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Calculate number of fatalities of conflict events from ACLED

Source: R/calc_fatalities_acled.R
fatalities_acled.Rd

The indicator aggregated the number of fatalities within a given asset on a monthly cadence stratified either by event type, sub-event type or disorder type. To learn about the different categorisation ACLED uses to encode events please consult ACLED's codebook.

Usage

calc_fatalities_acled(
  years = 2000,
  stratum = c("event_type", "sub_event_type", "disorder_type"),
  precision_location = 1,
  precision_time = 1
)

Arguments

years

A numeric vector indicating the years for which to summarize fatalities.

stratum

A character vector indicating the stratification to be applied. Should be one of "event_type", "sub_event_type", or "disorder_type". Defaults to "event_type".

precision_location

A numeric indicating precision value for the geolocation up to which events are included. Defaults to 1.

precision_time

A numeric indicating the precision value of the temporal coding up to which events are included. Defaults to 1.

Value

A function that returns an indicator tibble with the type of violence as variable and counts of civilian fatalities as value.

Details

The required resources for this indicator are:

You may apply quality filters based on the precision of the geolocation of events and the temporal precision. By default, these are set to only include events with the highest precision scores.

For geo-precision there are levels 1 to 3 with decreasing accuracy:

  • value 1: the source reporting indicates a particular town, and coordinates are available for that town

  • value 2: the source material indicates that activity took place in a small part of a region, and mentions a general area or if an activity occurs near a town or a city, the event is coded to a town with geo-referenced coordinates to represent that area

  • value 3: a larger region is mentioned, the closest natural location noted in reporting (like “border area,” “forest,” or “sea,” among others) – or a provincial capital is used if no other information at all is available

For temporal precision there are levels 1 to 3 with decreasing precision:

  • value 1: the source material includes an actual date of an event

  • value 2: the source material indicates that an event happened sometime during the week or within a similar period of time

  • value 3: the source material only indicates that an event took place sometime during a month (i.e. in the past two or three weeks, or in January), without reference to the particular date, the month mid-point is chosen

References

Raleigh, C., Kishi, R. & Linke, A. Political instability patterns are obscured by conflict dataset scope conditions, sources, and coding choices. Humanit Soc Sci Commun 10, 74 (2023). doi:10.1057/s41599-023-01559-4

Examples

# \dontrun{
library(sf)
library(mapme.biodiversity)

outdir <- file.path(tempdir(), "mapme-data")
dir.create(outdir, showWarnings = FALSE)

mapme_options(
  outdir = outdir,
  verbose = FALSE,
  chunk_size = 1e8
)

aoi <- system.file("extdata", "burundi.gpkg",
  package = "mapme.biodiversity"
) %>%
  read_sf() %>%
  get_resources(get_acled(years = 2020)) %>%
  calc_indicators(
    calc_fatalities_acled(
      years = 2020,
      precision_location = 1,
      precision_time = 1
    )
  ) %>%
  portfolio_long()
#> Error in get_acled(years = 2020): Please read and agree to ACLED's Terms of Use here:
#> https://acleddata.com/terms-of-use/

aoi
#> Error: object 'aoi' not found
# }