We design and develop a range of mathematical models and conduct simulation studies to support HPTN research activities including:
- Understand HIV epidemic dynamics: Identify who is most vulnerable to acquiring and transmitting infection, assess the impact of past interventions and key prevention gaps
- Identify new interventions: Inform design, conduct, final analysis of clinical trials
- Optimise HIV prevention programmes: Assess the population-level impact of scaling up HIV intervention programmes and monitor progresses toward set goals
- Determine HIV prevention needs: Define the efforts needed to control and eliminate HIV as well as define and validate useful prevention targets
- Improve and develop new mathematical modelling tools: Conduct methodological and validation studies and innovative model development work to address new and challenging research questions
- Assess existing evidence to improve model assumptions: Systematic and detailed meta-analytic reviews and secondary data analysis
Our projects are divided in three main types:
- HPTN Protocol based projects
- Non-protocol based projects
- External consultation projects
HPTN Protocol based projects
We conduct modelling studies to inform the design, conduct, analysis and interpret clinical trials before, during, and after they are completed
- Research questions and directions
- HPTN protocol development
- Study objectives
- Survey instruments
- Trial design
- Preliminary analysis of efforts needed to have meaningful intervention impact at the population level
- Interim analysis of trials using programatic data to monitor progress and inform the conduct of the trial
- Population level impact on HIV based on final trial results
- Generalisation of trial results to a wider ranges of settings and populations
- Cost-effectiveness analysis of scaling up tested interventions
Non protocol based projects
- Understand HIV transmission dynamics
- Novel model development to study challenging new research questions
- Inform the design of clinical trials
- Validate mathematical models, assess the influence of structural assumptions and formal model comparisons
- Systematic literature reviews of mathematical models and of epidemiological studies to estimate model parameters