Modelling the contribution of relapse infections to the epidemiology and control of Plasmodium vivax malaria

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Plasmodium vivax is the most widely distributed species of malaria across the world, with almost 3 billion people living in at-risk countries, and an estimated 100 - 400 million clinical cases every year, mostly in Asia and South America. Despite the enormous burden to public health, research into P. vivax is neglected compared to P. falciparum (the parasite species responsible for the majority of cases of malaria in Africa). A key feature of P. vivax malaria not seen in all forms of malaria is the occurrence of relapse infections, where infected individuals become re-infected weeks to months after recovering from their initial infection. This is a phenomenon occasionally seen in British and European travellers returning from Asia and South America. Despite taking daily anti-malarial tablets during their trip, some travellers suffer relapse infections upon their return and may experience a potentially fatal episode of clinical malaria, often up to a year later. In contrast, relapse infections are a regular occurrence for people living in countries with P. vivax malaria. However in practice, in regions of the world where P. vivax is continuously transmitted it is difficult to distinguish these relapses from new infections arising from mosquito bites.Relapse infections arise from P. vivax parasites that lie dormant in the liver and re-activate at a later date. The triggers for relapse infections are still poorly understood, with explanations ranging from fever due to other diseases, exposure to subsequent mosquito bites, and a biological clock for relapse infections. In this project, I aim to explore what causes infections to relapse by using simulation models to analyse data from approximately 4,000 people exposed to P. vivax infection in trials in Papua New Guinea, the Solomon Islands, Thailand and Brazil. With an understanding of how infections relapse, I will develop a simulation model of how P. vivax is transmitted between humans and mosquitoes, and use this to investigate how scaling up malaria control interventions can be used to control or eliminate P. vivax from endemic countries. P. vivax can be prevented by using insecticide treated nets to kill infected mosquitoes, or anti-malarial drugs to kill the parasites inside humans. Most anti-malarial drugs only target blood-stage infection and leave parasites in the liver untouched. A notable exception is primaquine which targets both parasites in the blood and dormant parasites in the liver. A century of experience of malaria control has shown that drug treatment and vector control reduce cases of P. vivax malaria, however the impact of these interventions on population level transmission has been difficult to predict. I will use a simulation model of the transmission of P. vivax to compare how treatment programmes with drugs targeting different stages in the parasite's lifecycle can protect the infected individual, and the wider community by preventing onward transmission. Insights from these models will contribute to the evidence base required to choose optimal combinations of malaria control interventions as national malaria control programmes strive for increased P. vivax control and in some cases, elimination.