Updated version expected in early 2022
This tool harnesses the power of machine learning to make predictions about the status of water points based on the past performance of similar water points in the country.
- Predict which water points are at a higher risk of failure in order to carry out preventative maintenance
- Identify high-risk water points in order to increase monitoring where it is most needed
- Determine which districts have relatively more high-risk water points to more effectively match maintenance budgets with likely need
- Select target country from the drop-down menu
- Select target district(s) from the drop-down menu
- Select whether you want the points on the map colored by the “Last Known Status” (when the last data was collected), or “Today’s Prediction”
- Click Submit
- Access data by clicking “Download Data”
This tool uses available WPDx attributes, such as #water_tech, #water_source, #pay, and others as training data for developing a classification machine learning model. The target variable is #status_id. The models are tuned to optimize the precision (percent of water points that are actually broken) and the recall (percent of all broken water points that are identified as high risk). Predictions are based on adjusting calculating the age of each water point based on #install_year and the current year. A priority for each water point (high/medium/low) is assigned based on the relative number of water points within 1 kilometer and the population within 1 kilometer.
Like all predictions, these predictions are based on probabilities and may not reflect the reality of the status of water points at a given point in time.
New Features Added to WPdx Decision Support Tools
We are excited to share some new features and updates which have been added to the WPdx decision support tools app. Please take a few
Utilizing WPdx in the Amhara Region of Ethiopia
Contributed by Tedla Mulatu, Ethiopia Country Director, Millennium Water Alliance The Millennium Water Alliance (MWA) has been implementing a five-year Water, Sanitation and Hygiene (WASH)
Integrating Governance Factors into WPdx
Governance is recognized as a key aspect of sustainable rural water services. The USAID Governance Research on Rural Water Systems (GROWS) activity was designed to