Calibration and analysis of complex models: methodological development and application to explore the impact of HAART in AfricaMR/J014362/1

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Mathematical models are used routinely in government, the public sector, industry and academia to help predict the future and make policy decisions, such as what is the impact of ocean currents on the climate and how should we best prepare for the next flu pandemic? The usefulness of models in helping to make decision relies on how well they are can be matched to real data (model calibration) and how well we can analyse the models to find out how confident we should be about the predictions they make. In recent years models have become increasingly complex, but we don't yet have good methods to calibrate and analyse these more complicated models. The lack of these methods is a major obstacle to improving our predictions, and the policy decisions that affect all of us in the UK. HIV/AIDS remains the leading public health problem in much of sub-Saharan Africa. While increased access to treatment for HIV (highly active anti-retroviral therapy or HAART) has successfully reduced suffering and deaths among people living with HIV/AIDS, it is unknown how best HAART can be used to reduce the number of new HIV infections. Models would help us determine the best strategy, but we need improved methods of model calibration and analysis to do this.In this project we will develop new methods to calibrate and analyse complex individual-based stochastic models (these models are very computer-intensive as every individual is explicitly tracked through time). First we will develop two new model calibration methods specifically for stochastic models and also develop new methods that allow us to calibrate multiple models outputs at the same time (eg the number of people infected with HIV and the number of deaths from AIDS). Then we will compare these new methods with existing methods to see how they perform. We will go on to develop hybrid calibration methods that combines the strengths of our new and existing methods, to get the best of both. Finally we will apply our new methods to calibrate a complex model to data on HIV/AIDS trends in Africa, and use our fitted models to predict the impact of HAART on HIV/AIDS in Africa. The development and evaluation of robust methods for the calibration and analysis of complex models should result in the generation of more reliable scientific evidence and better health policy and funding decisions. In addition, an effective method of assessing the likely impact of HAART should lead to better informed policies and improved public health in Africa. If the models are accurate, the benefits may include fewer people dying and being infected with HIV, alleviating the substantial social and economic burden of the epidemic as well as reducing the burgeoning costs of HIV-related health care.An international multidisciplinary team will carry out this research. Statistical expertise is available from investigators from Durham University, Sheffield University and Cambridge University; expertise in the development and application of complex HIV models is available from investigators in the London School of Hygiene and Tropical Medicine; and virologic expertise and uniquely detailed high quality empirical data is available from MRC/UVRI in Uganda.