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yusufHAIGermany

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The yusufHAIGermany R package offers a reproducible simulation and visualisation framework for examining Healthcare-Associated Infections (HAIs) in Germany.
It is inspired by the Eurosurveillance study by Zacher et al. (2019).
“Application of a new methodology and R package reveals a high burden of healthcare-associated infections (HAI) in Germany compared to the average in the European Union/European Economic Area, 2011 – 2012.”

This package generates daily, weekly, and monthly simulated datasets calibrated from the 2011 – 2012 ECDC PPS (Point Prevalence Survey) data.

This package can be accessed online, with the website explaining it, and the shiny dashboard can be reached via the App menu. Here is the link to access it: https://yusufkurniar.github.io/yusufHAIGermany/

Installation

The package can be installed by running the latest version from GitHub:

# install.packages("pak")
pak::pak("yusufkurniar/yusufHAIGermany")

Or from source:

# install.packages("remotes")
remotes::install_github("yusufkurniar/yusufHAIGermany")

Run the Live Shiny App

The app provides the interactive dashboard to analyse the dataset.

See: Shiny App

Run the Shiny App Locally 

# install.packages("yusufHAIGermany")  # or devtools::install_local("path")
yusufHAIGermany::launch_app()

Launch the built-in Germany HAI Explorer directly from your R console:

App Features

  • Choose data frequency (Monthly, Weekly, or Daily)
  • Explore time-series trends of simulated infections
  • View distribution analysis metric, heatmap analysis metric, and animated monthly analysis

Datasets

The dataset is combination of orginal source and the simulated time series. See the detail in: articles/data-description.html

Dataset Description Frequency Data Type
sim_daily Daily-level simulated infections and DALYs Daily data.frame
sim_weekly Weekly aggregated simulations Weekly data.frame
sim_monthly Monthly aggregated simulations Monthly data.frame

Variable Descriptions

Variable Description Type Used in Visualisation
date Observation date Date X-axis for time-based plots
hai Infection type (UTI, HAP, SSI, BSI, CDI) Factor Color grouping
cases Estimated cases Numeric Bar & line charts
deaths Estimated deaths Numeric Bar charts & annotations
dalys Disability-adjusted life years Numeric Heatmap or cumulative chart
freq Frequency level Character Filter selector

These simulations introduce mild seasonality and random variation to reflect uncertainty in real-world HAI burdens.

Data Source

Original data reference:

Zacher, B., Haller, S., Willrich, N., Walter, J., Abu Sin, M., Cassini, A., Plachouras, D., Suetens, C., Behnke, M., Gastmeier, P., Wieler, L. H., & Eckmanns, T. (2019).
Application of a new methodology and R package reveals a high burden of healthcare-associated infections (HAI) in Germany compared to the average in the European Union/European Economic Area, 2011–2012.
Eurosurveillance, 24(46). https://doi.org/10.2807/1560-7917.ES.2019.24.46.1900135

Data licensed under Creative Commons Attribution 4.0 (CC BY 4.0).

Example Usage 

library(yusufHAIGermany)

# Explore simulated monthly data
head(sim_monthly)

# Summarise DALYs by infection type
library(dplyr)
sim_monthly |>
  group_by(hai) |>
  summarise(total_dalys = sum(dalys))

Vignettes

Full documentation is provided here:

To browse locally in R:

browseVignettes("yusufHAIGermany")

# or open directly:
vignette("data-description", package = "yusufHAIGermany")
vignette("examples", package = "yusufHAIGermany")
vignette("germany-HAI-explorer", package = "yusufHAIGermany")
vignette("get-started", package = "yusufHAIGermany")

Changelog

All updates are documented in NEWS.md. The latest version is 0.1.3, which includes the most recent integrated dataset and an updated Shiny dashboard.

License

  • Package code © 2025 Yusuf Romadhon, licensed under MIT License.
  • Data source: ECDC PPS 2011–2012, licensed under CC BY 4.0.

Credits

Developed for ETC5523 – Communicating with Dashboard (Monash University, 2025).
Instructor: Michael Lydeamore & Maliny Po

Built with: shiny, bslib, ggplot2, plotly, dplyr, tidyr, lubridate, scales, glue, yusufHAIGermany.

Developed with: devtools, usethis, roxygen2, pkgdown, knitr, rmarkdown, rsconnect.

  1. Install package: pak::pak("yusufkurniar/yusufHAIGermany")
  2. Launch app: launch_app()
  3. View vignette: browseVignettes("yusufHAIGermany")
  4. Check changelog: NEWS.md
  5. View documentation via pkgdown site