This option specifies a fixed forecast horizon in days. EpiSewer will produce concentration predictions and forecasts of all latent variables such as Rt, infections and load until the end of the forecast horizon.
Usage
horizon_assume(horizon, modeldata = modeldata_init())Arguments
- horizon
The forecast horizon in days. If 0, no forecasts are produced. Note that this functionality is intended for short-term forecasts. Projections over longer horizons can be highly inaccurate.
- modeldata
A
modeldataobject to which the above model specifications should be added. Default is an empty model given bymodeldata_init(). Can also be an already partly specified model returned by otherEpiSewermodeling functions.
Value
A modeldata object containing data and specifications of the model
to be fitted. Can be passed on to other EpiSewer modeling functions to
add further data and model specifications.
The modeldata object also includes information about parameter
initialization (.init), meta data (.metainfo), and checks to be
performed before model fitting (.checks).
Details
Forecasts account for the estimated variation of transmission
dynamics over time and therefore tend to become more uncertain at longer
forecast horizons. However, it is important to keep in mind that depending
on the Rt model used, EpiSewer will project the current transmission
dynamics to continue unchanged (when using R_estimate_rw(),
R_estimate_splines(), R_estimate_piecewise()) or according to a
(dampened) linear trend (when using R_estimate_ets() and
R_estimate_changepoint_splines()). This assumption can be violated by
various factors such as depletion of susceptible individuals, changes in
behavior, or public health interventions.