Methods currently used around the world for predicting the development of COVID-19 and other pandemics fail to report precisely on the best and worst case scenarios.
Methods currently used around the world for predicting the development of COVID-19 and other pandemics fail to report precisely on the best and worst case scenarios. Newly developed prediction method for epidemics, published in Nature Physics, solve this problem.
“It is about understanding best and worst case scenarios - and the fact that worst case is one of the most important things to keep track of when navigating through pandemics - regardless whether it be in Denmark, the EU, the USA or the WHO. If you are only presented with an average estimate for the development of an epidemic – not knowing how bad it possible can get, then it is difficult to act politically”, says Professor Sune Lehmann, one of four authors of the article Fixed-time descriptive statistics underestimate extremes of epidemic curve ensembles just published in Nature Physics .
Researchers Jonas L. Juul, Kaare Græsbøll, Lasse Engbo Christiansen and Sune Lehmann, all from DTU Compute, act as advisors to the National Board of Health in Denmark during the corona crisis. And partly based on their own experience as advisors, they have become aware that the existing methods of projecting the development of epidemics such as COVID-19 have a problem in describing the extremes possibilities of the expected development.
Read more at Technical University of Denmark
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