EpiNow2 (version 1.7.1)

create_shifted_cases: Create Delay Shifted Cases

Description

This functions creates a data frame of reported cases that has been smoothed using a centred partial rolling average (with a period set by smoothing_window) and shifted back in time by some delay. It is used by estimate_infections() to generate the mean shifted prior on which the back calculation method (see backcalc_opts()) is based.

Usage

create_shifted_cases(data, shift, smoothing_window, horizon)

Value

A <data.frame> for shifted reported cases

Arguments

data

A <data.frame> of disease reports (confirm) by date (date). confirm must be numeric and date must be in date format. Optionally this can also have a logical accumulate column which indicates whether data should be added to the next data point. This is useful when modelling e.g. weekly incidence data. See also the fill_missing() function which helps add the accumulate column with the desired properties when dealing with non-daily data. If any accumulation is done this happens after truncation as specified by the truncation argument.

shift

Numeric, mean delay shift to apply.

smoothing_window

Numeric, the rolling average smoothing window to apply. Must be odd in order to be defined as a centred average.

horizon

Deprecated; use forecast instead to specify the predictive horizon

Details

The function first shifts all the data back in time by shift days (thus discarding the first shift days of data) and then applies a centred rolling mean of length smoothing_window to the shifted data except for the final period. The final period (the forecast horizon plus half the smoothing window) is instead replaced by a log-linear model fit (with 1 added to the data for fitting to avoid zeroes and later subtracted again), projected to the end of the forecast horizon. The initial part of the data (corresponding to the length of the smoothing window) is then removed, and any non-integer resulting values rounded up.

Examples

if (FALSE) {
shift <- 7
horizon <- 7
smoothing_window <- 14
## add NAs for horizon
cases <- add_horizon(example_confirmed[1:30], horizon)
## add zeroes initially
cases <- data.table::rbindlist(list(
  data.table::data.table(
    date = seq(
      min(cases$date) - 10,
      min(cases$date) - 1,
      by = "days"
    ),
    confirm = 0, breakpoint = 0
  ),
  cases
))
create_shifted_cases(cases, shift, smoothing_window, horizon)
}