Infectious disease research involves the collection and analysis of quantifiable data. Good data can provide important insights into the characteristics of infectious diseases, and enables our researchers to find correlations, test hypotheses or predict future outcomes, leading to the development of better treatments, cures, and preventions for infectious diseases.
Our researchers are leaders in biostatistics, quantitative analysis, and modelling, contributing to a wide range of infectious disease analysis and study design.
Working with clinical researchers at the Kirby Institute and with our partners, our biostatisticians apply rigorous statistical methodology to the design, conduct and analysis of biomedical research studies to facilitate gold-standard clinical research. This involves setting up the technical framework to collect and analyse the data that is collected in a clinical trial, which tests a biomedical intervention such as a treatment or cure. Multiple clinical trials designed and implemented with our biostatisticians have led to changes in international HIV treatment guidelines, including low dose-efavirenz, NRTI-sparing second-line ART, and immediate initiation of ART for all people diagnosed with HIV.
Our modellers use mathematical, statistical or economic models to evaluate potential interventions and to predict future health outcomes under different scenarios, or to compare alternative policy options.
Our researchers have taken a lead role in modelling COVID-19 pandemic scenarios, including in remote Aboriginal communities. They've helped predict the public health impact of health interventions like lockdowns, mask wearing, and vaccination scenarios. This work helps to inform policy makers on public health measures to ensure minimal disease burden in the community and the health system. In addition, modelling of immune dynamics has contributed to understanding immune boosting and waning immunity in SARS-CoV-2 vaccination and infection.
We also have a team of scientists who apply mathematical techniques to a range of biological health data to predict how infectious diseases will spread and respond to treatments in a range of environments. For example, our teams are using mathematical modelling and analysis to understand the HIV life cycle. Measuring the number of cells in the latent reservoir of HIV when a person is taking treatment is well understood, but our teams are building on that knowledge by investigating when and how HIV cells reactivate from latency to active infection. Ultimately, this work will provide the evidence base to develop new ways to target and eliminate HIV.
The Kirby Institute is also home to EPIWATCH, an artificial intelligence-driven system harnessing vast, open-source data to generate automated early warnings for epidemics worldwide. This system works to identify outbreak signals earlier than traditional laboratory or hospital-based surveillance and can provide a trigger to investigate an early outbreak signal. We also specialise in risk analysis tools in biosecurity.
Programs working in this area:
- Biostatistics and Databases Program
- Infection Analytics Program
- Biosecurity Program
- Surveillance and Evaluation Research Program