Quantifying transmissibility during epidemics is essential to calibrate and adjust public health responses. Transmissibility at a certain time step can be measured by the instantaneous reproduction number R, the ratio of the number of new infections in this time step to the current infectivity due to previously infected cases. In this package, we propose a ready-to-use tool for estimating R from the incidence time-series. This tool uses novel analytical estimates of R, and also incorporates uncertainty on the serial interval distribution.
We also propose an implementation of the method proposed by Wallinga and Teunis (AJE, 2004) to estimate a related, though different, quantity, the case reproduction number (see Fraser, PLoS One, 2007 for the difference between the two).
The functions implemented in this package are:
DiscrSI, which computes the discrete distribution of the serial interval with a given mean and standard deviation;
OverallInfectivity, which calculates, at each time step, the overall infectivity due to previously infected individuals;
EstimateR, which estimates, for each time step, the instantaneous reproduction number, given the incidence time series and the serial interval distribution.
WT, which estimates, for each time step, the case reproduction number, given the incidence time series and the serial interval distribution.
Together with the package a few datasets are provided that contain time series of incidence and serial interval distribution for the following epidemics:
Measles1861: 1861 measles epidemic in Hagelloch, Germany;
Flu1918: 1918 H1N1 influenza pandemic in Baltimore;
Smallpox1972: 1972 smallpox epidemic in Kosovo;
SARS2003: 2003 severe acute respiratory syndrome (SARS) epidemic in Hong Kong;
Flu2009: 2009 H1N1 influenza pandemic in a school in Pennsylvania.
Package: EpiEstim
Type: Package
Version: 1.0-0
Date: 2012-06-06
License: GPL (>=2)
Cori, A. et al. A new framework and software to estimate time-varying reproduction numbers during epidemics. (submitted) Fraser, C. (2007) Estimating individual and household reproduction numbers in an emerging epidemic. PLoS One 2(1): e758. Wallinga, J. and P. Teunis (2004). Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures. Am J Epidemiol 160(6): 509-516.