EpiInvert

EpiInvert (version 0.3.1, December 2022)

Using variational techniques we address some epidemiological problems as the seasonal-trend daily incidence curve decomposition or the estimation of the functional relationship between epidemiological time series. We also propose a learning method for the short time forecast of the trend incidence curve.

Vignettes of the main package functionalities

• EpiInvert : an incidence curve decomposition by inverting the renewal equation.

• EpiInvertForecast

  a learning method for the short time forecast of the trend incidence curve.

• EpiIndicators : estimation of the delay and ratio between epidemiological indicators.

We also present in Rt Comparison a comparative analysis of the methods : EpiInvert, EpiEstim, Wallinga-Teunis and EpiNow2.

EpiInvert Installation

You can install the development version of EpiInvert from GitHub with:

 install.packages("devtools")
 devtools::install_github("lalvarezmat/EpiInvert")

Example

We attach some required packages

library(EpiInvert)
library(ggplot2)
library(dplyr)
library(grid)

Loading data on COVID-19 daily incidence up to 2022-05-05 for France, Germany, the USA and the UK:

data(incidence)
tail(incidence)
#>           date   FRA    DEU    USA    UK
#> 828 2022-04-30 49482  11718  23349     0
#> 829 2022-05-01 36726   4032  16153     0
#> 830 2022-05-02  8737 113522  81644    32
#> 831 2022-05-03 67017 106631  61743 35518
#> 832 2022-05-04 47925  96167 114308 16924
#> 833 2022-05-05 44225  85073  72158 12460

Loading some festive days for the same countries:

data(festives)
head(festives)
#>          USA        DEU        FRA         UK
#> 1 2020-01-01 2020-01-01 2020-01-01 2020-01-01
#> 2 2020-01-20 2020-04-10 2020-04-10 2020-04-10
#> 3 2020-02-17 2020-04-13 2020-04-13 2020-04-13
#> 4 2020-05-25 2020-05-01 2020-05-01 2020-05-08
#> 5 2020-06-21 2020-05-21 2020-05-08 2020-05-25
#> 6 2020-07-03 2020-06-01 2020-05-21 2020-06-21

Executing EpiInvert using Germany data:

res <- EpiInvert(incidence$DEU,"2022-05-05",festives$DEU)

Plotting the results:

EpiInvert_plot(res)

For a detailed description of EpiInvert outcomes see the EpiInvert vignette.