Health Metrics and Disease Modelling

Supporting Sustainable Healthcare

We live in an age where digital technologies and AI are extending possibilities for medical and healthcare, interventions, and models of delivery. Research developing intelligent healthcare technology and innovative metagovernance approaches will support significant scaling of medical infrastructures, capable of sustainable development.

Understanding the precursors for poor health through healthcare metrics, AI, big data and modelling of disease incidence, development, spread, and viral load implications will be a third research focus of the institute.

LIIRH will deliver novel insights and interventions aimed at democratising healthcare delivery and providing equitable access to quality care and disease management for disadvantaged communities and rural populations globally. An evolving programme will deliver excellence in peer-reviewed research and collaborative community engagement in rural healthcare projects.

Research insights from disease demographics, big data intelligence, and contextual study will provide opportunities to deliver enhanced diagnostics, responsive interventions and exponential, untapped healthcare technologies and mobile solutions to support sustainable, effective healthcare to rural populations.

Further expertise in big data analytics, Machine Learning, and interactive technologies are provided by the School of Computer Science (SoCS), who are leading innovative rural health technology and educational programs, launching the world's first Centre for Doctoral Training in Agri-Food Robotics in collaboration with Cambridge and East Anglia universities. The advanced training centre in agri-food robotics is the largest ever cohort of Robotics and Autonomous Systems (RAS) specialists for the global food and farming sectors, supported by an Engineering and Physical Sciences Research Council (EPSRC) award.