Body Surface Translations, Inc.

  • Institution Country: U.S.A.
  • Implementation Country: South Sudan
  • Sector: Health
  • Funding Stage: Proof of Concept

AutoAnthro: 3D Scanning for Improved Malnutrition Assessment in Conflict Areas

THE CHALLENGE

In South Sudan, many children living in conflict-affected areas suffer from stunting and malnutrition. To determine malnutrition, the standard for decades has been manual measurement, despite this method’s persistent challenges, including the need to transport cumbersome equipment, staff fatigue during the measurement process, poor digital record capture, and difficulty ensuring the cooperation of young children. Collectively, these barriers undermine the accuracy and timeliness of data collection, making it difficult for humanitarian actors to adequately map the nutritional status of vulnerable child populations.

THE SOLUTION

To develop a more effective method of measuring malnutrition, Body Surface Translations (BST) developed AutoAnthro, a 3D scanning system that captures child anthropometry to enable easier, faster, more accurate digital measurements to improve individual and population-level outcomes in cases of malnutrition. By capturing quick scans of children and developing a 3D model from which a variety of data can be extracted, AutoAnthro can measure length, height, mid-upper-arm circumference (MUAC), and head circumference for children ages 0-5 years. Under CHIC funding, BST’s innovation was tested on 539 children in South Sudan in collaboration with the International Medical Corps. Unfortunately, due to insufficient reliability testing, pandemic-related travel restrictions—which prevented the BST team from travelling to South Sudan to conduct in-country, first-hand training on the use of the technology and methods for evaluating its effectiveness—, and major software failures, the technology did not perform as expected and consequently failed to accurately detect acute malnutrition. This nonetheless offered important learnings to the BST team which has now informed their shift towards the development of alternative technologies to enhance methods of anthropometry as needed to improve the targeting of nutritional interventions towards malnourished children.

 

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