The goal of watercostaccra is to provide users with documentation on two surveys on household water costs, coping mechanisms as well as water point estimates conducted in November 2023 in Accra, Ghana. The data sets are associated with the following project report completed by Elizabeth Vicario for the “data science for openwashdata” course offered by openwashdata.org.
Installation
You can install the development version of watercostaccra from GitHub with:
# install.packages("devtools")
devtools::install_github("openwashdata/watercostaccra")Alternatively, you can download the individual data sets as a CSV or XLSX file from the table below.
| dataset | CSV | XLSX |
|---|---|---|
| households | Download CSV | Download XLSX |
| waterpoints | Download CSV | Download XLSX |
Data
The package provides access to household water costs, coping mechanisms as well as water point estimates.
The households data set contains data about a household survey on water costs and coping strategies in Accra. It has 116 observations and 89 variables.
| variable_name | variable_type | description |
|---|---|---|
| community | factor |
the communities surveyed, options including 1 kg: Korle Gonno and 2 abuja: Abuja
|
| housing_type | factor |
housing type, options includin 1 block_unit: unit in a row of apartments made of cement blocks, 2 wood_unit: unit in a row of apartments made of wood, 3 house, 4 compound_house: single-story L- or C-shaped house with a multiple units around a shared courtyard, 5 multistory_apt: multi-story apartment building, 6 wood_shack: wooden shack, 7 no_structure, and 8 other
|
| respondent_relationship_to_hh | factor |
respondent’s relationship to the household head (respondent identified), options including 1 self, 2 child, 3 spouse, and 4 other_relative
|
| gender | factor |
gender (self-identified) of respondent, options including 1 female and 2 male
|
| tenure | factor |
tenure status, options including 1 rented: renter, 2 owned: homeowner, or 3 no_payment: living without payment)
|
| years_in_community | integer | number of years respondent has lived in community |
| adult_count | double | number of adults in household including respondent. Household is described as those “eating from the same pot” |
| child_count | double | number of children under 18 in household. Household is described as those “eating from the same pot” |
| rooms_in_hh | double | number of rooms used for sleeping. Household is described as those “eating from the same pot” |
| business_ownership | factor |
household or respondent owns a business, options including 1 respondent-owned and 2 household-owned
|
| business_location | factor |
location type of the business, options including 1 home_based, 2 outside_home: fixed location outside home, or 3 mobile: mobile location.
|
| business_category | factor |
type of business, options including 1 food, 2 shop, 3 salon, 4 vented_water, 5 tailoring, and 6 other_services.
|
| business_water_use | logical | respondent’s business uses water beyond typical needs of household (true or false) |
| business_water_source | factor | primary source of water for business use (packaged water, piped to home, piped to neighbor’s home, piped to compound, commercial or public tap, borehole, dug well, spring water, delivered water) |
| primary_dw_source | factor | primary source of drinking water (packaged water, piped to home, piped to neighbor’s home, piped to compound, commercial or public tap, borehole, dug well, spring water, delivered water) |
| dw_reason_x | logical | columns about respondent reasons for using drinking water source on convenience, affordability, availability, temperature, cleanliness, taste, habit or cultural norm, trustworthiness, health, other. (true or false) |
| package_type_preference | factor |
respondent typically purchases individual, options including 1individual: sachets/packets/bottles, 2 bag: multipacks of these, or 3 both
|
| package_size_reason_x | logical | columns about reasons for purchasing preferred package type on storage space in home, cost effectiveness, temperature at time of purchase, availability of money, convenience, size needed for respondent or household, avoiding wasting water by purchasing only when needed. (true or false) |
| dw_treatment | factor |
treatment methods of water before drinking, options including 1no_treatment, 2 boil, 3boil;settle, 4 filter, and 5settle
|
| primary_water_source | factor |
primary water source for non-drinking water, options including 1packaged water, 2piped_to_home, 3piped to neighbor’s home, 4piped to compound, 5commercial or public tap, 6borehole, 7dug well, 8spring water, and 9 delivered water)
|
| primary_source_reason_x | logical | columns about reasons for using primary source of non-drinking water on proximity to home, convenience, affordability, availability, cleanliness, other. (true or false) |
| other_non_dw_source_use | logical | respondent uses at least one source besides primary non-drinking water source (true or false) |
| other_non_dw_sources_x | logical | columns about additional water source(s) for non-drinking water on packaged water, piped to home, piped to neighbor’s home, piped to compound, commercial or public tap, borehole, dug well, spring water, delivered water. (true or false) |
| secondary_source_reason_x | logical | columns about reason for using secondary source of non-drinking water (primary source is not available, primary source is not clean, primary source is crowded, availability of shower stalls, convenient location) |
| tap_payment_mode | factor |
respondent’s mechanism for paying for piped water (all respondents use piped water as a primary or secondary source). Options include 1 pay_to_fetch: paying to fetch, 2 shares_bill: sharing or paying the whole bill, or 3 both (at different taps).
|
| daily_hh_water_cost_for_pay_to_fetch | double | daily estimated cost of drinking water for respondent’s household |
| daily_hh_water_cost_phhm_for_pay_to_fetch | double | daily estimated cost of drinking water for respondent’s household per household member |
| past_struggle_to_find_water | logical | respondent has struggled to find water before (defined as extreme difficulty in accessing water) (true or false) |
| time_of_last_struggle_to_find_water | factor |
respondent’s last time of struggle to find water, options including 1 last_3_days, 2 last_7_days, 3 last_30_days, 4 last_year, and 5 over_year_ago.
|
| weekdays_struggle_to_find_water | double | days in a week the respondent typically struggles to find or pay for water |
| past_struggle_primary_reason | factor |
primary reason for past struggles to find water, options including 1 availability: availability, 2 cost, and 3 distance: distance to nearest source.
|
| tap_closure_knowledge_x | logical | columns about respondent’s knowledge about tap closures (usually known, sometimes known, expected due to patterns in closures, not known, or no answer). (true or false) |
| coping_mechanism_x | logical | columns about strategies for coping with water shortage (spending more on the same amount of water, purchasing extra water to store at home, using another source, using packaged water for cooking, skipping cooking, using packaged water for bathing, skipping bathing, closing business due to water shortage, skipping laundry). (true or false) |
| water_storage_drinking_water | logical | respondent typically stores drinking water at home (true or false) |
| water_storage_non_drinking_water | logical | respondent typically stores non-drinking water at home (true or false) |
| water_storage_none | logical | respondent typically does not store water at home (true or false) |
| storage_containers_x | logical | columns about if respondent typically stores non-drinking water, types of storage containers (plastic jugs also called jerry cans or Kufuor gallons, uncovered or covered barrels, other covered or uncovered containers) |
| estimated_non_dw_storage_capacity | double | estimated capacity of storage for non-drinking water (liters) |
| estimated_stored_non_dw | double | estimated actual storage of non-drinking water (liters) |
The waterpoints data set contains data about a water point survey conducted in Accra as well. It has 49 observations and 30 variables. For an overview of the variable names, see the following table. observations and 89 variables.
| variable_name | variable_type | description |
|---|---|---|
| id | integer | identification number |
| community | factor |
the communities surveyed, options including 1 kg: Korle Gonno and 2 abuja: Abuja
|
| type | factor |
water point type,options including 1 piped_water, 2 borehole, 3 public_bath, and 4 natural_spring.
|
| available_services | factor | services available at water point, options including (bathing, public sale of water, toilet, or comination of these) |
| location | factor |
location of the water point, options including 1 within_a_compound or 2 on_the_street: outside compound adjacent to street.
|
| year_established | integer | year established |
| owner | factor |
owner, options including 1 household_head, 2 household_member, 3 community_member: community member outside household, and 4 multiple_community_members: multiple community members outside household
|
| constructor | factor |
type of constructor, options including 1 government or 2 community_member.
|
| managers | factor | type of typical manager(s) of water point, options including household head or member(s), employee(s), self managed by customers, or combination of these) |
| estimated_storage_capacity_liters | double | estimated storage capacity in liters |
| average_visits_per_customer | double | average number of daily visits per customer |
| respondent_would_use_to_prepare_rice | logical | respondent would use this water to prepare rice, based on its quality (true or false) |
| perception_of_quality | factor |
respondent’s perception of water quality, options including 1 acceptable, 2 high, and 3 low.
|
| tap_closure_days_per_week | double | typical number of tap closures per week |
| price_25_liter_jug | double | current price of 25-liter jug of water (cedis) |
| price_20_liter_bucket | double | current price of 20-liter bucket of water (cedis) |
| price_30_liter_basin | double | current price of 30-liter basin of water (cedis) |
| avg_price_per_liter_cedis | double | average price per liter, calculated by averaging price per liter of known prices (cedis) |
| tap_closure_changes | factor | typical dynamics of water point management during closure (increasing prices, water point likely to close due to low storage, bathing customers have less water than when taps are flowing) |
| flexible_pricing | logical | manager adjusts price depending on amount of water needed or familiarity or need of customer (true or false) |
| price_increase | logical | price of any volume of water has increased in the last year (true or false) |
| CBT_sample_source | factor |
source of sample for compartment bag test (CBT) supplied by Aquagenx (https://www.aquagenx.com/cbt-ectc/), options including 1 indirect_from_tap_(traveled_through_hose), 2 other_storage_(traveled_through_hose_or_poured_through_container), 3 storage_tank, and 4 tap.
|
| coli_mpn | double | results of E. Coli most probable number (MPN) test per 100 mL sample |
| coli_mpn_ci | double | results of E. Coli most probable number (MPN) test per 100 mL sample - upper 95% confidence interval (CI) |
| coli_mpn_health_risk | factor |
results of E. Coli most probable number (MPN) test per 100 mL sample - descriptive health risk, options including options including 1safe, 2possibly_safe, 3 possibly_unsafe and 4unsafe.
|
| tc_mpn | double | results of Total Coliforms (TC) most probable number (MPN) test per 100 mL sample |
| tc_mpn_ci | double | results of Total Coliforms (TC) most probable number (MPN) test per 100 mL sample - upper 95% confidence interval (CI) |
| tc_mpn_health_risk | factor |
results of Total Coliforms (TC) most probable number (MPN) test per 100 mL sample - descriptive health risk, options including 1safe, 2possibly_safe, 3 possibly_unsafe and 4unsafe.
|
Example
Here is an example illustrating health risks associated with the water samples collected in Accra.
library(watercostaccra)
library(ggplot2)
library(dplyr)
library(tidyr)
long_data <- waterpoints |>
pivot_longer(cols = c(coli_mpn_health_risk, tc_mpn_health_risk),
names_to = "risk_type",
values_to = "health_risk")
# Count occurrences of each health_risk category within each community and risk_type
count_data <- long_data |>
group_by(community, risk_type, health_risk) |>
summarise(count = n(), .groups = 'drop')
facet_labels <- c(
coli_mpn_health_risk = "Coliform MPN health risk",
tc_mpn_health_risk = "Total Coliform MPN health risk"
)
# Create the bar plot
ggplot(count_data, aes(x = community, y = count, fill = health_risk)) +
geom_bar(stat = "identity", position = "dodge") +
facet_wrap(~ risk_type, labeller = labeller(risk_type = facet_labels)) +
labs(title = "Health risk assessment by community",
x = "community",
y = "count",
fill = "health risk") +
scale_fill_brewer(palette = "Dark2") +
theme_minimal()
License
Data are available as CC-BY.
Citation
Please cite this package using:
citation("watercostaccra")
#> To cite package 'watercostaccra' in publications use:
#>
#> Vicario E, Götschmann M, Davidson B, Amankwaa E, Zhong M (2024).
#> "watercostaccra: Household water costs and coping strategies data
#> from metropolitan Accra." doi:10.5281/zenodo.13981225
#> <https://doi.org/10.5281/zenodo.13981225>,
#> <https://github.com/openwashdata/watercostaccra>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Misc{vicario_etall:2024,
#> title = {watercostaccra: Household water costs and coping strategies data from metropolitan Accra},
#> author = {Elizabeth Vicario and Margaux Götschmann and Betty Avanu Davidson and Ebenezer F. Amankwaa and Mian Zhong},
#> year = {2024},
#> doi = {10.5281/zenodo.13981225},
#> url = {https://github.com/openwashdata/watercostaccra},
#> abstract = {A household survey on water costs and coping strategies as well as a water point survey were conducted in two low-income communities in metropolitan Accra. These are Korle Gonno, a larger, well-planned coastal area with over 35 household water vendors, and Abuja, a small, densely packed, extralegal settlement with 15 water vendor and bathhouse businesses.},
#> keywords = {accra,ghana,household-surveys,open-data,openwashdata,r,water-cost},
#> version = {0.0.0.9000},
#> }