Timely assessments of child acute malnutrition are essential for effective treatment and prevention of undernutrition. We developed a simple smartphone app, D2A (“Data to Analysis”), to enable regular self-collection of Family MUAC (Mid-upper Arm Circumference) and key household drivers of wasting by mothers and caregivers. Based on a seven-month pilot study with 180 households, we explore the acceptance, accuracy, and cost of app-based self-collection of Family MUAC with and without the assistance of Community Health Volunteers (CHVs) relative to paper-based nutrition screenings. Results indicate: (i) similar classification accuracy of wasted children; (ii) no difference in participant dropout rates and a 15% higher completion rate for CHV-assisted reporting by households (compared to no assistance); (iii) lower cost for app-based collection amortized over seven months. Preliminary evidence suggests that self-reporting by households via smartphone apps constitutes a feasible alternative to less frequent, more costly paper-based nutrition screening, the latter more susceptible to interruption in remote, hard-to-access areas.
Bhavnani et al. (Fri,) studied this question.
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