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Forecasting disease spread risk based on human movement patterns

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.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty of Science
School of Computer Science

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