This project aims to forecast the risk of infectious disease spread, such as COVID-19 and dengue, based on human movement patterns. We'll use multiple data sources that describe people movement in order to understand individual and population level mobility patterns, and use empirical disease case data to model the effect of movement on the spread of disease.
Within this project, you'll:
- collect and analyse different data sources on human movement, including:
- airline travel statistics
- geo-tagged social media
- travel surveys
- arrival cards
- design models that describe and predict human movement
- model diffusion processes on top of the mobility network.
The project has the following expected outcomes:
- models of people movement at in-country and inter-country levels
- diffusion models and algorithms for relevant diseases
- research outputs (publications) on the development models and algorithms.
Skills and experience
To participate in this research, we expect you to have skills or experience with:
- data analysis
- Python, R, or Matlab.
While not mandatory, we'd also prefer if you had skills or experience with:
- mobility modelling
- network science.
You may be eligible to apply for a research scholarship.
Contact the supervisor for more information.