Authors
Andrea Saltelli, Gabriele Bammer, Isabelle Bruno, Erica Charters, Monica Di Fiore, Emmanuel Didier, Wendy Nelson Espeland, John Kay, Samuele Lo Piano, Deborah Mayo, Roger Pielke Jr, Tommaso Portaluri, Theodore M Porter, Arnald Puy, Ismael Rafols, Jerome R Ravetz, Erik Reinert, Daniel Sarewitz, Philip B Stark, Andrew Stirling, Jeroen van Der Sluijs, Paolo Vineis
Publication date
2020/6
Source
Nature
Volume
582
Issue
7813
Pages
482-484
Publisher
Nature Publishing Group
Description
Well before the coronavirus pandemic, statisticians were debating how to prevent malpractice such as p-hacking, particularly when it could influence policy 1. Now, computer modelling is in the limelight, with politicians presenting their policies as dictated by ‘science’2. Yet there is no substantial aspect of this pandemic for which any researcher can currently provide precise, reliable numbers. Known unknowns include the prevalence and fatality and reproduction rates of the virus in populations. There are few estimates of the number of asymptomatic infections, and they are highly variable. We know even less about the seasonality of infections and how immunity works, not to mention the impact of social-distancing interventions in diverse, complex societies.
Mathematical models produce highly uncertain numbers that predict future infections, hospitalizations and deaths under various scenarios. Rather than using …
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A Saltelli, G Bammer, I Bruno, E Charters, M Di Fiore… - 2020