An approach to model the costs and effects of case management of Plasmodium falciparum malaria in sub-saharan Africa.

An important shortcoming of existing methods for estimating the cost-effectiveness of malaria control interventions is that the incidence of illness and transmission dynamics are assumed to be independent of the case management system. We have developed a model for case management and integrated it into a stochastic simulation of Plasmodium falciparum malaria dynamics. This allows us to predict the incidence of clinical episodes and of mortality while incorporating effects of case management on persistence of parasites and transmission. We make predictions for a range of different transmission intensities in sub-Saharan Africa and simulate a range of case management scenarios with different coverage rates. The model predicts that high treatment rates have a proportionately greater epidemiologic impact at low transmission levels. Further development is needed for models for health-seeking behavior and referral patterns. The current model is a first step towards useful predictions of the epidemiologic and economic consequences of introducing and/or scaling-up of malaria control interventions.