washmalawi: WASH Household Level Survey Data 2018 - 2023

This dataset contains results from the Sustainable Development Goals (SDG) Household-Level Survey for WASH conducted by BASEFlow Malawi between 2018 and 2023, using the mWater platform. The data provides detailed, household-level insights into access to water, sanitation, hygiene, and environmental conditions across different communities in Malawi.

Each row represents a completed household survey and includes:

• Survey metadata: submission date, consent, GPS location

• Water point information: type, method of collection, region, location accuracy, altitude

• Water quality indicators: microbial tests, confidence levels, associated health risks

• Sanitation: toilet type, waste removal and treatment methods

• Hygiene: handwashing facility availability, presence of water and soap

• Other socio-environmental factors: including responses to structured and open-ended questions

🔍 Use Cases

This dataset is suitable for a range of applications, including:

1. WASH Program Monitoring & Evaluation Evaluate household access to clean water and sanitation services over time and across regions.

2. Public Health Research Identify environmental and behavioral factors contributing to hygiene-related illnesses.

3. Geospatial Analysis Map infrastructure such as boreholes and sanitation facilities to analyze regional disparities.

4. Evidence-Based Planning & Advocacy Support national and local policymakers in achieving SDG 6: Clean Water and Sanitation for All.

5. Education and Capacity Building Use in training programs and university courses on data-driven development, environmental health, or digital health systems.

6. Data Science and ML Train models to predict risk patterns or infrastructure needs based on survey indicators.

Installation

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

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

## 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.

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
washmalawi	Download CSV	Download XLSX

Data

The package provides access to Sustainable Development Goals (SDG) Household-Level Survey data for Malawi between 2018 and 2023

library(washmalawi)

washmalawi

The dataset washmalawi contains 23112 observations and 27 variables

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

date_submitted	latitude	longitude	water_point_identification_method	traditional_authority	district	water_source_type	water_source_location	water_collection_time_mins	time_not_known	water_insufficiency_30days	water_insufficiency_30days_not_known	water_quality_tested	bacteriological_test_done_at_location	parameters_tested_methods	chemical_quality_tested	arsenic_tested_water	fluoride_tested_water	toilet_facility_type	toilet_facility_shared	waste_removed	waste_treated	waste_disposal	handwash_available	handwashing_water_presence	handwashing_soap_presence	handwashing_supplies_available
13/11/2018	-15.98578	35.34706	NA	STA Mpunga	Chiradzulu	Borehole or tubewell	Elsewhere	60	NA	No, always sufficient	NA	No	NA	NA	No	NA	NA	Pit latrine without slab/ Open pit	No	No - there is no removal of waste	Yes	Waste pit is filled in or covered over	Not observed - no handwashing place in dwelling / yard / plot	NA	NA	NA
10/06/2019	-16.14591	35.34064	NA	TA Mazengera	Lilongwe	Borehole or tubewell	Elsewhere	90	NA	No, always sufficient	NA	No	NA	NA	No	NA	NA	Pit latrine without slab/ Open pit	Yes	No - there is no removal of waste	Yes	Waste pit is filled in or covered over	Observed - Fixed facility or mobile object in dwelling / yard / plot	Water is not available	Soap or detergent not present	NA
22/11/2018	-15.90557	35.33917	NA	TA Nkalo	Chiradzulu	Borehole or tubewell	Elsewhere	0	TRUE	Yes, at least once	NA	No	NA	NA	No	NA	NA	Pit latrine without slab/ Open pit	No	No - there is no removal of waste	Yes	Waste pit is filled in or covered over	Not observed - no handwashing place in dwelling / yard / plot	NA	NA	NA

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

variable_name	variable_type	description
date_submitted	character	The date on which the household survey form was submitted.
latitude	numeric	The geographic latitude coordinate of the household location.
longitude	numeric	The geographic longitude coordinate of the household location.
water_point_identification_method	character	Method used to identify the water point
traditional_authority	character	The name of the Traditional Authority where the household is located.
district	character	The name of the district where the household is located.
water_source_type	character	Type of water source used by the household
water_source_location	character	Location of the water source relative to the household
water_collection_time_mins	numeric	Estimated round-trip time in minutes to collect water, including waiting time.
time_not_known	logical	TRUE if respondent does not know or cannot estimate the water collection time.
water_insufficiency_30days	character	Whether the household experienced water insufficiency in the past 30 days
water_quality_tested	character	Whether the water quality at the source has been tested.
bacteriological_test_done_at_location	character	Indicates whether a bacteriological test was performed on-site at the household or source.
parameters_tested_methods	character	List or description of water quality parameters tested and methods used.
chemical_quality_tested	character	Indicates whether chemical tests were performed on the water.
arsenic_tested_water	character	Indicates whether the water was tested for arsenic contamination.
fluoride_tested_water	character	Indicates whether the water was tested for fluoride levels.
toilet_facility_type	character	The type of toilet facility used by the household
toilet_facility_shared	character	Indicates whether the toilet facility is shared with other households.
waste_removed	character	Indicates whether household waste is regularly removed
waste_treated	character	Whether the waste is treated
waste_disposal	character	Method used for waste disposal
handwash_available	character	Whether the household has a designated place for handwashing.
handwashing_water_presence	character	Whether water was present at the handwashing location at the time of visit.
handwashing_soap_presence	character	Whether soap or detergent was present at the handwashing place at the time of visit.
handwashing_supplies_available	character	Overall availability of both soap and water for handwashing.

Example

# Plot a bar chart for the type of toilets in use
library(washmalawi)
library(dplyr)
library(ggplot2)
library(maps)
# Filter out records with missing or empty 'toilet_type'
# Then count the number of occurrences for each toilet type
toilet_data <- washmalawi %>%
  filter(!is.na(toilet_facility_type) & toilet_facility_type != "NA") %>%
  count(toilet_facility_type, sort = TRUE)

# Create a horizontal bar chart showing the number of households
# using each type of toilet
ggplot(toilet_data, aes(x = reorder(toilet_facility_type, n), y = n)) +
  geom_bar(stat = "identity", fill = "#2C7BB6") +  # Use blue bars for counts
  coord_flip() +  # Flip axes to make the chart horizontal
  labs(
    title = "Distribution of Toilet Types in Surveyed Households",  # Chart title
    x = "Toilet Type",  # X-axis label showing toilet types)
    y = "Number of Households"  # Y-axis label (number of entries)
  ) +
  theme_minimal(base_size = 13)

# Plots maps for the water collection points 
# Filter usable water point locations
water_map_data <- washmalawi %>%
  filter(!is.na(latitude) & !is.na(longitude))  # Ensure geo-points are valid

# Get Malawi map outline
malawi_map <- map_data("world", region = "Malawi")

# Plot the water point locations
ggplot() +
  geom_polygon(data = malawi_map, aes(x = long, y = lat, group = group),
               fill = "gray90", color = "gray70") +
  geom_point(data = water_map_data,
             aes(x = longitude, y = latitude, color = water_source_type),
             size = 2, alpha = 0.7) +
  coord_fixed(1.3) +
  labs(
    title = "Geo-Referenced Water Point Locations in Malawi",
    x = "Longitude", y = "Latitude", color = "Water Source Type"
  ) +
  theme_minimal(base_size = 13) +
  theme(legend.position = "bottom")

License

Data are available as CC-BY.

Citation

Please cite this package using:

citation("washmalawi")
#> To cite washmalawi in publications use:
#> 
#>   Mhango, E., Robertson, D., Mandala, C., et al. (2025). washmalawi:
#>   WASH Household Level Survey Data 2018 - 2023. R package version
#>   1.0.1. https://doi.org/10.5281/zenodo.15799918
#> 
#> Ein BibTeX-Eintrag für LaTeX-Benutzer ist
#> 
#>   @Manual{,
#>     title = {washmalawi: WASH Household Level Survey Data 2018 - 2023},
#>     author = {Emmanuel Mhango and Donald Robertson and Chifundo Mandala and M Nzengo and Muthi Nhlema and M. Banda and Khumbo Zinyongo and Christian Nedi and Leman Ngwena and M Kazembe and Yankho Mthindi and E. Mofolo and Jeffrey Bauleni and Khallen Malliot and Thandi Mtemangombe and Tamandani Tembo and Samuel Mlenga and Dufter Joshua and Andrew Mthunzi and Martha Kafuwa and Takondwa Tembo and Peter Singogo and Goodwin Mkandawire and Monica Msiska and Lemekezani Chilora and Tendai Jambo and William Kanyinji and Chikondi Kanyinji and Madalitso Kamamkhudza and Sylvia Siliya and Edward K Gadi and Buli Echika and Sunganani Monjeza and Derick Macheke and Fatsani Chinawa and Jonathan Sunthika and Precious Phiri and Bright Mphero and Rodney Kananji},
#>     year = {2025},
#>     note = {R package version 1.0.1},
#>     doi = {10.5281/zenodo.15799918},
#>     url = {https://github.com/openwashdata/washmalawi},
#>   }