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aedseo

Description

The Automated and Early Detection of Seasonal Epidemic Onset and Burden Levels (aedseo) package provides a powerful tool for automating the early detection of seasonal epidemic onsets in time series data. It offers the ability to estimate growth rates for consecutive time intervals. With use of the average observations within those intervals and an estimated disease-specific threshold it also offers the possibility to estimate seasonal onset of epidemics. Additionally it offers the ability to estimate burden levels for seasons based on historical data. It is aimed towards epidemiologists, public health professionals, and researchers seeking to identify and respond to seasonal epidemics in a timely fashion.

Installation

# Install aedseo from CRAN
install.packages("aedseo")

Development version

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

# install.packages("devtools")
devtools::install_github("ssi-dk/aedseo")

Getting started

To quickly get started with aedseo, follow these steps:

  1. Install the package using the code provided above.
  2. Load the package with library(aedseo).
  3. Create a time series data object (tsd) from your data using the to_time_series() function or generate_seasonal_data() functions.
  4. Apply the combined_seasonal_output() function to get a comprehensive seasonal analysis with seasonal onset and burden levels.

Vignette

For a more detailed introduction to the workflow of this package, see the Get Started vignette or run; vignette("aedseo").

Contributing

We welcome contributions to the aedseo package. Feel free to open issues, submit pull requests, or provide feedback to help us improve.

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Version

Install

install.packages('aedseo')

Monthly Downloads

388

Version

1.1.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Lasse Engbo Christiansen

Last Published

January 23rd, 2026

Functions in aedseo (1.1.0)

epi_calendar

Determine Epidemiological Season
aedseo-package

aedseo: Automated and Early Detection of Seasonal Epidemic Onset and Burden Levels
estimate_disease_threshold

Estimate the disease specific threshold of your time series data
autoplot

Autoplot a tsd object
consecutive_growth_warnings

Create a tsd_growth_warning object to count consecutive significant observations
combined_seasonal_output

Compute seasonal onset and burden levels from seasonal time series observations.
fit_growth_rate

Fit a growth rate model to time series cases.
fit_percentiles

Fits weighted observations to distribution and returns percentiles
historical_summary

Summarises estimates like seasonal peak and onset from all available seasons
generate_seasonal_data

Generate Simulated Data of Seasonal Waves as a tsd object
plot.tsd

Create a complete 'ggplot' appropriate to a particular data type
predict.tsd_onset

Predict Cases for Future Time Steps
summary.tsd_onset

Summary method for tsd_onset objects
summary.tsd_burden_levels

Summary method for tsd_burden_levels objects
to_time_series

Create a tibble-like tsd (time-series data) object from time series data and corresponding dates.
seasonal_onset

Automated and Early Detection of Seasonal Epidemic Onset
seasonal_burden_levels

Compute burden levels from seasonal time series observations of current season.