We presented a general methodology capable of interpreting quantitatively emerging disease surveillance data in real time with quantified uncertainty that complements other methods proposed recently [21, 29, 30, 32] . Although we illustrated the method with data for H5N1 influenza, these inference strategies are general and can be applied to time series from other communicable diseases. We verified that the model developed here also applies to standard epidemics, yielding agreement with previous estimates of R for the 1918 influenza pandemic in US cities [14, 44] (Figures S5, S6 in Supporting Information) and with other estimation methods [34] . We have also shown how to construct p-value statistical significance tests suitable for automatically monitoring changes in transmissibility of (emerging) communicable diseases [43] .