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R0 (version 1.2-6)

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, ...)

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

Value

estimates
List containing all results from called methods.
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)

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
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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