HOPE and HELP: Modelling for Complex Humanitarian Engagement
THE CHALLENGE
Several notable challenges in the humanitarian system stem from poorly coordinated response efforts and a lack of effective leadership owing to disruptions in the flow of accurate information. Vulnerable populations themselves also often lack access to life-saving information, as well as the channels to provide feedback to humanitarian actors. Without effective feedback loops and consistent access to accurate, reliable information, humanitarian actors cannot be accountable to the populations they serve or optimize their decision-making.
THE SOLUTION
To address impediments to the smooth flow of information in humanitarian emergencies, Humanity Data Systems developed two applications: Humanitarian Operations Planning Environment (HOPE) and Humanitarian Enterprise Logistics and Provisioning (HELP). Both exhibit state-of-the-art functions of complex event processing, machine learning, and modelling for the humanitarian context whilst simplifying the process of collecting large-scale community feedback, thereby acting as a shared, interoperable solution for humanitarian stakeholders. Throughout their funding period, Humanity Data Systems completed the development of these applications and established a partnership with the Yemen Relief and Reconstruction Foundation to pilot their use in Yemen’s conflict context. An additional scaling strategy was developed, informed by a landscape analysis of humanitarian data science initiatives through engagements with various actors including IFRC, MSF, and UNHCR.
