About the model

Some additional details about the model

The trend analyses presented here use Automatic Selection of Models Outlier DEtection for Epidemics (ASMODEE). This new algorithm has not been peer reviewed yet.

ASMODEE in a nutshell

ASMODEE aims to detect recent deviation from the trend followed by the data in time series. Data is first partitioned into ‘recent’ data, using the last ‘k’ observations as supplementary individuals, and older data used to fit the trend. Trend-fitting is done by fitting a series of user-specified models for the time series, with different methods for selecting best fit (see details, and the argument ‘method’). The prediction interval is then calculated for the best model, and every data point (including the training set and supplementary individuals) falling outside are classified as ‘outliers’. The value of ‘k’ can be fixed by the user, or automatically selected to minimise outliers in the training period and maximise and the detection of outliers in the recent period.


R package trendbreaker

ASMODEE is implemented in the R package trendbreaker, hosted by the R Epidemics Consortium.

Try it out

You can install trendbreaker from R by typing:

if (!require(remotes)) {


This package is still under development. Contributions are most welcome. A good place to start would be to look at the current issues.