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Create a tsd_growth_warning object to count consecutive significant observations

Source: R/consecutive_growth_warnings.R
consecutive_growth_warnings.Rd

This function calculates the number of consecutive significant ("growth_warning") observations, grouping them accordingly. The result is stored in an S3 object of class tsd_growth_warning.

Uses data from a tsd_onset object (output from seasonal_onset()).

seasonal_onset() has to be run with arguments;

  • season_start

  • season_end

  • only_current_season = FALSE

Usage

consecutive_growth_warnings(onset_output)

Arguments

onset_output

A tsd_onset object returned from seasonal_onset().

Value

An object of class tsd_growth_warning, containing; A tibble of processed observations, the significant_counter column specifies when a sequence of significant observation starts and ends. The first number is how many subsequent observations will be significant.

Examples

# Generate simulated data of seasonal waves
sim_data <- generate_seasonal_data(
  years = 5,
  start_date = as.Date("2022-05-26"),
  trend_rate = 1.002,
  noise_overdispersion = 2,
  relative_epidemic_concentration = 3
)

# Estimate seasonal onset
tsd_onset <- seasonal_onset(
  tsd = sim_data,
  season_start = 21,
  season_end = 20,
  only_current_season = FALSE
)

# Get consecutive significant observations
consecutive_growth_warnings(tsd_onset)
#> # A tibble: 256 × 18
#>    reference_time cases season    population incidence growth_rate
#>    <date>         <dbl> <chr>     <lgl>      <lgl>           <dbl>
#>  1 2022-06-23        95 2022/2023 NA         NA             0.263 
#>  2 2022-06-30       139 2022/2023 NA         NA             0.330 
#>  3 2022-07-07       134 2022/2023 NA         NA             0.230 
#>  4 2022-07-14       139 2022/2023 NA         NA             0.131 
#>  5 2022-07-21       186 2022/2023 NA         NA             0.132 
#>  6 2022-07-28       186 2022/2023 NA         NA             0.0935
#>  7 2022-08-04       230 2022/2023 NA         NA             0.138 
#>  8 2022-08-11       193 2022/2023 NA         NA             0.0816
#>  9 2022-08-18       237 2022/2023 NA         NA             0.0529
#> 10 2022-08-25       204 2022/2023 NA         NA             0.0205
#> # ℹ 246 more rows
#> # ℹ 12 more variables: lower_growth_rate <dbl>, upper_growth_rate <dbl>,
#> #   growth_warning <lgl>, average_observations_window <dbl>,
#> #   average_observations_warning <lgl>, seasonal_onset_alarm <lgl>,
#> #   skipped_window <lgl>, converged <lgl>, counter <dbl>, changeFlag <lgl>,
#> #   groupID <int>, significant_counter <dbl>