Poster Presentation First Malaria World Congress 2018

Towards a predictive model of human malaria infection treatment and transmission control (#246)

Pengxing Cao 1 , Katharine Collins 2 , Sophie Zaloumis 3 , James McCarthy 2 , Julie Simpson 3 , James McCaw 1 3 4
  1. School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia
  2. QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
  3. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
  4. Modelling and Simulation, Infection and Immunity Theme, Murdoch Childrens Research Institute, The Royal Children's Hospital, Melbourne, Victoria, Australia

The World Health Organization’s goal is to eliminate malaria from the Greater Mekong Subregion by 2025. Achieving this is threatened by the spread of artemisinin resistance, highlighting the importance and urgency of assessing new antimalarial drugs and drug combinations that clear the blood-stage of the infection and reduce onward transmission. Controlled human malaria infection (CHMI) transmission studies where intensive sampling is undertaken to quantify parasitaemia, before and after treatment, and also targeted qRT-PCR assays can be undertaken to quantify the appearance of transmission stages (gametocytes) provide a rich data source to better understand the dynamics of both asexual blood-stage infection and gametocyte development. In this presentation, we will show how in silico models informed by data from a CHMI transmission study, contribute to improving malaria treatment and control. By constructing a mechanistic model of human malaria infection, that describes the interplay between drug concentration and parasite and gametocyte dynamics, and fitting the model to data from the CHMI transmission study of 17 subjects, we show that the model is able to reproduce the clinical data. We also estimate a number of key parameters related to the replication of asexual parasites, gametocyte generation and maturation, probability of transmission from human to mosquitoes and effect of piperaquine on gametocytogenesis. With further work on the calibration and validation of our model, we anticipate its predictive power will facilitate the design of future clinical trials, optimisation of drug regimens for treatment and for development of more effective interventions to block transmission.