ArticleInfectious Disease Modelling2024
Modeling and investigating malaria P. Falciparum and P. Vivax infections: Application to Djibouti data.
Article in Infectious Disease Modelling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of epidemiological models for malaria transmission in Sub-Saharan Africa.Malaria journal · 2026Pooled it
- [Mosquito-borne diseases in the Republic of Djibouti: a review of the literature].Medecine tropicale et sante internationale · 2025Pooled it
- Computational Screening of Djiboutian Medicinal Plants Reveals Potential Dual Inhibitors AgainstCurrent issues in molecular biology · 2026Article
- Comparative evaluation of synchronization methods for Plasmodium falciparum: Efficiency, practicality and experimental applicability.Parasites, hosts and diseases · 2026Article
- Immune Modulation by Plasmodium yoelii: Insights From Lethal and Non-Lethal Strains.Parasite immunology · 2026Review
- Mixed malaria infections: A critical review and Detect-Characterise-Act surveillance framework.Current research in parasitology & vector-borne diseases · 2026Review
- The probability of Plasmodium vivax acute illness following primary infection and relapse in Papua New Guinea.PLoS neglected tropical diseases · 2025Article
- Anopheles mosquito fauna, blood meal sources and transmission intensity from high and moderate malaria endemic areas of Ethiopia.Scientific reports · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malaria is an infectious and communicable disease, caused by one or more species of Plasmodium parasites. There are five species of parasites responsible for malaria in humans, of which two, Plasmodium Falciparum and Plasmodium Vivax, are the most dangerous. In Djibouti, the two species of Plasmodium are present in different proportions in the infected population: 77% of P. Falciparum and 33% of P. Vivax. In this study we present a new mathematical model describing the temporal dynamics of Plasmodium Falciparum and Plasmodium Vivax co-infection. We focus briefly on the well posedness of this model and on the calculation of the basic reproductive numbers for the infections with each Plasmodium species that help us understand the long-term dynamics of this model (i.e., existence and stability of various eqiuilibria). Then we use computational approaches to: (a) identify model parameters using real data on malaria infections in Djibouti; (b) illustrate the influence of different estimated parameters on the basic reproduction numbers; (c) perform global sensitivity and uncertainty analysis for the impact of various model parameters on the transient dynamics of infectious mosquitoes and infected humans, for infections with each of the Plasmodium species. The originality of this research stems from employing the FAST method and the LHS method to identify the key factors influencing the progression of the disease within the population of Djibouti. In addition, sensitivity analysis identified the most influential parameter for Falciparium and Vivax reproduction rates. Finally, the uncertainty analysis enabled us to understand the variability of certain parameters on the infected compartments.
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