Electrochemical Lateral Flow Assay with Linked Analytics for Surveillance of Cassava Brown Streak Disease in East Africa

Abstract

Cassava brown streak disease (CBSD) severely threatens food security in East Africa and the livelihoods of hundreds of millions globally. Effective control requires large-scale surveillance in resource-limited settings, which is currently lacking. We present ELLA (Electrochemical Lateral Flow Assay with Linked Analytics), a portable, battery-free, low-cost digital diagnostic platform integrating lateral flow assays with near-field communication and electrochemical readouts for cloud-based data storage and analytics. Validated through extensive field trials in East Africa and smaller studies in Brazil, ELLA achieved 89% agreement with RT-qPCR and 95% with ELISA, often surpassing ELISA sensitivity at a material cost below US$1 per test. Leveraging ELLA’s molecular results, we trained a deep-learning model (DeepELLA) for rapid, image-based diagnosis of CBSD, enabling scalable surveillance of this and potentially emerging plant pathogens. By combining electrochemical sensing, digital connectivity, and AI-driven analytics, ELLA offers a powerful tool to strengthen plant disease monitoring and food security. Its modular design also allows adaptation to other chemical and biological targets, creating opportunities for novel datasets and new insights into plant and environmental health.

Taliya Weinstein

Research Engineer and Data Scientist

Pursuing inventive, interdisciplinary solutions for impactful change while advancing the engineering field.