This preprint estimates a high R0 and attempts to predict future spread. While not completely implausible, the confidence intervals they attach to their estimates are too narrow and don't reflect the true uncertainty and stochasticity of the dynamics.https://www.medrxiv.org/content/10.1101/2020.01.23.20018549v1 …
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I’d like to know the potential biases arising from ignoring among-case variation in R0 (which, by analogy to SARS, could be very high indeed).
I would argue that variation in the number of secondary cases is important for establishing new transmission clusters/chains, but does influence the overall epidemic growth when incidence is high. Also see Julien Riou’s manuscript on #nCoV2019:https://github.com/jriou/wcov
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does = doesn't?
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doesn’t, indeed!
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