We have developed a general computing platform for comparing, fitting, and evaluating different individual-based stochastic simulations of malaria epidemiology.
In the next phase of the project, we propose to exploit the functionality of this modeling platform to provide high quality input to policy and planning processes.
The project will continue to develop new models and model components for modeling of intervention mixes, including vaccines, vector control, and chemotherapy, and also surveillance and response systems. The project will develop methods for bringing together the results of ensembles of multiple models. In addition model validations will be carried out, and the models will be integrated with high quality databases to render them geographically specific. Specific components of the project will focus on outreach to potential clients, and develop capacity to anticipate and react promptly to requests from the R & D and malaria intervention communities.