March 16, 2020
Understanding and controlling the spread of antimalarial resistance is a major challenge for malaria elimination. Mathematical models, synthesising existing data collected from both individual and population scale, are particularly useful and efficient tools to study the dynamics of drug resistance and make predictions about optimal control strategies.
Supported by the ACREME Seed Grant scheme, Dr Pengxing Cao and colleagues have developed a data-informed multiscale model of malaria transmission which now serves as a platform to further study the emergence and spread of antimalarial resistance. The novelty of the model lies in the establishment of a sophisticated within-host model of malaria parasite infection calibrated and validated based on novel human volunteer infection trial data and the integration of the predictive within-host model into population-level transmission dynamics. The within-host model has been published in eLife (https://doi.org/10.7554/eLife.49058) and the transmission model is in development.