apply_zero_threshold function

Convert zero case counts to 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")

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.
• threshold: 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.
• obs_column: 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.

Returns

A data.table with the zero threshold applied.