Household Water Point Satisfaction Survey – Zomba & Mangochi District

This dataset captures household-level information on water access, reliability, and user satisfaction across selected communities in Zomba and Mangochi Districts in Malawi. The data was collected on September 20, 2021, using mWater, a mobile-based data collection platform. Enumerators visited households to gather geo-referenced responses through structured digital surveys, ensuring high-quality and spatially traceable data.

The survey focused on understanding the condition and accessibility of household water sources, user satisfaction with water services, seasonal availability, and the economic aspects of water usage. It also gathered insights into household well-being and demographics relevant to water access and decision-making.

Potential Use Cases

This dataset is valuable to a wide range of stakeholders, including:

1. Local Government and District Water Offices – for planning water infrastructure repairs, expansions, and equitable service delivery.

2. NGOs and Development Partners (e.g., WaterAid, UNICEF, WASH-focused NGOs) – for identifying priority areas, targeting interventions, and measuring impact.

3. Policy Makers and Researchers – for analyzing rural water access trends, community resilience, and household-level satisfaction indicators.

4. WASH Engineers and Planners – for designing technically informed and community-responsive water systems.

5. Academic Institutions – for research and student projects focusing on water governance, rural development, and environmental health.

Installation

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

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

## 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)
library(fmsb)

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

1. Click Download CSV. A window opens that displays the CSV in your browser.
2. Right-click anywhere inside the window and select “Save Page As…”.
3. Save the file in a folder of your choice.

dataset	CSV	XLSX
waterconsumersurvey	Download CSV	Download XLSX

Data

The package provides access to Household Water Access and Satisfaction Survey collected in 2021 in Zomba and Mangochi districts in Malawi.

library(waterconsumersurvey)

waterconsumersurvey

The dataset waterconsumersurvey contains 423 observations and 41 variables

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

submitted_on	latitude	longitude	gps_method	district	traditional_authority	group_village_headman	village	well_being_analysis	household_id	respondent_gender	attended_school	highest_education_qualification	marital_status	religion	main_income_source	monthly_family_income	household_size	main_water_source	waterpoint_functional_status	nonfunctional_reason	waterpoint_current_issues	waterpoint_current_problem	waterpoint_current_problem_other	water_collection_time_minutes	seasonal_water_shortage	shortage_months	daily_water_use_buckets	has_water_tariff	no_tariff_reason	no_tariff_reason_other	waterpoint_breakdown_response	willing_to_pay_for_improvement	current_tariff_kwacha	current_tariff_unknown	max_tariff_willing_to_pay	satisfaction_service_level	satisfaction_maintenance_fund	satisfaction_sanitation_hygiene	satisfaction_theft_protection	satisfaction_water_quality
9/20/2021	-15.47244	35.29495	GPS	Zomba	Chikowi	Matache	Kagaso	Stepping-up	70	Female	Yes	Primary	Single	Muslim	Income from piecework or ganyu	Below K100,000	3	Unprotected dug well	NA	NA	NA	NA	NA	NA	NA	NA	NA	No	Other	It's unprotected dug well	Contribute to maintain	Yes	NA	NA	NA	Very satisfied	Very satisfied	Satisfied	Very satisfied	Very satisfied
9/20/2021	-15.46819	35.29386	GPS	Zomba	Chikowi	Matache	Kagaso	Hanging-in	62	Female	Yes	Primary	Widowed	Christian	Farming	Below K100,000	5	Borehole or tubewell	Partially functional but in need of repair	NA	Yes	Worn out parts	NA	4	Yes	October, November	5	Yes	NA	NA	NA	NA	200	NA	500	Very satisfied	Very satisfied	Very satisfied	Very satisfied	Very satisfied
9/20/2021	-15.46737	35.29396	GPS	Zomba	Chikowi	Matache	Kagaso	Stepping-up	54	Male	Yes	Secondary	Married	Christian	Income from piecework or ganyu	Below K100,000	3	Borehole or tubewell	Functional	NA	No	NA	NA	45	Yes	October	3	Yes	NA	NA	NA	NA	200	NA	NA	Very satisfied	Very satisfied	Somewhat satisfied	Satisfied	Very satisfied

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

variable_name	variable_type	description
submitted_on	character	Date the survey response was submitted.
latitude	numeric	GPS latitude of the household location.
longitude	numeric	GPS longitude of the household location.
gps_method	character	Method used to collect the GPS coordinates (e.g., phone, GPS device).
district	character	Name of the district where the household is located.
traditional_authority	character	Name of the traditional authority overseeing the area.
group_village_headman	character	Name of the group village headman in the household’s locality.
village	character	Name of the specific village where the household is located.
well_being_analysis	character	Categorization of household well being (e.g., poor, moderate, better off).
household_id	numeric	Unique identifier for the household in the survey.
respondent_gender	character	Gender of the person responding to the survey.
attended_school	character	Indicates whether the respondent has ever attended school.
highest_education_qualification	character	Highest level of education completed by the respondent.
marital_status	character	Current marital status of the respondent.
religion	character	Religious affiliation of the respondent.
main_income_source	character	Primary source of household income (e.g., farming, business, salary).
monthly_family_income	character	Approximate total family income per month (in local currency).
household_size	numeric	Total number of people living in the household.
main_water_source	character	Primary source of water for the household (e.g., borehole, tap, river).
waterpoint_functional_status	character	Functional status of the households main water point.
nonfunctional_reason	character	Reason why the water point is non functional, if applicable.
waterpoint_current_issues	character	Whether there are ongoing problems with the water point.
waterpoint_current_problem	character	Type of problem currently affecting the water point (e.g., broken pump, contamination).
waterpoint_current_problem_other	character	Specification of any other problem not captured by predefined choices.
water_collection_time_minutes	numeric	Round trip time (in minutes) to collect water from the source, including waiting time.
seasonal_water_shortage	character	Indicates if the water source becomes unavailable at certain times of the year.
shortage_months	character	Specific months when water shortages are experienced.
daily_water_use_buckets	numeric	Average number of 20 litre buckets of water used daily by the household.
has_water_tariff	character	Whether a tariff or user fee is charged for water use.
no_tariff_reason	character	Reason for not charging a tariff, if applicable.
no_tariff_reason_other	character	Additional explanation for why there is no tariff, if not listed in predefined options.
waterpoint_breakdown_response	character	Usual response or process followed when the water point breaks down.
willing_to_pay_for_improvement	character	Indicates if the household is willing to pay for improved water services.
current_tariff_kwacha	numeric	Amount of the current tariff or user fee in Malawi Kwacha.
current_tariff_unknown	logical	Indicates if the respondent does not know the current tariff.
max_tariff_willing_to_pay	numeric	Maximum amount the household is willing to pay monthly for improved water supply.
satisfaction_service_level	character	Level of satisfaction with the overall water service received.
satisfaction_maintenance_fund	character	Satisfaction with how the maintenance fund is managed by the Water Point Committee.
satisfaction_sanitation_hygiene	character	Satisfaction with sanitation and hygiene practices around the water point.
satisfaction_theft_protection	character	Satisfaction with how the water point is protected from theft and vandalism.
satisfaction_water_quality	character	Satisfaction with the quality of the water (e.g., taste, color, smell).

Example

library(waterconsumersurvey)
library(dplyr)
library(ggplot2)
library(tidyr)
library(ggplot2)
library(dplyr)

# Visualization 1: Bar Chart of Waterpoint Functional Status by District
# Filter out rows where waterpoint functional status is NA,
# then group by district and functional status and count number of waterpoints
status_district <- waterconsumersurvey %>%
  filter(!is.na(waterpoint_functional_status)) %>%   # Exclude NA functional statuses
  group_by(district, waterpoint_functional_status) %>%
  summarise(count = n()) %>%                         # Count occurrences in each group
  ungroup()

# Create a stacked bar chart showing waterpoint status distribution by district
ggplot(status_district, aes(x = district, y = count, fill = waterpoint_functional_status)) +
  geom_bar(stat = "identity") +                      # Use counts directly for bar heights
  labs(
    title = "Waterpoint Functional Status by District",
    x = "District",
    y = "Number of Waterpoints",
    fill = "Functional Status"
  ) +
  theme_minimal() +
  # Rotate x-axis labels for better readability if district names are long
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

# Vizualisation 2: Water Shortage Seasonality Line Chart

# Step 1: Filter households reporting seasonal water shortage
shortage_data <- waterconsumersurvey %>%
  filter(seasonal_water_shortage == "Yes" & !is.na(shortage_months)) %>%
  select(household_id, shortage_months)

# Step 2: Split shortage_months into separate rows per household
shortage_expanded <- shortage_data %>%
  mutate(shortage_months = strsplit(as.character(shortage_months), ",")) %>%
  unnest(shortage_months) %>%
  mutate(shortage_months = trimws(shortage_months))  # Remove leading/trailing spaces

# Step 3: Count households by month
monthly_shortage_counts <- shortage_expanded %>%
  group_by(shortage_months) %>%
  summarise(households = n()) %>%
  ungroup()

# Optional: Order months chronologically (adjust if months in dataset differ)
month_levels <- c("January", "February", "March", "April", "May", "June",
                  "July", "August", "September", "October", "November", "December")
monthly_shortage_counts$shortage_months <- factor(monthly_shortage_counts$shortage_months,
                                                  levels = month_levels,
                                                  ordered = TRUE)

# Step 4: Plot line chart
ggplot(monthly_shortage_counts, aes(x = shortage_months, y = households, group = 1)) +
  geom_line(color = "steelblue", size = 1.2) +
  geom_point(color = "steelblue", size = 3) +
  labs(
    title = "Seasonal Water Shortage: Number of Households by Month",
    x = "Month",
    y = "Number of Households Reporting Shortage"
  ) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("waterconsumersurvey")
#> To cite package 'waterconsumersurvey' in publications use:
#> 
#>   Mhango, E. et al. (2025). waterconsumersurvey: Household Water Point
#>   Satisfaction Survey Data from Malawi. R package version 0.0.0.9000.
#>   https://github.com/openwashdata/waterconsumersurvey
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {waterconsumersurvey: Household Water Point Satisfaction Survey Data from Malawi},
#>     author = {Emmanuel Mhango and Feston Bwanyula and Rhodrick D. Sagawa and Fatsani Chinawa and Baleke Banda and Alex Mchotsa and Paul Kumpukwe and Derick Macheke and George Mangochi Martin and Khallen Malliot and Christopher Mwafulirwa and Tellia Billiat and Verson Chilombo and Doreen Chalira and Catherine Chapotera},
#>     year = {2025},
#>     note = {R package version 0.0.0.9000},
#>     url = {https://github.com/openwashdata/waterconsumersurvey},
#>   }