Malaria

Imperial malaria model

Lead modeller: Lucy Okell

Link to all modelling group members

Institution(s): Imperial

Brief description of model:

To be updated.

Key publication(s)

Model code (where available):

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CRID malaria model

Lead modeller: Charles Wondji

Link to all modelling group member

Institution(s): Centre for Research in Infectious Diseases

Brief description of model:

To be updated.

Link to publication(s)

Link to publicly available code (where available):

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UAC-LABEF malaria model

Lead modeller: Romain Glèlè Kakaï

Link to all modelling group members

Institution(s): Universite D'Abomey-Calavi (UAC) and Mountain Top University

Brief description of model:

An age-structure mathematical stochastic model is developed to analyze the impacts of vaccination on malaria transmission and burden in endemic countries. The model stratifies the human population into three subgroups: vaccinated with first three doses (age cohort 0), vaccinated with a booster dose (age cohort 1) and unvaccinated (age cohorts 2 to 100). Each subgroup is split into six compartments: Susceptible, Exposed, Asymptomatic, Uncomplicated malaria, Severe malaria, Hospitalized and Recovered. The model incorporates other interventions, such as the use of Long-lasting Insecticide-treated bed Nets (LLINs) and access to treatment for uncomplicated and severe malaria. Two malaria vaccines are considered: RTS,S/AS01E and R21. The model’s parameters are estimated using a nonlinear least squares method with the built-in function fminsearchbnd of Matlab2023a. The model is driven by the Entomological Inoculation Rate (EIR) and first estimates the initial vaccine efficacy and the decay rate before predicting the mean number of malaria cases, deaths, number of years of life lost YLL), and disability-adjusted life-years (DALYs) in each human age cohort for several years under various vaccination scenarios.

Key publication(s)

Model code (where available):

https://github.com/ProfGLELE/Malaria-model-code-.git

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TKI malaria model

Lead modeller:

Link to all modelling group members

Institution(s):

Brief description of model:

To be updated.

Key publication(s)

Model code (where available):

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