Oral Presentation 8th International Conference on Plasmodium vivax Research 2022

A mathematical model of hypnozoite accrual, multiple infections and acquired immunity for Plasmodium vivax (80216)

Somya Mehra 1 , Peter G Taylor 1 , James M McCaw 1 , Eva Stadler 2 , David Khoury 2 , Jennifer A Flegg 1
  1. University of Melbourne, Parkville, VICTORIA, Australia
  2. Kirby Institute, University of New South Wales, Kensington, New South Wales, Australia

The hypnozoite reservoir is a salient characteristic of the epidemiology of Plasmodium vivax, with implications for the acquisition of immunity and the distribution of multiple infections. Mathematical modelling of hypnozoite dynamics can provide key epidemiological insights.

Here, we present a mathematical model of P. vivax transmission, allowing for hypnozoite accrual; multiple blood-stage infections and the acquisition of transmission-blocking and clinical immunity. Rather than assuming distributional forms for key epidemiological parameters, we derive joint probabilistic distributions for hypnozoite and blood-stage infection dynamics from first principles. We capture three key sources of stochasticity, namely:

  • Stochasticity in dormancy, clearance and activation times for each hypnozoite;
  • Variability in the number of relapses arising from each bite; and
  • A random sequence of bite times, under a known bite rate.

By constructing a ‘queue’ of hypnozoites within a human host, we draw on results from queueing theory to jointly characterise hypnozoite, blood-stage infection and immunity dynamics for an individual in a general transmission setting. Our analytic within-host distributions elucidate important patterns of P. vivax infection. 

We then embed our derived probabilistic distributions in a simple population-level transmission model, monitoring only the proportion of infected mosquitoes and the probability of human-to-mosquito transmission for each bloodmeal.  By drawing on results from our within-host model, we are able to recover complete population-level distributions for several quantities of epidemiological interest, including the size of the hypnozoite reservoir; acquired immunity; multiple blood-stage infections; the relative contribution of relapses to the infection burden and the cumulative number of recurrences over time. Our models provide insights into important, but poorly understood features of the epidemiology of Plasmodium vivax.