R0 (version 1.2-6)

est.R0.EG: Estimate R from exponential growth rate

Description

Estimate R from exponential growth rate.

Usage

est.R0.EG(epid, GT, t = NULL, begin = NULL, end = NULL, date.first.obs = NULL, time.step = 1, reg.met = "poisson", checked = FALSE, ...)

Arguments

epid
object containing epidemic curve data. see Details.
GT
generation time distribution
t
Vector of dates at which incidence was calculated
begin
At what time estimation begins
end
Time at which to end computation
date.first.obs
Optional date of first observation, if t not specified
time.step
Optional. If date of first observation is specified, number of day between each incidence observation
reg.met
Regression method used. Default is "poisson" (for GLM), but can be forced to "linear".
checked
Internal flag used to check whether integrity checks were ran or not.
...
parameters passed to inner functions

Value

R
The estimate of the reproduction ratio.
conf.int
The 95% confidence interval for the R estimate.
r
Exponential growth rate of the epidemic.
conf.int.r
Confidence interval of the exponential growth rate of the epidemic.
Rsquared
The deviance R-squared measure for the considered dates and model.
epid
object containing epidemic curve data. see Details.
GT
generation time distribution
data.name
Name of the data used in the fit.
begin
At what time estimation begins
begin.nb
The number of the first day used in the fit.
end
Time at which to end computation
end.nb
The number of the las day used for the fit.
fit
Method used for fitting.
pred
Prediction on the period used for the fit.
method
Method for estimation.
method.code
Internal code used to designate method.

Details

For internal use. Called by est.R0.

method "poisson" uses Poisson regression of incidence. method "linear" uses linear regression of log(incidence)

CI is computed from the 1/M(-r) formula using bounds on r from the Poisson regression.

References

Wallinga, J., and M. Lipsitch. "How Generation Intervals Shape the Relationship Between Growth Rates and Reproductive Numbers." Proceedings of the Royal Society B: Biological Sciences 274, no. 1609 (2007): 599.

Examples

Run this code
library(R0)

## Data is taken from the paper by Nishiura for key transmission parameters of an institutional
## outbreak during 1918 influenza pandemic in Germany)

data(Germany.1918)
mGT<-generation.time("gamma", c(3, 1.5))

est.R0.EG(Germany.1918, mGT, begin=1, end=27)
## Reproduction number estimate using  Exponential Growth 
## R :  1.525895[ 1.494984 , 1.557779 ]

Run the code above in your browser using DataLab