NA (missing) if the 7-day average is above a
threshold.This function aims to detect spurious zeroes by comparing the 7-day average
of the case counts to a threshold. If the 7-day average is above the
threshold, the zero case count is replaced with NA.
apply_zero_threshold(data, threshold = Inf, obs_column = "confirm")A data.table with the zero threshold applied.
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.
Numeric, defaults to Inf. Indicates if detected zero
cases are meaningful by using a threshold number of cases based on the
7-day average. If the average is above this threshold at the time of a
zero observation count then the zero is replaced with a missing (NA)
count and thus ignored in the likelihood.
Character (default: "confirm"). If given, only the column specified here will be used for checking missingness. This is useful if using a data set that has multiple columns of hwich one of them corresponds to observations that are to be processed here.