from COVID-19: Finding, Synthesizing and Communicating Research that Matters (FREE)

Keynote: Summary of the NLM-publisher Collaboration on COVID-19 

Patricia Flatley Brennan, RN, PhD, Director, National Library of Medicine

To respond to the urgent and widespread demand for speedy, open, and convenient access to content related to COVID-19 and the associated pandemic, over 50 publishers worked closely with NLM to provide centralized discovery. This talk explores the lessons learned from this public/private effort, and how they might inform plans to provide sustainable solutions for future public health emergencies. This talk will provide context for a subsequent series of panels from a range of stakeholders relevant to the information and data.

Panel 1: Publishers Strategies Faster Peer Review, Content Identification, and Curation Methods – Evolution of the Process

Publishers responded to the COVID-19 pandemic by putting business-as-usual aside and implementing accelerated review processes for COVID-19 related manuscripts, identifying and opening published papers related to treatment and research. A variety of approaches were taken to speed processes involved with accelerating research output, while maintaining quality, ensuring relevance, and disseminating the most relevant evidence to researchers, policymakers, and clinical responders. This panel looks at the techniques, adapted workflows, and the evolution of those processes over the first year of the pandemic from key publishers’ perspectives.

Panel 2: Search Strategies – The Machine Element: Signals and noise: How AI and ML techniques are being deployed to track a global pandemic.

With the onset of the pandemic, researchers, scientists and publishers and curators of knowledge have faced the daunting challenge of keeping pace with an overwhelming amount of new data. Many publishers have made COVID research freely available. The NLM continues to make sure it is centralized, searchable and available for text and data mining to the research community. Yet as new data and discoveries are introduced, the challenge of identifying and making sense of complex and rapidly evolving information in a way that brings together the most important points, remains a significant challenge. This panel will explore how AI and ML have become essential tools in navigating a rapidly shifting and expanding body of evidence to track a wide-reaching global pandemic.

Moderator: Ian Mulvany, Chief Technology Officer, The BMJ 

George Tsatsaronis, PhD – Vice President, Data Science Research Content & Operations, Elsevier 

Zubair Afzal, PhD – Director of Data Science, Elsevier

Lucy Lu Wang, PhD –  Young Investigator, Allen Institute for Artificial Intelligence

Break

Panel 3: What COVID-19 Research Should I Ignore? The Clinician’s Perspective

The COVID-19 pandemic is unprecedented in many ways. However, the targeted acceleration and “opening up” of related research may have the most significant long-term impact on clinical practice by fundamentally reconfiguring the parameters of the relationship between health science and society. So much research has been generated, so quickly, which remains available to everybody without restriction. Relevant data, preprints, code, protocols and publications are being shared to an unparalleled extent, hastening progress in battling COVID-19 and related illnesses. How do clinicians and the public cope with this tsunami of information? How do they interpret the constantly changing and sometimes conflicting emphases from authoritative and trusted sources -leaders, media and scientists –and adjust their own actions to protect their families and their patients? The current pandemic has been accompanied by a misinformation pandemic. How do clinicians choose what is valid and relevant, while ignoring the noise?

Moderator: Nick Campbell, PhD, Vice President, Academic Affairs, Springer Nature

Paul Garner – Co-coordinator, Centre for Evidence Synthesis for Global Health, Co-ordinating Editor of the Cochrane Infectious Diseases Group,Director of the Research, Evidence and Development Initiative (READ-It)

Laura Helmuth, PhD – Editor in Chief, Scientific American

Jason Smith, MLIS – Medical/Health Sciences Librarian with the Department of Veterans Affairs

Closing comments