AI for vector-borne diseases under changing climates

Project ID: 2228cd1389 (You will need this ID for your application)

Research Theme: Information and Communication Technologies

UCL Lead department: Institute for Risk and Disaster Reduction (IRDR)

Department Website

Lead Supervisor: Ting Sun

Project Summary:

One Health - the integration of human and animal surveillance systems - has been on the horizon for years, yet challenges persist in areas such as data formats, governance and system integration. Given that a significant majority of emerging infectious diseases (EID) are zoonotic, it is highly probable that future human epidemics will originate from animals. Meanwhile, climate change represents one of the most urgent issues facing humanity today. Among numerous climate-related risks, the increased potential for vector-borne and zoonotic diseases due to habitat displacement caused by changing climates could lead to endemic situations in previously unaffected parts of the world. Through synergies between climate modelling and AI predictive tools, we aim to enhance our understanding of how changing climates impact the abundance of vector populations across various ecosystems and their subsequent effects on human health.

This project is based at UCL Centre for Digital Public Health (dPHE) research initiative in LMICs (specifically Brazil). It offers opportunities for engagement with local stakeholders and impactful activities.

We anticipate successful candidates will hold an MSc degree in a STEM subject area; ideally demonstrating strong expertise in fields such as climate science, computer science, machine learning, statistics or remote sensing; epidemiology or public health would also be advantageous.