Last Updated: 21/11/2023
New approaches to modelling malaria transmission and insecticide resistance: using realistic mosquito biology and behaviour, and network methods
Objectives
The proposed project aims to adapt standard mosquito-borne modelling frameworks by including additional details about mosquito biology and behaviour in the presence of insecticides.
Liverpool School of Tropical Medicine (LSTM), United Kingdom
This research relates to Mathematical Epidemiology, i.e. mathematical modelling of infectious diseases. Specifically, modelling of malaria, a serious mosquito-borne disease, which is the cause of death of thousands of people every year, especially in African countries. Emerging insecticide resistance among mosquitoes is a key concern and worthy of further exploration. The lack of research on networks regarding vector-borne diseases and detailed vector biology gives an opportunity to produce novel methodologies. The aims and objectives of the research – This project will adapt standard mosquito-borne modelling frameworks by taking into consideration details about mosquito biology and behaviour, and further understand the impact of insecticide resistance on malaria transmission. The aim is to calibrate the adapted model to real-life mosquito data collected in Côte d’Ivoire, and explore different scenarios regarding insecticides. An additional aim is to develop theoretical approaches on network models in order to better understand malaria transmission dynamics. The novelty of the research methodology – This project will apply adapted models on data collected from specific regions in Africa to compare the different model frameworks. Additionally, construct network models aiming to develop the limited existing research in network models regarding vector-borne disease and insecticide. The potential impact, applications, and benefits – Malaria affects millions of people each year. Insecticides (bednets or spraying) are one main way to control this disease due to the current lack of vaccine. This project could support understanding of appropriate disease control strategies in African countries by looking at malaria from using a novel network approach. This project falls into the category of Mathematical Biology and also Complexity Science. It aims to develop and apply mathematical techniques in order to investigate biological systems at a population level.
Sep 2019 — Sep 2023
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