estimate.R: Estimate R0 for one incidence dataset using several methods

Description

Estimate R0 for one incidence dataset using several methods.

Usage

estimate.R(epid = NULL, 
    GT = NULL, t = NULL, 
    begin = NULL, end = NULL, 
    date.first.obs = NULL, 
    time.step = 1, AR = NULL, 
    pop.size = NULL, 
    S0 = 1, methods = NULL, 
    checked = TRUE, ...)

Value

A list with components:

estimates: List containing all results from called methods.
epid: Epidemic curve.
GT: Generation Time distribution function.
t: Date vector.
begin: Begin date for estimation.
end: End date for estimation.

Arguments

epid: Name of epidemic dataset
GT: Generation Time repartition function
t: Date vector
begin: Begin date for estimation. Can be an integer or a date (YYYY-mm-dd or YYYY/mm/dd)
end: End date for estimation. Can be an integer or a date (YYYY-mm-dd or YYYY/mm/dd)
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
AR: Attack rate as a percentage from total population
pop.size: Population size in which the incident cases were observed. See more details in est.R0.AR documentation
S0: Initial proportion of the population considered susceptible
methods: List of methods to be used for R0 estimation/comparison. Must be provided as c("method 1", "method 2", ...)
checked: Internal flag used to check whether integrity checks were ran or not.
...: Parameters passed to inner functions

Author

Pierre-Yves Boelle, Thomas Obadia

Details

Currently, supported methods are Exponential Growth (EG), Maximum Likelihood (ML), Attack Rate (AR), Time-Dependant (TD), and Sequential Bayesian (SB). See references below.

References

est.R0.EG: 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.

est.R0.ML: White, L.F., J. Wallinga, L. Finelli, C. Reed, S. Riley, M. Lipsitch, and M. Pagano. "Estimation of the Reproductive Number and the Serial Interval in Early Phase of the 2009 Influenza A/H1N1 Pandemic in the USA." Influenza and Other Respiratory Viruses 3, no. 6 (2009): 267-276.

est.R0.AR: Dietz, K. "The Estimation of the Basic Reproduction Number for Infectious Diseases." Statistical Methods in Medical Research 2, no. 1 (March 1, 1993): 23-41.

est.R0.TD: Wallinga, J., and P. Teunis. "Different Epidemic Curves for Severe Acute Respiratory Syndrome Reveal Similar Impacts of Control Measures." American Journal of Epidemiology 160, no. 6 (2004): 509.

est.R0.SB: Bettencourt, L.M.A., and R.M. Ribeiro. "Real Time Bayesian Estimation of the Epidemic Potential of Emerging Infectious Diseases." PLoS One 3, no. 5 (2008): e2185.

Examples

Run this code

#Loading package
library(R0)

## Outbreak during 1918 influenza pandemic in Germany)
data(Germany.1918)
mGT<-generation.time("gamma", c(3, 1.5))
estR0<-estimate.R(Germany.1918, mGT, begin=1, end=27, methods=c("EG", "ML", "TD", "AR", "SB"), 
                  pop.size=100000, nsim=100)

attributes(estR0)
## $names
## [1] "epid"      "GT"        "begin"     "end"       "estimates"
## 
## $class
## [1] "R0.sR"

## Estimates results are stored in the $estimates object
estR0
## Reproduction number estimate using  Exponential Growth  method.
## R :  1.525895[ 1.494984 , 1.557779 ]
## 
## Reproduction number estimate using  Maximum Likelihood  method.
## R :  1.383996[ 1.309545 , 1.461203 ]
## 
## Reproduction number estimate using  Attack Rate  method.
## R :  1.047392[ 1.046394 , 1.048393 ]
## 
## Reproduction number estimate using  Time-Dependent  method.
## 2.322239 2.272013 1.998474 1.843703 2.019297 1.867488 1.644993 1.553265 1.553317 1.601317 ...
## 
## Reproduction number estimate using  Sequential Bayesian  method.
## 0 0 2.22 0.66 1.2 1.84 1.43 1.63 1.34 1.52 ...


## If no date vector nor date of first observation are provided, results are the same
## except time values in $t are replaced by index

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