Evaluating the effectiveness and cost-effectiveness of interventions to eliminate infectious diseases

Since highly effective treatments for hepatitis C (HCV) became available in Australia in 2016, elimination of the disease is now a realistic possibility. However, many people remain undiagnosed, and elimination will involve a concerted effort to find and link them to care so that they can be cured before developing liver cirrhosis or liver cancer. So far, many interventions have been implemented to try to increase diagnosis rates, but it is unclear which ones have been the most effective because they have been implemented simultaneously in some locations. This project will use mathematical modelling to untangle these combined effects to determine which interventions have had the greatest impact. The project will involve calibrating an existing HCV model to testing, treatment, and epidemiological data, all of which includes the combined effects of changes to multiple interventions over time. The model they will then be used to simulate counter-factual scenarios where individual interventions did not occur, to estimate what might have happened in their absence and therefore their effectiveness. Data from the specific health services will be analysed to inform the model and cost of interventions. Interventions will be ranked according to their increase in treatment uptake, and cost per additional person treated. Outcomes of this project will be used to inform the response to HCV elimination in Australia.