Preparing for a world with artemisinin resistance: using individual-based epidemiological modeling to minimize the long-term detrimental effects of antimalarial drug resistance

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Project Summary/Abstract Plasmodium falciparum is the deadliest of the five species of malaria parasites that infect humans. Annually, there are over 200 million symptomatic cases of falciparum malaria and over 400,000 deaths – the majority of which occur in African children under the age of five. The two major interventions that have had an effect on reducing malaria prevalence over the past twenty years are mosquito control and use of antimalarial drugs. The most important class of drugs in this effort has been the artemisinin derivatives, which since 2005 have been deployed as artemisinin combination therapies (ACTs) only, in order to reduce the probability of emergence and spread of artemisinin-resistant genotypes. Despite these efforts, artemisinin resistance did emerge, and we are now facing the dangerous prospect that these drug-resistant genotypes may spread to Africa, where most of the world’s malaria cases occur. In this proposal, we will introduce and evaluate a number of drug-resistance management strategies that are intended to prevent, delay, and slow down the spread of drug-resistant genotypes of P. falciparum. First, we will make a number of technical advances in our existing individual-based (agent-based) simulation that we already use to model the evolution and epidemiology of P. falciparum in human populations. We will add explicit grid- based spatial structure to make the model more realistic. Additionally, we will add a genotype-phenotype map and clinically-parameterized pharmacodynamic/pharmacokinetic sub-models to make the model’s drug- resistance component as realistic as current data allow. Second, we will evaluate strategies for how best to manage the population-level introduction of novel antimalarial therapies that will become available in the 2020s. The strategies will be aimed at minimizing the long-term risk of drug resistance to both the novel therapies and to currently used ACTs, in order to minimize the number of treatment failures in the long run. Finally, we will parameterize country scenarios for Cambodia, Zambia, and Burkina Faso to provide specific country-level advice in low, medium, and high transmission malaria settings on how best to preëmpt drug resistance or minimize its current spread. As Cambodia is the epicenter of the current wave of artemisinin resistance, the Cambodia- specific model will be used to provide advice on how to contain and eliminate currently circulating artemisinin- resistant genotypes of P. falciparum.