Malaria is an infectious disease with an immense global health burden. Plasmodium vivax is the most geographically widespread species of malaria. Relapsing infections, caused by the activation of liver-stage parasites known as hypnozoites, are a critical feature of the epidemiology of Plasmodium vivax. Hypnozoites remain dormant in the liver for weeks or months after inoculation, but cause relapsing infections upon activation. Here, we introduce a dynamic probability model of the activation-clearance process governing both potential relapses and the size of the hypnozoite reservoir. We begin by modelling activation-clearance dynamics for a single hypnozoite using a continuous-time Markov chain. We then extend our analysis to consider activation-clearance dynamics for a single mosquito bite, which can simultaneously establish multiple hypnozoites, under the assumption of independent hypnozoite behaviour. We derive analytic expressions for the time to first relapse and the time to hypnozoite clearance for mosquito bites establishing variable numbers of hypnozoites, both of which are quantities of epidemiological significance. Our results extend those in the literature, which were limited due to an assumption of collective dormancy. Our within-host model can be embedded readily in multiscale models and epidemiological frameworks, with analytic solutions increasing the tractability of statistical inference and analysis. Our work therefore provides a foundation for further work on immune development and epidemiological-scale analysis, both of which are important for achieving the goal of malaria elimination.
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S. Mehra acknowledges funding from the Australian Mathematical Sciences Institute (AMSI) Vacation Research Scholarships 2018/2019. J.M. McCaw’s research is supported by the Australian Research Council (ARC) Discovery Project DP170103076. J.A. Flegg’s research is supported by the ARC DECRA Fellowship DE160100227. P.G. Taylor’s research is supported by the ARC Laureate Fellowship FL130100039 and the ARC Centre of Excellence for the Mathematical and Statistical Frontiers (ACEMS).
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Mehra, S., McCaw, J.M., Flegg, M.B. et al. An Activation-Clearance Model for Plasmodium vivax Malaria. Bull Math Biol 82, 32 (2020). https://doi.org/10.1007/s11538-020-00706-1
- Continous time Markov chain