Integration of biostatistics and mathematical modelling to improve the control of malaria
Approximately 200 million clinical cases of malaria are treated globally each year. Artemisinin derivatives are the first line treatment for falciparum malaria. Alarmingly, resistance to these artemisinin derivatives, the most highly effective antimalarial drugs, has emerged in Southeast Asia, jeopardizing malaria control. This research program brings together advanced biostatistical research with mathematical modelling with the aim of improving treatment outcomes for malaria patients and identifying interventions that will prevent future disease. The research program will primarily focus on malaria, but the methodological advances have widespread applicability to other infectious diseases.
Mathematical models integrating blood anti-malarial drug concentrations with the parasite-time profile of an infected individual provide an avenue to studying drug action. Within this program, novel mathematical models for antimalarial drugs that account for the immune function of the infected individual and the drug action against sensitive and resistant strains will be developed. The predictive value of these biologically informed mathematical models depends on the validation of these models against clinical data. Drawing on advances in nonlinear mixed-effects modelling, we plan to fit a complex mechanistic nonlinear mixed-effects model to the data using Markov chain Monte Carlo Methods (MCMC).Using the derived parameter distributions and a simulation-based approach, optimal dosing regimens will be determined and provided to the World Health Organization.
For more details of individual research projects and publications please see our qMalaria research group website:- https://qmalaria.org/
Prof. Julie Simpson
Ms Tharkeshi Thanuja
Mr Saber Dini
- Members of the WorldWide Antimalarial Resistance Network (WWARN) and Tracking Resistance to Artemisinins Collaboration (TRAC)
- A/Prof Freya Fowkes, Burnet Institute, Melbourne, Australia
- Prof James McCaw, The University of Melbourne
- Profs. Francois Nosten, Ric Price and Nicholas White, The University of Oxford
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