unhcrwash

The goal of unhcrwash is to make available data on WASH indicators in refugee camps and settlements.

Installation

You can install the development version of unhcrwash from GitHub with:

# install.packages("devtools")
devtools::install_github("openwashdata/unhcrwash")

## Run the following code in console if you don't have the packages
## install.packages(c("dplyr", "knitr", "readr", "stringr", "gt", "kableExtra"))
library(dplyr)
library(knitr)
library(readr)
library(stringr)
library(gt)
library(kableExtra)

Alternatively, you can download the individual datasets as a CSV or XLSX file from the table below.

dataset	CSV	XLSX
unhcrwash	Download CSV	Download XLSX

Data

The package provides access to WASH indicators in refugee camps and settlements

library(unhcrwash)

unhcrwash

The dataset unhcrwash contains data about WASH indicators in refugee camps and settlements. It has 6425 observations and 27 variables

unhcrwash |> 
  head(3) |> 
  gt::gt() |>
  gt::as_raw_html()

form_id	start_date	end_date	location_id	location_name	country	post_emergency	persons_per_handpump	persons_per_tap	liters_per_person_per_day	non_chlorinated_0_cfu	chlorinated_safe_water_quality	households_with_toilet	persons_per_toilet	persons_per_shower	persons_per_hygiene_promoter	refugee_pop	reporting_monthly	liters_per_person_household	potable_water_storage_10l	protected_water_sources	menstrual_hygiene_satisfaction	household_toilet	defecate_in_toilet	access_to_soap	solid_waste_disposal_access	reporting_annual
54418187	2024-01-01	2024-12-31	518	Dagahaley	Kenya	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	18.2	99	98	64	42	83	87	96	2024-05-17
54418188	2024-01-01	2024-12-31	519	Hagadera	Kenya	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	13.4	98	97	72	39	91	75	99	2024-05-17
54418189	2024-01-01	2024-12-31	520	Ifo	Kenya	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	15.0	99	87	63	43	89	69	95	2024-05-17

For an overview of the variable names, see the following table.

variable_name	variable_type	description
form_id	double	Unique Identifier for the form
date_start	double	Start Date for the data collection
date_end	double	End date for the data collection
location_id	double	Unique Identifier for the location of the refugee camp
location_name	character	Name of the location of the refugee camp
country_name	character	Country in which the refugee camp is located
emergency_post_emergency	character	If emergency is ongoing or not (Emergency or Post Emergency)
number_of_persons_per_usable_handpump_well_spring	double	No. of persons per usable handpump well spring
number_of_persons_per_usable_water_tap	double	Number of persons per unit of usable tap water source
average_number_liters_of_potable_water_available_per_person_per_day	double	Average number of litres of potable water available per person per day
percent_water_quality_tests_at_non_chlorinated_water_collection_locations_with_0_cfu_100ml	double	Percentage of water quality tests conducted at non-chlorinated water collection points that returned results with 0 colony-forming units (CFU) per 100 milliliters
percent_of_water_quality_tests_at_chlorinated_collection_locations_with_frc_in_the_range_0_2_2mg_l_and_turbidity_5ntu5	double	Percentage of water quality tests at chlorinated collection points where the Free Residual Chlorine (FRC) levels were within the range of 0.2 to 2 mg per L, and turbidity was less than or equal to 5 NTU (Nephelometric Turbidity Units)
percent_households_with_household_toilet_latrine_monthly	double	Percentage of households that have access to a household toilet or latrine, evaluated on a monthly basis
number_of_persons_per_toilet_latrine	double	Number of persons per toilet latrine
number_of_persons_per_bath_shelter_shower	double	Number of persons per bath shower
number_of_persons_per_hygiene_promoter	double	Number of persons per hygiene promoter
refugee_population	double	Refugee Population
reporting_period_monthly_indicator	double	Monthly Reporting Period
average_number_l_p_d_of_potable_water_collected_at_household_level	double	Average water (litres) collected per household per day
percent_households_with_at_least_10_liters_person_potable_water_storage_capacity	double	Percentage of households with at least 10 litres of water storage capacity
percent_households_collecting_drinking_water_from_protected_treated_sources	double	Percentage of households collecting water from sheltered and treated sources
percent_of_women_of_reproductive_age_who_are_satisfied_with_menstrual_hygiene_management_materials_and_facilities	double	Percentage of women of reproductive age satisfied with facilities for management of menstrual hygiene and waste
percent_households_with_household_toilet_latrine	double	Percentage of households with a latrine
percent_households_reporting_defecating_in_a_toilet	double	Percentage of households defecating in a toilet
percent_households_with_access_to_soap	double	Percentage of households with access to soap
percent_households_with_access_to_solid_waste_disposal_facility	double	Percentage of households with access to a waste disposal facility
reporting_period_annual_indicator	double	Annual Reporting Period

Example

library(unhcrwash)

# Average Water Availability by Country 
unhcrwash |> dplyr::group_by(country) |> 
  dplyr::summarise(avg_water_avail = mean(liters_per_person_per_day, na.rm = TRUE)) |> 
  dplyr::arrange(desc(avg_water_avail)) |> 
  head(5) |> 
  gt::gt() |> 
  gt::as_raw_html()

country	avg_water_avail
Iraq	99.06584
Democratic Republic of the Congo	43.85081
Jordan	40.07407
Ghana	38.13077
Bangladesh	35.86667

library(ggplot2)
# Toilet availability
unhcrwash |> 
  dplyr::mutate(year = lubridate::year(as.Date(start_date))) |>  # Extract year as whole number
  dplyr::filter(!is.na(year) & !is.na(persons_per_toilet)) |>    # Remove missing values
  dplyr::group_by(year) |> 
  dplyr::summarise(avg_persons_per_toilet = mean(persons_per_toilet, na.rm = TRUE)) |> 
  ggplot2::ggplot(aes(x = year, y = avg_persons_per_toilet)) +
  ggplot2::geom_line() +
  ggplot2::labs(title = "Average Persons per Toilet in Refugee Camps",
                x = "Year",
                y = "Average persons per toilet") +
  ggplot2::theme_minimal()

# Countries with highest refugee populations
unhcrwash |> 
  dplyr::group_by(country) |> 
  dplyr::summarise(total_population = sum(refugee_pop, na.rm = TRUE)) |> 
  dplyr::arrange(desc(total_population)) |> 
  head(5) |> 
  gt::gt() |> 
  gt::as_raw_html()

country	total_population
Uganda	33730168
Ethiopia	30630168
Kenya	18034151
Chad	15437507
Sudan	12848789

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("unhcrwash")
#> To cite package 'unhcrwash' in publications use:
#> 
#>   Dubey Y (2024). "unhcrwash: WASH Data From Refugee Camps and
#>   Settlements (UNHCR)." doi:10.5281/zenodo.14185117
#>   <https://doi.org/10.5281/zenodo.14185117>,
#>   <https://github.com/openwashdata/unhcrwash>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Misc{unhcrwashwash:2024,
#>     title = {unhcrwash: WASH Data From Refugee Camps and Settlements (UNHCR)},
#>     year = {2024},
#>     author = {Yash Dubey},
#>     doi = {10.5281/zenodo.14185117},
#>     url = {https://github.com/openwashdata/unhcrwash},
#>     abstract = {This is a dataset on WASH indicators in refugee camps and settlements. The data is collected from the UNHCR Information Management System (IRIS) and is available on the UNHCR WASH dashboard. This dataset includes data from 191 sites and 29 countries.},
#>     version = {0.1.0},
#>   }