How to Use USAID’s Local Data Mapping Tool for Insights into Water and Sanitation Access
Employees of the Sohag Water and Wastewater Company in Egypt undertake training exercises to improve their GIS mapping skills for identifying leaks and prevent non-revenue water losses. Photo credit: Nour Mamadouh/WADA
Summary
USAID’s Demographic and Health Surveys (DHS) Program’s Local Data Mapping Tool allows users to explore and compare Admin 1 estimates, modeled Admin 2 estimates, and modeled estimates at a resolution of 5x5 km of key water, sanitation, and hygiene (WASH) indicators.
On World Water Day, USAID’s Demographic Health Surveys Program released a WASH Atlas, as part of its Local Data Mapping Tool, that can help to identify populations without access to safe water and basic sanitation at local levels.
Why the Local Data Mapping Tool?
DHS Program surveys generally provide estimates for indicators at the national and first subnational administrative levels, known as Admin 1. These areas are the largest administrative divisions within a country, such as provinces, states, regions, or counties. But, because decisions about health policies and programs are increasingly made at more local levels, the DHS Program also provides data for smaller areas known as Admin 2, or the second subnational administrative level composed of divisions such as districts and departments.
The need for more localized data for decision making is equally true for water and sanitation access and interventions. While tools such as USAID’s WASH Needs Index provide data on water and sanitation access at the country and Admin 1 level, few resources exist that provide data at the Admin 2 and even more local levels. Considering that water and sanitation access can vary dramatically within countries and that relevant policies, institutions, and regulatory bodies are often situated at local levels, this is a critical information gap.
To address this need for data at Admin 2, the DHS Program applies geospatial modeling to predict indicator values at non-surveyed locations. Using DHS Program survey data and geospatial covariates such as elevation, precipitation, and population density, geospatial modeling generates indicator estimates at a resolution of 5x5 kilometers (km), and then uses a population-weighted approach to aggregate these estimates to the Admin 2 level.
How can I use the Local Data Mapping Tool?
Users can explore and compare Admin 1 estimates, modeled Admin 2 estimates, and modeled estimates at a resolution of 5x5 km. Watch the videos and read the steps below to learn more!
Where to find the tool and how to get started:
- Navigate to the Local Data Mapping Tool.
- Select a survey (country of interest) from the dropdown menu.
- Select an indicator from the dropdown menu:
- Population without basic water service
- Population using open defecation
- Population without basic sanitation service
- Population without improved water source on the premises
Diving into the data:
- Use the radio buttons to view results at the Admin 1, Admin 2, or 5x5 km levels.
- Select a “Level” to focus on a single Admin 1 area (default view is the entire country).
- Toggle between visualizing estimates, population, and uncertainty using the second row of radio buttons (see data notes below for more information).
- While viewing Admin 2 data, click on any area on the map for a pop-up of the estimate, population, and uncertainty values.
- You can view Admin 2 data in a table or bar chart using the icon toggles below “Select a Survey.”
→ - Data can be downloaded as tables, shapefiles, and raster images.
This is great! Which countries have this data available?
Currently, there are WASH maps available under the Local Data Mapping Tool for nine Global Water Strategy High Priority Countries: Ethiopia, Haiti, Liberia, Madagascar, Mali, Nigeria, Rwanda, Uganda, and Zambia. Over the next year, USAID plans to release 11 more. Watch this space for more!
Read more about geospatial modeling for locally available data in the DHS Program’s full report: Interpolation of DHS Survey Data at Subnational Administrative Level 2.
DATA NOTES
Indicator estimate: Describes the proportion of the population in that area without WASH access. An area may have a high indicator estimate but if it is sparsely populated, targeted interventions there will not reach many individuals.
Population: Represents the number of people in that area who lack WASH access and is calculated by multiplying the total population of a spatial unit by that area’s indicator estimate.
Uncertainty: There is a 95 percent chance that the indicator’s true value for a population is between the upper and lower bounds of the uncertainty interval. Larger intervals indicate higher uncertainty for a given estimate. Uncertainty depends on many factors, including survey cluster locations, survey sample sizes, goodness of fit to the geospatial covariates, and the spatial scale of predictions. The 5x5 km data can have very high uncertainty and should be interpreted accordingly.