Predicting the impact of primaquine on Plasmodium falciparum transmission using multiscale modelling
- 1The University of Melbourne
Abstract
Primaquine is currently the only widely available antimalarial drug that targets mature Plas-modium falciparum gametocytes, the life stage in the human bloodstream that mediates transmission from humans to mosquitoes. The only study that provided large-scale field data suitable for examining the additional impact of the WHO-recommended dose of 0.25 mg/kg primaquine in an artemisinin-based combination therapy (ACT)-based mass drug administration (MDA) campaign was reported by Deng et al. (2018, Clinical Infectious Diseases). The study showed that both ACT alone and ACT plus primaquine substantially reduced average monthly malaria hospital rates and the prevalence of infection after the MDA campaign but no additional benefit was observed with primaquine. These findings challenge our expectations for the population-level impacts of primaquine and are in stark contrast to the predictions (of substantial population-level impacts) made by existing epidemiological-scale modelling studies. To address these knowledge gaps, we hypothesised that individuals adherence patterns to multi-round MDA campaigns could be a factor that explains these conflicting empirical observations. To examine this hypothesis, we developed a data-driven multiscale agent-based model of malaria infection and transmission, which quantitatively captures both the detailed biology of human infection kinetics and the pharmacodynamic actions of antimalarial drugs. Our model provides a coherent explanation for these apparently disparate observations, including the individual-level gametocytocidal effect of primaquine, the population-level impacts of primaquine in MDA campaigns, and the population-level impacts predicted by previous modelling studies. All three observations can be explained by underlying adherence patterns within a single modelling framework. We used our model to predict the effect of primaquine in routine case management outside MDA, finding that administration could significantly reduce the prevalence of infection, supporting its use as a transmission-blocking intervention against malaria.
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BibTeX
@misc{sun2026predicting,
title = {{Predicting the impact of primaquine on Plasmodium falciparum transmission using multiscale modelling}},
author = {X. Sun and J. A. Simpson and J. McCaw and P. Cao},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.21.26366166},
url = {https://www.medrxiv.org/content/10.64898/2026.10.21.26366166v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Predicting the impact of primaquine on Plasmodium falciparum transmission using multiscale modelling
AU - X. Sun
AU - J. A. Simpson
AU - J. McCaw
AU - P. Cao
PY - 2026
DA - 2026/10/21
PB - medRxiv
DO - 10.64898/2026.10.21.26366166
UR - https://www.medrxiv.org/content/10.64898/2026.10.21.26366166v1
AB - Primaquine is currently the only widely available antimalarial drug that targets mature Plas-modium falciparum gametocytes, the life stage in the human bloodstream that mediates transmission from humans to mosquitoes. The only study that provided large-scale field data suitable for examining the additional impact of the WHO-recommended dose of 0.25 mg/kg primaquine in an artemisinin-based combination therapy (ACT)-based mass drug administration (MDA) campaign was reported by Deng et al. (2018, Clinical Infectious Diseases). The study showed that both ACT alone and ACT plus primaquine substantially reduced average monthly malaria hospital rates and the prevalence of infection after the MDA campaign but no additional benefit was observed with primaquine. These findings challenge our expectations for the population-level impacts of primaquine and are in stark contrast to the predictions (of substantial population-level impacts) made by existing epidemiological-scale modelling studies. To address these knowledge gaps, we hypothesised that individuals adherence patterns to multi-round MDA campaigns could be a factor that explains these conflicting empirical observations. To examine this hypothesis, we developed a data-driven multiscale agent-based model of malaria infection and transmission, which quantitatively captures both the detailed biology of human infection kinetics and the pharmacodynamic actions of antimalarial drugs. Our model provides a coherent explanation for these apparently disparate observations, including the individual-level gametocytocidal effect of primaquine, the population-level impacts of primaquine in MDA campaigns, and the population-level impacts predicted by previous modelling studies. All three observations can be explained by underlying adherence patterns within a single modelling framework. We used our model to predict the effect of primaquine in routine case management outside MDA, finding that administration could significantly reduce the prevalence of infection, supporting its use as a transmission-blocking intervention against malaria.
ER -