NEWS.md

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

aedseo 0.3.0

Deprecations

• aedseo() is now deprecated. Please use seasonal_onset() instead. A warning is shown when using aedseo() (#41).

• tsd() is now deprecated. Please use to_time_series() instead. A warning is shown when using tsd() (#41).

Features

• Added the seasonal_burden_levels() function, which calculates burden levels based on data from previous seasons with two different methods; "peak_levels" or "intensity_levels" (#37).

• Added the fit_percentiles() function, which optimises a user selected distribution and calculates the percentiles based on observations and weights. It is meant to be used within the seasonal_burden_levels() function (#35, #37) - Renamed fit_quantiles() to fit_percentiles() (#60).

• Added combined_seasonal_output() as the main function to run both seasonal_onset() and seasonal_burden_levels() to get a combined result for the newest season (#44).

• Added consecutive_growth_warnings() function to help the user with a method to define the disease-specific threshold (#80).

• Added a new argument only_current_season to seasonal_onset(), seasonal_burden_levels() and combined_seasonal_output() which gives the possibility to either get output from only the current season or for all available seasons (#45).

• Added historical_summary() which uses a tsd_onset object to summarise historical estimations (#75).

• summary() can now summarise tsd_burden_level objects (#60).

• plot() and autoplot() can now plot tsd_combined_seasonal_output and tsd_consecutive_growth_warning objects (#57, #80).

• Added generate_seasonal_data() to generate synthetic data for testing and documentation purposes (#56).

• Added seasonal_onset() as a replacement for the deprecated aedseo() function (#41).

• Added to_time_series() as a replacement for the deprecated tsd() function (#41).

Improvements

• Enhanced clarity and user guidance in the vignettes:
• vignette("generate_seasonal_wave"),
• vignette("aedseo"),
• vignette("seasonal_onset")

• vignette("burden_levels") providing a comprehensive walkthrough of the application of the functions provided by the aedseo package with detailed explanations and illustrative examples (#56, #57, #58, #59, #60, #61).

• Improved the autoplot() function which can now visualise dates as days, weeks and months on the x-axis with the time_interval argument (#56).

• Improved the epi_calendar() function to work for a season spanning new year (#34).

• Using predict() on tsd_onset objects now uses the same time-scale as the given object (#61). That is, the time_interval attribute controls if predictions are by "days", "weeks" or "months".

• The aedseo() function now allows for the choice of adding season as an input argument (#34).

• {checkmate} assertions have been added to enhance user feedback with clearer error messages and to ensure functions operate correctly by validating inputs (#33).

• Improved the aedseo() function to work with NA values. The user now defines how many NA values the function should allow in each window (#32).

Minor changes

• Added Sofia Myrup Otero as an author of the R package (#55).

• Added Rasmus Skytte Randløv as a reviewer of the R package (#55).

• The disease_threshold argument now reflects the disease threshold in one time step. If the total number of cases in a window of size k exceeds disease_threshold * k, a seasonal onset alarm can be triggered (#32).

aedseo 0.1.2

Minor changes

• Transferring maintainership of the R package to Lasse Engbo Christiansen.

aedseo 0.1.1

Improvements

• Enhanced clarity and user guidance in the introductory vignette, providing a more comprehensive walkthrough of the application of the 'aeddo' algorithm on time series data with detailed explanations and illustrative examples.

Minor changes

• Updated LICENSE.md to have Statens Serum Institut as a copyright holder.

• Fixed installation guide for the development version in the README.Rmd and README.md

• Added Lasse Engbo Christiansen as an author of the R package.

• Added a new function epi_calendar() that determines the epidemiological season based on a given date, allowing users to easily categorize dates within or outside specified seasons.

• Introduced additional visualizations in the autoplot() method, enhancing the capabilities of the plot() method with new displays of observed cases and growth rates.

aedseo 0.1.0

Features

• Added the aedseo function, which automates the early detection of seasonal epidemic onsets by estimating growth rates for consecutive time intervals and calculating the Sum of Cases (sum_of_cases).

• Introduced autoplot and plot methods for visualizing aedseo and aedseo_tsd objects. These functions allow you to create insightful ggplot2 plots for your data.

• Included the fit_growth_rate function, enabling users to fit growth rate models to time series observations.

• Introduced the predict method for aedseo objects, which allows you to predict observations for future time steps given the growth rates.

• Added the summary method for aedseo objects, providing a comprehensive summary of the results.

• Introduced the tsd function, allowing users to create S3 aedseo_tsd (time-series data) objects from observed data and corresponding dates.

aedseo documentation built on April 12, 2025, 1:35 a.m.