Dual-indicator digital surveillance (DIDS): integrating MUAC and hemoglobin monitoring for pediatric recovery assessment in humanitarian settings

In high-volume humanitarian settings, rapid screening often prioritizes operational speed over diagnostic depth. While Mid-Upper Arm Circumference (MUAC) is universally relied upon as a standalone indicator for pediatric "nutritional recovery" and subcutaneous fat tracking, it fails to capture internal micronutrient saturation and biochemical stability. This study evaluates a digitized surveillance framework designed to bridge field screening with laboratory-grade monitoring during the 2024 humanitarian crisis in Gaza.

A specialized digital workflow was established to screen 45,435 children, with a high-detail cohort of 20 subjects monitored longitudinally. Mobile digital entry tools were utilized by field teams to synchronize anthropometric measurements with point-of-care (POC) Hemoglobin (Hb) testing. Over an 8-week monitoring cycle, both MUAC (cm) and Hb (g/dL) were measured bi-weekly to map concurrent recovery trajectories and automate risk scoring via a digital dashboard.

The integrated digital data revealed a critical diagnostic divergence between physical improvement and internal biochemical health. At baseline, high mortality risk correlated with a severe MUAC of < 11.5 cm and severe anemia (Hb < 8.0 g/dL). By Week 4, partial physical recovery was noted (MUAC 11.5–12.5 cm; Hb 8.5–9.0 g/dL). By Week 8, although 100% of the children achieved formal "nutritional recovery" via normal MUAC standards (> 13.0 cm), 70% remained clinically anemic (Hb < 10.0 g/dL). Without digital laboratory integration, these fragile patients present a diagnostic false negative for overall health.

Relying solely on physical anthropometry in famine-like conditions risks premature discharge and high relapse rates. Transitioning to a dual-indicator digital system allows for automated risk scoring and real-time detection of micronutrient stagnation, shifting humanitarian digital health from mere data collection to active diagnostic correction.