A Nonparametric Bayesian Approach to Estimating Malaria Prophylactic Effect After Two Treatments (International Journal of Statistics in Medical Research, 2013)
Two treatment regimens for malaria are compared in their abilities to cure and combat reinfection. Bayesian analysis techniques are used to compare two typical treatment therapies for uncomplicated malaria in children under five years, not only in their power to resist recrudescence, but also how long they can postpone recrudescence or reinfection in case of failure. We present a new way of analysing this type of data using Markov Chain Monte Carlo techniques. This is done using data from clinical trials at two different centres. The results which give the full posterior distributions show that artemisinin-based combination therapy is more efficacious than sulfadoxine-pyrimethamine. It both reduced the risk of recrudescence and delayed the time until recrudescence.