A Multiscale Mathematical Model of Plasmodium Vivax Transmission
Anwar, Md Nurul, Hickson, Roslyn I., Mehra, Somya, McCaw, James M., and Flegg, Jennifer A. (2022) A Multiscale Mathematical Model of Plasmodium Vivax Transmission. Bulletin of Mathematical Biology, 84. 81.
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Abstract
Malaria is caused by Plasmodium parasites which are transmitted to humans by the bite of an infected Anopheles mosquito. Plasmodium vivax is distinct from other malaria species in its ability to remain dormant in the liver (as hypnozoites) and activate later to cause further infections (referred to as relapses). Mathematical models to describe the transmission dynamics of P. vivax have been developed, but most of them fail to capture realistic dynamics of hypnozoites. Models that do capture the complexity tend to involve many governing equations, making them difficult to extend to incorporate other important factors for P. vivax, such as treatment status, age and pregnancy. In this paper, we have developed a multiscale model (a system of integro-differential equations) that involves a minimal set of equations at the population scale, with an embedded within-host model that can capture the dynamics of the hypnozoite reservoir.
In this way, we can gain key insights into dynamics of P. vivax transmission with a minimum number of equations at the population scale, making this framework readily scalable to incorporate more complexity. We performed a sensitivity analysis of our multiscale model over key parameters and found that prevalence of P. vivax blood-stage infection increases with both bite rate and number of mosquitoes but decreases with hypnozoite death rate. Since our mathematical model captures the complex dynamics of P. vivax and the hypnozoite reservoir, it has the potential to become a key tool to inform elimination strategies for P. vivax.
| Item ID: | 75466 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 1522-9602 |
| Keywords: | Vivax transmission model, Hypnozoite dynamics, Multiscale model, Hypnozoite activation |
| Copyright Information: | © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Funders: | Australian Research Council (ARC), National Health and Medical Research Council Australia (NHMRC) |
| Projects and Grants: | ARC DP170103076, ARC DP210101920, ARC DE160100227, ARC DP200100747, NHMRC Australian Centre of Research Excellence in Malaria Elimination |
| Research Data: | https://github.com/n-anwar/multiscale_model_Figures.git |
| Date Deposited: | 18 Jul 2022 23:21 |
| FoR Codes: | 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490102 Biological mathematics @ 50% 42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 50% |
| SEO Codes: | 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280112 Expanding knowledge in the health sciences @ 100% |
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