Adjust from Case Counts by Infection Date to Date of Report — adjust_infection_to

Maps from cases by date of infection to date of report via date of onset.

Usage

adjust_infection_to_report(
  infections,
  delay_defs,
  reporting_model,
  reporting_effect,
  type = "sample",
  truncate_future = TRUE
)

Arguments

infections: <data.table> containing a date variable and a numeric cases variable.
delay_defs: A list of single row data.tables that each defines a delay distribution (model, parameters and maximum delay for each model). See lognorm_dist_def() for an example of the structure.
reporting_model: A function that takes a single numeric vector as an argument and returns a single numeric vector. Can be used to apply stochastic reporting effects. See the examples for details.
reporting_effect: A numeric vector of length 7 that allows the scaling of reported cases by the day on which they report (1 = Monday, 7 = Sunday). By default no scaling occurs.
type: Character string indicating the method to use to transform counts. Supports either "sample" which approximates sampling or "median" would shift by the median of the distribution.
truncate_future: Logical, should cases be truncated if they occur after the first date reported in the data. Defaults to TRUE.

Value

A data.table containing a date variable (date of report) and a cases variable. If return_onset = TRUE there will be a third variable reference which indicates what the date variable refers to.

Examples

# \donttest{
# This function is deprecated and its functionality can now be accessed
# from [simulate_secondary()].
# Here are some examples of how to use [simulate_secondary()] to replace
# adjust_infection_to_report().

# Old (using adjust_infection_to_report()):
# Define example case data
cases <- data.table::copy(example_confirmed)
cases <- cases[, cases := as.integer(confirm)]
# Define a simple reporting delay distribution
delay_def <- lognorm_dist_def(
 mean = 5, mean_sd = 1, sd = 3, sd_sd = 1,
 max_value = 30, samples = 1, to_log = TRUE
)
#> Warning: `lognorm_dist_def()` was deprecated in EpiNow2 1.5.0.
#> ℹ Please use `LogNormal()` instead.
#> ℹ The function will be removed completely in version 2.0.0.
report <- adjust_infection_to_report(
 cases,
 delay_defs = list(delay_def),
 reporting_model = function(n) rpois(length(n), n)
)
#> Warning: `adjust_infection_to_report()` was deprecated in EpiNow2 1.5.0.
#> ℹ Please use `simulate_secondary()` instead.
#> ℹ See equivalent examples using `simulate_secondary()`
#> ℹ in ?adjust_infection_to_report.
#> ℹ This function will be removed completely in version 2.0.0.
#> Warning: The `delay_defs` argument of `adjust_infection_to_report()` should be a
#> dist_spec as of EpiNow2 1.5.0.
#> ℹ Specifying this as a list of data tables is deprecated.
print(report)
#>            date cases
#>          <Date> <int>
#>   1: 2020-02-23     5
#>   2: 2020-02-24    28
#>   3: 2020-02-25    41
#>   4: 2020-02-26    39
#>   5: 2020-02-27    53
#>  ---                 
#> 125: 2020-06-26   313
#> 126: 2020-06-27   315
#> 127: 2020-06-28   256
#> 128: 2020-06-29   272
#> 129: 2020-06-30   211

# New (using simulate_secondary()):
cases <- data.table::copy(example_confirmed)
cases <- cases[, primary := as.integer(confirm)]
uncertain_delay <- LogNormal(
 mean = Normal(5, 1), sd = Normal(3, 1),
 max = 30
)
#> Warning: Uncertain lognormal distribution specified in terms of parameters that are not the "natural" parameters of the distribution (meanlog, sdlog). Converting using a crude and very approximate method that is likely to produce biased results. If possible, it is preferable to specify the distribution directly in terms of the natural parameters.
delay <- fix_dist(uncertain_delay, strategy = "sample")
report <- simulate_secondary(
 cases,
 delays = delay_opts(delay),
 obs = obs_opts(family = "poisson")
)
print(report)
#>       date.date secondary
#>          <Date>     <num>
#>   1: 2020-02-22         0
#>   2: 2020-02-23         2
#>   3: 2020-02-24         9
#>   4: 2020-02-25        31
#>   5: 2020-02-26        58
#>  ---                     
#> 126: 2020-06-26       210
#> 127: 2020-06-27       354
#> 128: 2020-06-28       381
#> 129: 2020-06-29       279
#> 130: 2020-06-30       212
# }