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Comment
. 2020 Nov 17;117(46):28549-28551.
doi: 10.1073/pnas.2020200117. Epub 2020 Nov 3.

Predicting an epidemic trajectory is difficult

Claus O Wilke  1 , Carl T Bergstrom  2
Affiliations
Comment

Predicting an epidemic trajectory is difficult

Claus O Wilke et al. Proc Natl Acad Sci U S A. .
No abstract available

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Conflict of interest statement

Competing interest statement: C.T.B. consults on COVID testing for Color Genomics. C.O.W. has no competing interests.

Figures

Fig. 1.
Fig. 1.
Visualizing uncertainty in predicting epidemic outcomes. All three panels display the same scenario, an epidemic that has been developing for 33 days. In this particular example, given the observed caseloads for the initial 33 days, there is a 70% chance that the epidemic is contained, and thus a 30% chance of unbounded growth. (A) Median outcome (solid orange line) with uncertainty cone indicating the range of outcomes that have 95% probability. (B) Sample of 35 independent, equally likely individual outcomes. (C) Frequency framing. Each square indicates one possible outcome. Light squares represent epidemics that are contained, and dark squares represent epidemics that are not contained. Simulation data courtesy of Mario Castro.
See this image and copyright information in PMC

Comment on

References

    1. Castro M., Ares S., Cuesta J. A., Manrubia S., The turning point and end of an expanding epidemic cannot be precisely forecast. Proc. Natl. Acad. Sci. U.S.A. 117, 26190–26196 (2020). - PMC - PubMed
    1. Lloyd-Smith J. O., Schreiber S. J., Kopp P. E., Getz W. M., Superspreading and the effect of individual variation on disease emergence. Nature 438, 355–359 (2005). - PMC - PubMed
    1. Wallinga J., Lipsitch M., How generation intervals shape the relationship between growth rates and reproductive numbers. Proc. Biol. Sci. 274, 599–604 (2007). - PMC - PubMed
    1. Juul J. L., Græsbøll K., Christiansen L. E., Lehmann S., Fixed-time descriptive statistics underestimate extremes of epidemic curve ensembles. arXiv:2007.05035 (9 July 2020).
    1. Bauer P., Thorpe A., Brunet G., The quiet revolution of numerical weather prediction. Nature 525, 47–55 (2015). - PubMed

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