By Gene Alexander, CTO, Body Surface Translations
Editor's Note: Alesha Black serves as an advisor to BST. BST presented its technology at the Chicago Council Global Food Security Symposium in Spring 2017. To view that video, click here.
A little over a year ago, I presented Body Surface Translation’s (BST) early state technology to use 3D scanning to estimate key data points in order to determine child nutrition status, including stunting. The technology could help field workers capture the circumference of the head, upper-arm, and gather height/length--the key inputs to determine whether a child is considerably lower in height/length for age, an indication of stunting.
A year and a half later, my colleagues and our collaborators were thrilled to see the Centers for Disease Control demonstrating the power and ease of our AutoAnthro scanning technology to capture these measurements at the second annual GoalKeepers event in New York City. The foundation featured a talk by Maria Jeffords about our collaboration in Guatemala and the need for high-quality anthropometric data, along with a demonstration scanning session of a young child by Karim Bougma. The talk highlighted the challenges of quickly and accurately measuring dozens, if not hundreds of children. While traditional anthropometry works and it is not resource intensive to capture this measure, it is labor intensive and can be upsetting for the child and parent as it involves stretching children out to gather height or length. And, because it is done manually, it can leave room for significant variation between those who measure the same child, making it very difficult to evaluate the effectiveness of interventions in a timely manner.
We have recently received renewed support from the Bill & Melinda Gates Foundation to use our scanning technology in partnership with leading global health universities and their local partners to further test and improve the technology. In addition to updating the languages the platform operates in, we’ll be working to reduce the cost, improve the speed of the analytical process, and we’ll be looking for ways to make the technology as rugged and field-ready as possible.
We hope that by making the measurement process easier and making data entry automatic (as well as time and location stamped) that global data about child stunting will dramatically improve in the coming years. This can enable better targeting and progress toward Sustainable Development Goal 2.2, ending all forms of malnutrition, and specifically aligning to the global health goal of reducing stunting by 40% by 2025.
As we continue to progress, we’ll share our progress with you. In the coming months, we’ll be expanding the regions trialing the technology from Guatemala and Kenya to include Bangladesh, Tanzania, and others. Ultimately, better data means better decisions with scarce resources, which is essential with goals as ambitious as the the Sustainable Development Goals.