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EpiEstim method, software, and documentation

EpiEstim is a method and set of software pieces to estimate the instantaneous reproduction number Rt in real time during epidemics.

The underlying methods are described in two publications:

• Cori A., et al. (2013). A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics, American Journal of Epidemiology, 178(9):1505–1512. https://doi.org/10.1093/aje/kwt133
• Thompson, R. N., et al. (2019). Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics, 29, [100356]. https://doi.org/10.1016/j.epidem.2019.100356

The methods are implemented in the following pieces of software:

• R package EpiEstim, available on Github and on CRAN
• Web application
• Excel spreadsheet

FAQ on EpiEstim

Why are the estimates of R from estimate_R different from what I expect?

estimate_R produces Bayesian estimates of R so depend on the data but also on the prior chosen (see here and here for details of the method). By default in estimate_R the prior is set to a mean of 5 and a standard deviation of 5. You can change these settings using the function make_config. It is recommended to check whether changing the prior dramatically affects the estimates, to assess whether results are primarily driven by the data or not.

Can I use EpiEstim to estimate R from coarsely aggregated data, e.g. weekly data?

At the moment EpiEstim only allows estimation of R using the same time unit for the incidence and the serial interval data. If you want to estimate R from weekly incidence data, you will therefore have to specify the distribution of the serial interval with week as the time unit.