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EpiEstim

Summary

The R-package EpiEstim implements a Bayesian approach for quantifying transmissibility over time during an epidemic. More specifically, it allows estimating the instantaneous and case reproduction numbers during an epidemic for which a time series of incidence is available and the distribution of the serial interval (time between symptoms onset in a primary case and symptoms onset in secondary case) is _ more or less precisely _ known.


Features

   implementation of the approach of Cori et al. (AJE, 2013) for estimating the instantaneous reproduction number from incidence data and assumptions about the serial interval distribution.

   implementation of the approach of Wallinga and Teunis (AJE, 2004) for estimating the case reproduction number from incidence data and given a serial interval distribution.

   graphics to jointly visualize the epidemic curve, the estimated reproduction number and the serial interval distribution used for estimation.

   5 datasets from the literature (corresponding to outbreaks of pandemic influenza, smallpox, measles and severe acute respiratory syndrome) including both time series of incidence and serial interval distribution.

 

Download/installation

The current version of EpiEstim is 1.1-2 for R 3.0.2. EpiEstim can be installed from R as other packages by typing:

install.packages("EpiEstim”)

See CRAN for manual downloads.

 

Documentation

EpiEstim is distributed with a reference manual documenting every function of the package.

The methods implemented in EpiEstim are described in Cori A, Ferguson NM, Fraser C, Cauchemez S (2013) A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics. Am J Epidemiol.

 

Feature request / bug report

If there is a feature you would like to suggest, or a bug you would like to report, please email the author: a.cori@imperial.ac.uk.

 

Authors/contributors

EpiEstim is developed by Anne Cori

The original method has been developed by Anne Cori, Neil Ferguson, Christophe Fraser and Simon Cauchemez.


References

Cori A, Ferguson NM, Fraser C, Cauchemez S (2013) A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics. Am J Epidemiol.

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