STAMINA

Introduction

Recent pandemics demonstrated the potential for severe, cross-border public health threats, requiring coordinated international responses. However, varying legal, administrative, and political cultures, coupled with a lack of transboundary crisis management structures, often hinder effective disaster response.

The STAMINA project aimed to address these challenges by developing a decision support tool and policy guidelines to better equip pandemic crises management practitioners at national and regional levels. Specifically, the project partners:

Mapped existing pandemic emergency frameworks, identifying areas for improvement and best practices in cross-organisational preparedness,
Created a toolset that includes predictive modelling, a machine learning-based Early Warning System, real-time web and social media analytics, a scenario generation tool, point-of-care diagnostic tools for rapid detection of emerging diseases, and crisis management tools,
Generated guidelines for cross-organisational preparedness and response.

The STAMINA toolset was tested across 12 nations (Greece, Czech Republic, Romania, Turkey, Lithuania, Tunisia, UK, Slovenia, Austria, Netherlands, Spain and France) to enhance transboundary pandemic management capabilities.

Trilateral's role

Trilateral Research contributed to the project by:

Overseeing the project’s ethical and data protection protocols, conducting a comprehensive evaluation of the STAMINA tools to identify and address potential ethical risks and to guarantee adherence to GDPR standards.
Developing a real-time web and social media analytics tool to monitor public trust in science and institutions and flag possible disease outbreaks. Trilateral’s bespoke AI tool tracked online mentions of the outbreaks of disease to identify key reliable sources and enable more informed decision-making at a policy level.
Leading the project’s science communication efforts to raise awareness about the project’s findings among policymakers, experts, media, healthcare workers, and first responders.

Project impact

The project’s impact centred on advancing pandemic preparedness through innovative predictive modelling. Seven models, leveraging AI and Deep Learning, were developed to forecast outbreak impacts on society and healthcare systems. These models can enable authorities to proactively allocate resources by predicting case numbers, deaths, and healthcare infrastructure strain.

The STAMINA project’s goal of improving pandemic management was directly supported by a comprehensive legislative gap analysis which identified critical vulnerabilities in national preparedness, surveillance, and communication. These findings present a significant opportunity for policymakers to implement AI-driven public health strategies, thereby strengthening national pandemic management and enabling more effective international collaboration on data sharing and risk communication.