Existing measurement of malnutrition remains extremely unreliable because of human error.
- In emergency situations, such as the current crisis in South Sudan, Aid organizations often have difficulties to understand the magnitude of malnutrition, which is essential for a timely response.
- Nutrition Front-line workers, such as the Anganwadi worker in India, frequently fail to detect acute malnutrition due to wrong measurement or non-measurement of children (while faking the charts). This leads to prolonged malnutrition and death of children.
- Also, rural mothers themselves are often not aware about the malnutrition of their children and take measures too late.
- Even national data on malnutrition is frequently disputed due to mistrust in survey methodologies and data accuracy.
SMART surveys, which are best practice for localized surveys, require highly-experienced staff, and with a sample size of 400 children costs about 30.000€ and take about one month.
We provide a game-changer in the measurement and data processing of malnourished children. It is a fool proof solution based on a mobile app using augmented reality.
- The mobile app scans children under 5 in 3D to determine height and weight and therefore establishes the wasting rate. This is the main indicator for detecting moderate acute malnutrition (MAM) and severe acute malnutrition (SAM). SAM children are considered at risk of death.
- The mobile app is simple, fast, and provides accuracy and accountability in data collection (as the scans are saved), while further data options could be added per the survey design.
The app can save the lives of thousands of children every year.
It helps aid agencies to adequately respond to emergencies, and it helps front-line workers in emergencies but also in chronic relief situations to detect malnourished children and help them better.
Further, this solution could be integrated in survey methodologies, MIS of health service provider, or even mobile apps for the mass market.
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