Create an Emission Risk Factors (ERF) Row

Constructs and validates a single row of emission risk factor data for a given country, species, and disease context. This function serves as a robust helper to generate new entries in the emission risk factors dataset, ensuring compatibility with subsequent analytical workflows in the riskintroanalysis package.

The function performs input validation and data cleaning (e.g., coercing numeric fields to integer) and assigns appropriate data types. It ensures the output meets the schema expected by the emission risk scoring system, which uses this data to calculate risk scores across four weighted domains:

Epidemiological status (e.g., last_outbreak_end_date)
Surveillance measures (e.g., disease_notification, targeted_surveillance, general_surveillance, screening)
Control measures (e.g., slaughter, zoning, official_vaccination)
Animal commerce (e.g., commerce_illegal, commerce_legal)

The resulting row includes domain-specific fields that will be used by scoring algorithms such as build_emission_risk_table() to derive intermediate and final emission risk values.

Usage

erf_row(
  iso3,
  country,
  disease,
  animal_category,
  species,
  disease_notification = 0L,
  targeted_surveillance = 0L,
  general_surveillance = 0L,
  screening = 0L,
  precautions_at_the_borders = 0L,
  slaughter = 0L,
  selective_killing_and_disposal = 0L,
  zoning = 0L,
  official_vaccination = 0L,
  last_outbreak_end_date = as.Date("01/01/1900"),
  commerce_illegal = 0L,
  commerce_legal = 0L,
  data_source = paste0("User ", Sys.info()[["user"]], " - ", Sys.Date())
)

Arguments

iso3: ISO3 country code (e.g., "FRA"), it should be a valid ISO3 code with a match in column iso3 returned by country_reference() or a string starting with 'JOKER'.
country: Country name (e.g., "France"), the name is free text, but is expected to match the country name name_en or name_fr in the dataset returned by country_reference().
disease: Disease name (e.g., "ASF"), it should be a valid disease code or name. For now there is no check for the disease name: it is expected to match the disease name in the dataset of WAHIS diseases but as the data are not covering all deceases, it is not checked so that users can add their own diseases.
animal_category: Animal category, one of "wild" or "domestic".
species: Species name (e.g., "pig"), it is a free text. It's expected to match the species name in the dataset returned by WAHIS species dataset but as the data are not covering all species, it is not checked so that users can add their own species.
disease_notification: Integer (0 or 1). All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
targeted_surveillance: Integer (0 or 1). Is targeted surveillance applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
general_surveillance: Integer (0 or 1). Is general surveillance applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
screening: Integer (0 or 1). Are screening measures in place? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
precautions_at_the_borders: Integer (0 or 1). Are precautions taken at the borders? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
slaughter: Integer (0 or 1). Are slaughter processes in place? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
selective_killing_and_disposal: Integer (0 or 1). Are selective killing and disposal procedures in place? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
zoning: Integer (0 or 1). Are zoning strategies applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
official_vaccination: Integer (0 or 1). Are official vaccination programs applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
last_outbreak_end_date: Date. The end date of the last outbreak.
commerce_illegal: Integer (0, 1). Indicators of whether illegal commerce are being conducted.
commerce_legal: Integer (0, 1). Indicators of whether legal commerce are being conducted.
data_source: Character. A description of the data source, defaulting to the user name and current date. This is free text.

Value

A tibble::tibble() object with cleaned, validated, and structured emission risk factor data. The output is containing the input parameters stored in a table whose columns are:

iso3: ISO3 country code (e.g., "FRA"), it should be a valid ISO3 code with a match in column iso3 returned by country_reference() or a string starting with 'JOKER'.
country: Country name (e.g., "France"), the name is free text, but is expected to match the country name name_en or name_fr in the dataset returned by country_reference().
disease: Disease name (e.g., "ASF"), it should be a valid disease code or name. For now there is no check for the disease name: it is expected to match the disease name in the dataset of WAHIS diseases but as the data are not covering all deceases, it is not checked so that users can add their own diseases.
animal_category: Animal category, one of "wild" or "domestic".
species: Species name (e.g., "pig"), it is a free text. It's expected to match the species name in the dataset returned by WAHIS species dataset but as the data are not covering all species, it is not checked so that users can add their own species.
disease_notification: Integer (0 or 1). All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
targeted_surveillance: Integer (0 or 1). Is targeted surveillance applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
general_surveillance: Integer (0 or 1). Is general surveillance applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
screening: Integer (0 or 1). Are screening measures in place? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
precautions_at_the_borders: Integer (0 or 1). Are precautions taken at the borders? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
slaughter: Integer (0 or 1). Are slaughter processes in place? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
selective_killing_and_disposal: Integer (0 or 1). Are selective killing and disposal procedures in place? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
zoning: Integer (0 or 1). Are zoning strategies applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
official_vaccination: Integer (0 or 1). Are official vaccination programs applied? All are either 1 or 0, 0 means 'measure inplace' and 1 means 'no measure inplace', i.e. 1 = there is a risk, 0 = there is no risk.
last_outbreak_end_date: Date. The end date of the last outbreak.
commerce_illegal: Integer (0, 1). Indicators of whether illegal commerce are being conducted.
commerce_legal: Integer (0, 1). Indicators of whether legal commerce are being conducted.
data_source: Character. A description of the data source, defaulting to the user name and current date. This is free text.

Examples

erf_row(
  iso3 = "FRA",
  country = "France",
  disease = "ASF",
  animal_category = "livestock",
  species = "pig",
  disease_notification = 1,
  targeted_surveillance = 1,
  general_surveillance = 0,
  screening = 1,
  precautions_at_the_borders = 1,
  slaughter = 1,
  selective_killing_and_disposal = 0,
  zoning = 1,
  official_vaccination = 0,
  last_outbreak_end_date = "2020-05-01",
  commerce_illegal = 1,
  commerce_legal = 1
)
#> ✔ All data in "emission_risk_factors" valided.
#> # A tibble: 1 × 18
#>   iso3  country disease animal_category species disease_notification
#>   <chr> <chr>   <chr>   <chr>           <chr>                  <int>
#> 1 FRA   France  ASF     livestock       pig                        1
#> # ℹ 12 more variables: targeted_surveillance <int>, general_surveillance <int>,
#> #   screening <int>, precautions_at_the_borders <int>, slaughter <int>,
#> #   selective_killing_and_disposal <int>, zoning <int>,
#> #   official_vaccination <int>, last_outbreak_end_date <date>,
#> #   commerce_illegal <int>, commerce_legal <int>, data_source <chr>

Usage

Arguments

Value

See also

Examples