Preprocessed vaccine efficacy dummy data

A data frame containing the preprocessed vaccine efficacy data (converted to n-doses efficacy estimates) using preprocess_efficacy() and the vaccination schedule dummy_vs_info.

Usage

prep_dummy_efficacy

Format

A data frame with 14 rows and 7 columns:

serotype

[character] As in efficacy_default.

vaccine

[character] Vaccine name (e.g., 'OPV') extracted from vaccine_type. Must match the same column in dummy_vs_info but can cover more vaccines than in the vaccination schedule.

vaccine_type

[character] As in efficacy_default.

dose

[character] Dose identifier: <vaccine><dose_num> (e.g., 'OPV1'). Must conform to the rules specified for the same column of prep_dummy_vs_info but may cover more doses than those specified in the vaccination schedule.

efficacy

[numeric] n-doses efficacy value between 0 and 1.

from, to

[integer] First/last year this vaccine type was used. May be NA meaning 'from/to anytime'.

Source

Preprocessed efficacy_default using preprocess_efficacy() and dummy_vs_info

Details

Preprocessing Steps

The preprocess_efficacy() function:

1. Converts per-dose efficacy to n-doses format

2. Broadcasts efficacy values across serotypes when combined serotype notation (e.g., PV13) is used.

3. Validates dose consecutiveness

4. Ensures efficacy values are between 0 and 1

Important Note

This dataset uses the dummy vaccination schedule (dummy_vs_info) for preprocessing. For real analyses, users should preprocess efficacy_default with their own vaccination schedule using preprocess_efficacy().

See also

efficacy_default for raw efficacy data, preprocess_efficacy() for preprocessing function, prep_dummy_vs_info for corresponding schedule, validate_efficacy() for validation function

Examples

# \donttest{
# View efficacy
head(prep_dummy_efficacy)
#>   serotype vaccine vaccine_type dose efficacy from   to
#> 1      PV1     OPV         tOPV OPV0   0.3900   NA 2015
#> 2      PV1     OPV         tOPV OPV1   0.6279   NA 2015
#> 3      PV2     OPV         tOPV OPV0   0.3900   NA 2015
#> 4      PV2     OPV         tOPV OPV1   0.6279   NA 2015
#> 5      PV1     OPV         bOPV OPV0   0.6300 2016   NA
#> 6      PV1     OPV         bOPV OPV1   0.8631 2016   NA

# Validate preprocessed efficacy estimates data
validate_efficacy(prep_dummy_efficacy, dummy_vs_info, preprocessed = TRUE)

# Check efficacy ranges
summary(prep_dummy_efficacy$efficacy)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>  0.3500  0.4575  0.6290  0.6728  0.8573  0.9900 
# }