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EVI

EVI: the Epidemic Volatility Index as an early-warning tool for epidemic waves

Installation

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

Basic functions of EVI package

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

Troubleshooting

In case an error during download occur try the following

remotes::install_github("ku-awdc/EVI", force = TRUE, dependecies = TRUE)

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Version

Install

install.packages('EVI')

Monthly Downloads

181

Version

0.2.0-0

License

GPL (>= 3)

Maintainer

Konstantinos Pateras with contributions from Larisa Kosidou

Last Published

December 5th, 2023

Functions in EVI (0.2.0-0)

status

A function that defines the true status based on the case definition
rollsd

Rolling standard deviation
deviant_update

This function is used after first running the deviant function
EVI-package

EVI: Epidemic Volatility Index as an Early-Warning Tool
evi

Calculation of the Epidemic Volatility Index
evifcut

Sensitivity-Specificity estimation for each cut-off value and rolling window size
evi.graphs

This function produces plots of the time series data with the EVI predictions.
cEVI_fun

Calculation of the convergence Epidemic Volatility Index
deviant

This function produces the Epidemic Volatility Index based output data (beta)
evirlap

Combining multiple epidemic volatility indices into a multi-early warning index plot
indic

Issue of an Early Warning
medvol

Function that calculates the standard deviation
mova

Function that calculates the moving average of a time series
Italy

Cases of the first 149 days of the Covid-19 pandemic in Italy.
Austria

Cases of the first 149 days of the Covid-19 pandemic in Austria.