This is an R package implementing the epidemic volatility index (EVI), as discussed by Kostoulas et. al. (2021) and variations by Pateras et. al. (2023). EVI is a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold.
EVI: the Epidemic Volatility Index as an early-warning tool for epidemic waves
To install the current source from GitHub use:
install.packages(c("devtools", "remotes"))
require(devtools)
require(remotes)
remotes::install_github("ku-awdc/EVI")
To install a stable version from the drat repository use:
## Will be added once a stable version is available
require(EVI)
To load some example data:
data("Italy")
To run EVI analysis on the example data:
deviant(Italy$Cases)
To run EVI analysis when you already have historical data and need an update with the influx of new data you do the following: first you analyze the historical data. Let’s say we have first observed only the 148 cases from the Italian data. We initially run the deviant function:
deviant(Italy$Cases[1:148])
As a new observation (or observations) comes in we need to update our output file by adding the EVI output for the new case(s) as a new row(s). This is done by using the deviant_update function:
deviant_update(Italy$Cases[1:149])
This has as a result an updated output file (the “EVI_output” file) with 149 rows now, after the addition of the row from the analysis of the newly observed data.
To create a plot of the analysed data:
evi.graphs(EVI_output)
The basic two functions of the EVI analysis are deviant() and evi.graphs(). For help on these functions type:
?deviant
?deviant_update
?evi.graphs
In case an error during download occur try the following
remotes::install_github("ku-awdc/EVI", force = TRUE, dependecies = TRUE)