Projects
Australia-Aotearoa Consortium for Epidemic Forecasting & Analytics (ACEFA)
The ACEFA NHMRC Centre of Research Excellence aims to support the timely, effective response to epidemic diseases in Australia through real-time data analytics, modelling, and forecasting.
Published research
Temporal analysis of respiratory virus epidemics in Victoria over winter 2024
During winter months of temperate regions, concurrent epidemics of multiple respiratory pathogens can occur, causing periods of increased clinical burden. Case time series, which are predominantly used to monitor infection levels, can exhibit substantial noise and day-of-the-week effects, limiting the visual interpretation of trends in raw data.
Inferring temporal trends of multiple pathogens, variants, subtypes or serotypes from routine surveillance data
Estimating the temporal trends in infectious disease activity is crucial for monitoring disease spread and the impact of interventions. Surveillance indicators routinely collected to monitor these trends are often a composite of multiple pathogens. For example, "influenza-like illness"-routinely monitored as a proxy for influenza infections-is a symptom definition that could be caused by a wide range of pathogens, including multiple subtypes of influenza, SARS-CoV-2, and RSV.
Characterization and individual-level prediction of cognitive state in the first year after ‘mild’ stroke
Mild stroke affects more than half the stroke population, yet there is limited evidence characterizing cognition over time in this population, especially with predictive approaches applicable at the individual-level. We aimed to identify patterns of recovery and the best combination of demographic, clinical, and lifestyle factors predicting individual-level cognitive state at 3- and 12-months after mild stroke.
Education and Qualifications
- Bachelor of Arts, University of Pennsylvania
- Master of Environmental Studies, University of Pennsylvania
- Doctor of Philosophy, University of Melbourne