Call for transparency of COVID-19 models
Science2020Vol. 368(6490), pp. 482–483
Citations Over TimeTop 1% of 2020 papers
C. Michael Barton, Marina Alberti, Daniel P. Ames, Jo‐An Atkinson, Jerad Bales, Edmund Burke, Min Chen, Saikou Y. Diallo, David J. D. Earn, Brian D. Fath, Zhilan Feng, C. L. M. H. Gibbons, Ross A. Hammond, Jane M. Heffernan, Heather Houser, Peter S. Hovmand, Birgit Kopainsky, Patricia L. Mabry, Christina Mair, Petra Meier, Rebecca Niles, Brian A. Nosek, Nathaniel Osgood, Suzanne A. Pierce, Gary Polhill, Lisa A. Prosser, Erin Robinson, Cynthia Rosenzweig, Shankar Sankaran, Kurt C. Stange, Gregory E. Tucker
Abstract
A hallmark of science is the open exchange of knowledge. At this time of crisis, it is more important than ever for scientists around the world to openly share their knowledge, expertise, tools, and technology. Scientific models are critical tools for anticipating, predicting, and responding to complex biological, social, and environmental crises, including pandemics. They are essential for guiding regional and national governments in designing health, social, and economic policies to manage the spread of disease and lessen its impacts. However, presenting modeling results alone is not enough. Scientists must also openly share their model code so that the results can be replicated and evaluated.
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