Integrating parallel Plasmodium falciparum and Plasmodium vivax malaria models in a unified framework to capture co-endemic prevalence patterns
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Published version
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Author(s)
Type
Journal Article
Abstract
Background Plasmodium falciparum and Plasmodium vivax cause most malaria cases worldwide and are co-endemic in many countries, yet differ substantially in biology and in their responses to common interventions. As programmes drive down P. falciparum, P. vivax is a growing challenge for elimination, but most modelling tools assess the species separately, limiting coordinated policy. We aimed to build a unified malaria transmission modelling framework for co-endemic settings and assess how well it reflects global prevalence.
Methods We integrated an established P. vivax model into a flexible P. falciparum modelling platform, enabling parallel simulation of both species within a shared biological, demographic, and intervention environment. Modelled equilibrium prevalences, matched by mosquito density, were compared with 19,225 yearly co-prevalence estimates from the Malaria Atlas Project (769 sub-national regions, 33 co-endemic countries, 2000–2024); uncertainty was represented by 95% quantile-based regions from 50 parameter draws. We assessed how this fit was modified by biological factors and simulated interventions.
Results Here we show that the framework captures 51% of co-prevalence estimates within its uncertainty regions, rising to 65.5% when country-specific P. vivax relapse rates and human Duffy negativity are included. P. falciparum predominates where mosquito densities are high, whereas P. vivax is relatively more prevalent at lower densities. Simulated interventions produce larger relative reductions in P. falciparum prevalence, while P. vivax shows greater rebounds after intervention withdrawal, particularly at low mosquito densities.
Conclusions This unified framework provides a quantitative tool to support coordinated, species-specific intervention strategies in co-endemic settings, a step toward sustainable malaria elimination.
Methods We integrated an established P. vivax model into a flexible P. falciparum modelling platform, enabling parallel simulation of both species within a shared biological, demographic, and intervention environment. Modelled equilibrium prevalences, matched by mosquito density, were compared with 19,225 yearly co-prevalence estimates from the Malaria Atlas Project (769 sub-national regions, 33 co-endemic countries, 2000–2024); uncertainty was represented by 95% quantile-based regions from 50 parameter draws. We assessed how this fit was modified by biological factors and simulated interventions.
Results Here we show that the framework captures 51% of co-prevalence estimates within its uncertainty regions, rising to 65.5% when country-specific P. vivax relapse rates and human Duffy negativity are included. P. falciparum predominates where mosquito densities are high, whereas P. vivax is relatively more prevalent at lower densities. Simulated interventions produce larger relative reductions in P. falciparum prevalence, while P. vivax shows greater rebounds after intervention withdrawal, particularly at low mosquito densities.
Conclusions This unified framework provides a quantitative tool to support coordinated, species-specific intervention strategies in co-endemic settings, a step toward sustainable malaria elimination.
Date Issued
2026-07-07
Date Acceptance
2026-05-22
Citation
Communications Health, 2026, 1
ISSN
3091-4841
Journal / Book Title
Communications Health
Volume
1
Copyright Statement
© The Author(s) 2026. 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/.
License URL
Identifier
10.1038/s44528-026-00007-4
Publication Status
Published
Article Number
ARTN 11
Date Publish Online
2026-07-07