ArticleBioMed research international2015
The Implications of HIV Treatment on the HIV-Malaria Coinfection Dynamics: A Modeling Perspective.
Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Should we care about Plasmodium vivax and HIV co-infection? A systematic review and a cases series from the Brazilian Amazon.Malaria journal · 2021Pooled it
- A Systematic Literature Review of Mathematical Models for Coinfections: Tuberculosis, Malaria, and HIV/AIDS.Journal of multidisciplinary healthcare · 2024Review
- Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy.Computational and mathematical methods in medicine · 2020Article
- The Impact of Antiretroviral Therapy on Malaria Parasite Transmission.Frontiers in microbiology · 2019Article
- Spatial overlaps in the distribution of HIV/AIDS and malaria in Zimbabwe.BMC infectious diseases · 2018Article
- Malaria and HIV coinfection in sub-Saharan Africa: prevalence, impact, and treatment strategies.Research and reports in tropical medicine · 2018Review
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Most hosts harbor multiple pathogens at the same time in disease epidemiology. Multiple pathogens have the potential for interaction resulting in negative impacts on host fitness or alterations in pathogen transmission dynamics. In this paper we develop a mathematical model describing the dynamics of HIV-malaria coinfection. Additionally, we extended our model to examine the role treatment (of malaria and HIV) plays in altering populations' dynamics. Our model consists of 13 interlinked equations which allow us to explore multiple aspects of HIV-malaria transmission and treatment. We perform qualitative analysis of the model that includes positivity and boundedness of solutions. Furthermore, we evaluate the reproductive numbers corresponding to the submodels and investigate the long term behavior of the submodels. We also consider the qualitative dynamics of the full model. Sensitivity analysis is done to determine the impact of some chosen parameters on the dynamics of malaria. Finally, numerical simulations illustrate the potential impact of the treatment scenarios and confirm our analytical results.
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