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Monthly Routine Immunization (RI) dummy data

Source: R/aac-data-types.R
dummy_monthly_ri_data.Rd

A data frame containing dummy data for Routine Immunization (RI) across fakeland country's administrative units monthly for the period 2010 to 2020.

Usage

dummy_monthly_ri_data

Format

A data frame with 5280 rows and 9 columns:

prov_code, dist_code

[character] Administrative units identifiers (Province and District unique identifiers here). Matches admin1_code and admin2_code in fakeland. For the user's data, these column names should be the same as those specified in admin argument of config_pviem(). The user does not need to have two columns as here to identify the administrative units. This design is mainly for the possibility to estimate immunity at different administrative levels (e.g., national, provincial, etc.). See config_pviem() for more details about the column mappings and summarize_immunity_samples() for how the administrative unit identifiers are used to compute immunity at different administrative levels.

year

[integer] Year of vaccine administration (e.g., 2010).

month

[integer] Month index (1 to 12). For the user's data, this column name should be the same as that specified in month argument of config_pviem() if the monthly argument is set to TRUE.

OPV0, OPV1, IPV1, IPV2

[numeric] Number of doses administered per month. Column format: <vaccine><dose_num> as per the preprocessed vaccine information table prep_dummy_vs_info dose column values. Not all dose names in the vaccination schedule table need to be present in the data, but those that are present should follow the requirements defined in prep_dummy_vs_info for dose column values.

live_births

[numeric] Number of live births in the administrative unit per month. For the user's data, this column name should be the same as that specified in birth argument of config_pviem().

Source

Generated data for package examples

Important notes

  • Monthly data provides finer temporal resolution for seasonality analysis

  • Zero doses should be explicitly recorded as 0 (not missing)

  • Missing values (NA) are allowed only for dose columns

See also

dummy_yearly_ri_data, dummy_birth_seasonality, prep_dummy_vs_info, compute_immunity_sample(), validate_ri_data(), config_pviem()

Examples

# \donttest{
  # View the data
  head(dummy_monthly_ri_data)
#>   prov_code dist_code year month OPV0 OPV1 IPV1 IPV2 live_births
#> 1      PR_A       A01 2010     1 3881   NA 3653 3416        3932
#> 2      PR_A       A01 2010     2 2948 2532 4532   NA        4218
#> 3      PR_A       A01 2010     3 4751 3358 3359   NA        4281
#> 4      PR_A       A01 2010     4 4573 4052 3269   NA        4083
#> 5      PR_A       A01 2010     5 2675 1713   NA 2939        3300
#> 6      PR_A       A01 2010     6 3765 2894 2778   NA        3012

  # Validate the data
  ## Set admin and monthly = TRUE to tell the package to expect monthly data and the
  ## corresponding admin unit columns in the data for validation
  with_config(list(admin = c('prov_code', 'dist_code'), monthly = TRUE), {
    validate_ri_data(dummy_monthly_ri_data, prep_dummy_vs_info)
  })

  # Check dose columns present
  grep("^(OPV|IPV)", names(dummy_monthly_ri_data), value = TRUE)
#> [1] "OPV0" "OPV1" "IPV1" "IPV2"
# }