Add columns describing the fractions of the population in each age group that attend school/work (average FTE)

Add fractions of the population in each age group that attend school/work (average FTE) to compute the probability that both participant and contact attend school/work. Requires columns age_to and age_from. Note that it will operate on any column starting with age. Adds columns: school_probability, work_probability, school_year_probability, and school_weighted_pop_fraction. The columns school_probability and work_probability represent the probability a person of the other age goes to the same work/school. school_year_probability represents the probability that a person of the other age would be in the same school year. school_weighted_pop_fraction represents the weighted combination of contact population age distribution & school year probability, so that if the contact is in the same school year, the weight is 1, and otherwise it is the population age fraction. This can be used as an offset, so that population age distribution can be used outside the classroom, but does not affect classroom contacts (which due to cohorting and regularised class sizes are unlikely to depend on the population age distribution).

Usage

add_school_work_participation(
  contact_data,
  school_demographics = NULL,
  work_demographics = NULL
)

Arguments

contact_data: contact data containing columns: age_to, age_from, and pop_age_to (from add_population_age_to())
school_demographics: (optional) defaults to census average proportion at school. You can provide a dataset with columns, "age" (numeric), and "school_fraction" (0-1), if you would like to specify these details. See abs_avg_school for the default values. If you would like to use the original school demographics used in conmat, these are provided in the dataset, conmat_original_school_demographics.
work_demographics: (optional) defaults to census average proportion employed. You can provide a dataset with columns, "age" (numeric), and "work_fraction", if you would like to specify these details. See abs_avg_work for the default values. If you would like to use the original work demographics used in conmat, these are provided in the dataset, conmat_original_work_demographics.

Value

dataset with 9 extra columns: school_fraction_age_from, work_fraction_age_from, school_fraction_age_to, work_fraction_age_to, school_probability, work_probability, school_year_probability, and school_weighted_pop_fraction.

Note

To use previous approach input the arguments school_demographics and work_demographics with conmat_original_school_demographics and conmat_original_work_demographics, respectively.

Examples

age_min <- 10
age_max <- 15
all_ages <- age_min:age_max
library(tidyr)
example_df <- expand_grid(
  age_from = all_ages,
  age_to = all_ages,
)

example_df %>%
  add_population_age_to() %>%
  add_school_work_participation()
#> # A tibble: 36 × 12
#>    age_from age_to pop_age_to intergenerational school_fraction_age_from
#>       <dbl>  <dbl>      <dbl>             <int>                    <dbl>
#>  1       10     10      0.161                 0                    0.922
#>  2       10     11      0.163                 1                    0.922
#>  3       10     12      0.165                 2                    0.922
#>  4       10     13      0.168                 3                    0.922
#>  5       10     14      0.170                 4                    0.922
#>  6       10     15      0.173                 5                    0.922
#>  7       11     10      0.161                 1                    0.931
#>  8       11     11      0.163                 0                    0.931
#>  9       11     12      0.165                 1                    0.931
#> 10       11     13      0.168                 2                    0.931
#> # ℹ 26 more rows
#> # ℹ 7 more variables: school_fraction_age_to <dbl>, school_probability <dbl>,
#> #   school_year_probability <dbl>, school_weighted_pop_fraction <dbl>,
#> #   work_fraction_age_from <dbl>, work_fraction_age_to <dbl>,
#> #   work_probability <dbl>

example_df %>%
  add_population_age_to() %>%
  add_school_work_participation(
    school_demographics = conmat_original_school_demographics,
    work_demographics = conmat_original_work_demographics
  )
#> # A tibble: 36 × 12
#>    age_from age_to pop_age_to intergenerational school_fraction_age_from
#>       <int>  <int>      <dbl>             <int>                    <dbl>
#>  1       10     10      0.161                 0                        1
#>  2       10     11      0.163                 1                        1
#>  3       10     12      0.165                 2                        1
#>  4       10     13      0.168                 3                        1
#>  5       10     14      0.170                 4                        1
#>  6       10     15      0.173                 5                        1
#>  7       11     10      0.161                 1                        1
#>  8       11     11      0.163                 0                        1
#>  9       11     12      0.165                 1                        1
#> 10       11     13      0.168                 2                        1
#> # ℹ 26 more rows
#> # ℹ 7 more variables: school_fraction_age_to <dbl>, school_probability <dbl>,
#> #   school_year_probability <dbl>, school_weighted_pop_fraction <dbl>,
#> #   work_fraction_age_from <dbl>, work_fraction_age_to <dbl>,
#> #   work_probability <dbl>