Get a default and minimum and maximum date for the intervention time point for the glm algorithms with pandemic correction. This is based on the data provided and the settings for the delays.

Get a default and minimum and maximum date for the intervention time point for the glm algorithms with pandemic correction. This is based on the data provided and the settings for the delays.

get_valid_dates_intervention_start(
  data,
  date_var = "date_report",
  number_of_weeks = 6,
  time_trend = TRUE,
  min_timepoints_baseline = 12,
  min_timepoints_trend = 12,
  past_weeks_not_included = 4
)

Arguments

data

data.frame, preprocessed linelist of surveillance data obtained using preprocess_data()

date_var

a character specifying the date variable name used for the aggregation. Default is "date_report".

number_of_weeks

integer, specifying number of weeks to generate signals for

time_trend

boolean, default TRUE, when TRUE a timetrend is fitted in the glm describing the expected number of cases

min_timepoints_baseline

integer, default 12, specifying the number of weeks at least needed for fitting a new baseline after the intervention.

min_timepoints_trend

integer, default 12, specifying the number of weeks at least needed for fitting a new timetrend after the intervention.

past_weeks_not_included

An integer specifying the number of past weeks to exclude from the fitting process. This can be useful for excluding recent data with outbreaks or data that may not be fully reported. Default is `4`.

Value

list with three dates or NULL values. valid_start_date is the first date which is valid to chose as intervention_date, valid_end_date is the last date which is valid to chose to chose as intervention_date, default_intervention is a default date which is used for the intervention_date and usually set to "2020-03-15" but checked whether this is possible with the data we have

Examples

if (FALSE) {
input_prepro <- input_example %>% preprocess_data()
get_valid_dates_intervention_start(input_prepro) # this just gives the default date "2020-03-15" back
get_valid_dates_intervention_start(input_prepro %>% dplyr::filter(date_report >= "2020-04-01")) # this gives the valid_start date back as default date
get_valid_dates_intervention_start(input_prepro %>% dplyr::filter(date_report >= "2020-04-01") %>% dplyr::filter(date_report <= "2020-05-01")) # this gives NULL as the timeperiod of date provided is too short to do a intervention
}