Project description

Work Package 1 aims to deliver a field-ready, affordable digital diagnostic platform for soil-transmitted helminths and related infections in low-resource settings. It brings together (i) ruggedised, 3-D-printed opto-mechanical hardware and a smartphone-linked control system, (ii) human-centred design to tailor usability and acceptability for frontline health workers and communities in Uganda and Kenya, (iii) lightweight deep-learning algorithms that run on-device for rapid egg detection, and (iv) iterative cost-and-manufacture optimisation. The package culminates in statistically powered clinical and field studies, benchmarking diagnostic accuracy, speed, and usability against gold-standard methods, and generating performance, economic, and environmental evidence needed for large-scale deployment and integration into health systems.

Work Package 2 aims to create and validate a community-level, connected diagnostic system that turns latrine, pit, and wastewater samples into actionable public-health intelligence for helminth and schistosomiasis control. It combines (i) field-deployable DNA-based assays and battery-powered heaters that deliver rapid, contamination-free LAMP results on lateral-flow strips; (ii) laboratory and metagenomic benchmarking against qPCR and sequencing data to refine targets, explore sentinel organisms, and ensure analytical sensitivity and robustness; (iii) seamless ingestion of test and sequencing outputs into DHIS2 dashboards, where geo-linked analytics reveal transmission patterns and trigger alerts; and (iv) iterative field campaigns in Uganda and Kenya that correlate environmental signals with human prevalence, evaluate the platform’s predictive power for guiding mass-drug-administration timing, and demonstrate its value as an early-warning and decision-support tool for health authorities.

Work Package 3 turns the diagnostic outputs of WP1–2 into actionable intelligence by building an end-to-end digital data infrastructure. It delivers a secure Android app that tags every test with tamper-evident QR codes, blockchain-backed traceability and encrypted cloud synchronisation; interactive Power BI dashboards that visualise geo-linked case and community data and support on-device analytics; and a standards-based interface that feeds results into national DHIS2 health-information systems. Finally, it fuses retrospective and real-time climate datasets with health records, applying multivariate and machine-learning models to uncover weather-driven transmission patterns and forecast disease risk— providing ministries and frontline workers with intuitive tools for evidence-based intervention planning and timing.

Work Package 4 focuses on turning DIDIDI’s prototypes into deployable medical devices. It establishes the ethical, privacy and security foundations for digital diagnostics; charts the regulatory, quality-management and IP roadmaps needed for CE-marking and local approval of the microscopes, assays and mobile apps in Uganda and Kenya; and explores business models that enable in-country manufacturing to maximise regional economic benefit. Leveraging these case studies, the work package also expands the translational pathway to a third African country—such as Senegal or Tanzania—by building stakeholder networks, running outreach workshops and aligning the platform with national health priorities, thereby preparing the ground for broader, continent-wide adoption.

Work Package 5 quantifies the value of DIDIDI’s innovations by coupling rigorous Health-Economic and Technology Assessment (HETA) with climate-sensitivity modelling and policy translation. It builds adaptable cost-effectiveness and budget-impact models for Uganda and Kenya, capturing stakeholder trade-offs between financial, societal and environmental benefits, and iteratively updating them with technical performance data from WP1–4. The package then layers retrospective and projected climate variables onto these models to calculate eCO2 impacts and to compare “climate-aware” versus health-only intervention strategies. Finally, the resulting evidence is distilled in stakeholder workshops and policy briefs that equip local and national authorities—as well as global bodies such as WHO—with data-driven guidance for planning, prioritising and scaling sustainable helminth-control programmes.

Ensure smooth, transparent and compliant delivery of DIDIDI by establishing a three-tier governance structure (General Assembly, Work-Package Leader Group, Project Management Group) that meets regularly, monitors technical and financial progress, resolves risks promptly and fulfils all contractual, reporting and quality-assurance obligations to the European Commission.

Work Package 7 secures high-level scientific governance for DIDIDI. It appoints the Scientific Lead as the formal liaison with the Global Health EDCTP3 Joint Undertaking, chairs both the General Assembly and Work-Package Leader Group, and manages the Advisory and Ethics Advisory Boards to steer the programme’s research integrity. In parallel, the Scientific Lead—supported by the Project Coordinator and Project Manager—continuously tracks milestones, budgets, deliverables and key performance indicators, reviewing outputs before submission to guarantee that every component of the project meets its scientific, ethical and timeline commitments.

Maximise the project’s scientific, societal and commercial impact by implementing an approved DEC plan—overseen by a dedicated committee—that governs timely, IP-safe dissemination of results, coordinated stakeholder engagement, open-source exploitation pathways and stewardship/global-access commitments, while tracking key performance indicators and adapting strategies throughout the project lifecycle and four years beyond.