The purpose of this letter is to raise a few issues with the methodology of a recent paper by Ganyani et al. [1], which aimed to estimate the parameters of the generation interval of coronavirus disease (COVID-19)
We developed a generative model for key epidemiological events in COVID-19 patients and derived explicit formulae to correct for selection bias. We find that several early analyses of the COVID-19 pandemic were severely biased due to sample …
We propose a Bayesian model averaging method to account for the uncertainty about instrument validity in Mendelian randomization. This model is extended to allow for a large fraction of SNPs violating the InSIDE assumption.
We analyzed 46 2019-nCoV cases confirmed in Japan, Korea, Singapore, Taiwan, Hong Kong, and Macau who traveled from Wuhan before its lockdown. The known travel history allows us to narrow down when the cases were first infected. Our estimate of the …