Tremendous progress has been made over the last decades in controlling malaria. From 2000 to 2015 scale-up of control and curative interventions enabled a 60% reduction in malaria death rates and a 40% reduction in rate of clinical disease. Despite these gains, we face significant challenges if we are to eliminate malaria entirely. Changing malaria epidemiology that accompanies transmission decline requires programs to direct efforts toward populations historically underserved by the health sector. Reaching these communities with services is difficult and expensive. At the same time the efficacy of current malaria interventions is threatened by spreading resistance of mosquitos to insecticides and of malaria parasites to drugs. Succeeding toward elimination targets requires new tools, and we should prioritize tools that are best able to reduce and halt malaria transmission.
Mathematical modelling can help understand malaria dynamics and interactions between malaria tools and the malaria parasite, human and mosquito hosts. Models can also help assess new tools such as vaccines beyond clinical trials. Combining different models with early clinical data from new drugs and vaccines we are able to assess how likely these tools will achieve health goals and also define how best to deploy them. Until now, models have not been used in this way.
We will combine preclinical and clinical data from the Swiss Tropical and Public Health Institute and partners to build mathematical models to inform development of new malaria drugs and vaccines. Specifically, we aim to define which type and how to use these tools within populations for malaria elimination, especially in light of drug resistance. This project will yield evidence to accelerate decisions in drug and vaccine development.