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Fit all-of-polymod model and extrapolate to a given population an age breaks

extrapolate_polymod.Rd

Uses estimate_setting_contacts() to fit a contact model on the data from polymod and later extrapolate on to a desired population. Note that this function is parallelisable with future, and will be impacted by any future plans provided.

Usage

extrapolate_polymod(
  population,
  age_breaks = c(seq(0, 75, by = 5), Inf),
  per_capita_household_size = NULL
)

Arguments

population

a conmat_population object, specifying the age and population characteristics. Or a data frame with lower.age.limit and population columns. See get_polymod_population() for an example of this data.

age_breaks

vector depicting age values. Default value is c(seq(0, 75, by = 5), Inf)

per_capita_household_size

Optional (defaults to NULL). When set, it adjusts the household contact matrix by some per capita household size. To set it, provide a single number, the per capita household size. More information is provided below in Details. See get_abs_per_capita_household_size() function for a helper for Australian data with a workflow on how to get this number.

Value

Returns setting-specific and combined contact matrices for the desired ages.

Details

Also note that since this model uses the already fit polymod_setting_models data, which has been fit using symmetrical model terms, if you want to fit a model with asymmetric model terms, you will need to go through the full process of building new models. You can find this detail in last section of the vignette "example pipeline".

Examples

if (FALSE) {
polymod_population <- get_polymod_population()
synthetic_settings_5y_polymod <- extrapolate_polymod(
  population = polymod_population
)
synthetic_settings_5y_polymod
synthetic_settings_5y_fairfield <- extrapolate_polymod(
  population = abs_age_lga("Fairfield (C)")
)
synthetic_settings_5y_fairfield
}