Cletus Kwa Kum: A nonparametric Bayesian approach to estimating malaria prophylactic effect after two treatments

Two treatment regimens for malaria are compared in their abilities to cure and combat re-infection. Bayesian analysis techniques are used to compare two typical treatment therapies for uncomplicated malaria in children less than five years, not only in their power to resist recrudescence, but how long each treatment can postpone recrudescence or re-infection in case of failure. We derive a new way of analyzing this type of data using Markov Chain Monte Carlo techniques. The results which give the full posterior distributions, show that artemisinin-based combination therapy (ACT) is more efficacious than sulfadoxine--pyrimethamine. It reduced the risk of recrudescence. This is done using data from clinical trials at two different centres.