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2016

Ecology of insecticide resistant vectors : consequences for the effectiveness of malaria control strategies

Burkina Faso

Department for International Development UKAID

Titre : Ecology of insecticide resistant vectors : consequences for the effectiveness of malaria control strategies

Pays : Burkina Faso

Numéro du projet : GB-GOV-13-FUND—GCRF-MR_N015320_1

Organismes de mise en œuvre : University of Glasgow

Durée : Actual Start 01 Jul 2016 // 30 Jun 2019

Présentation partielle
This fellowship is driven by one of the most prominent challenges in the fight against malaria : increasing levels of insecticide resistance (IR) in malaria mosquitoes across sub-Saharan Africa. IR has the potential to threaten the effectiveness of insecticides implemented in long-lasting treated bednets (known as LLIN), the most widespread control strategy currently available for malaria. Despite the gravity of this impending threat, the extent of IR and its consequences for public health remain poorly understood. A fundamental assumption in this debate is that resistant mosquitoes are identical to susceptible ones in all aspects other than their response to insecticides. However, variation in basic ecological features between mosquito species such as life-history traits, behaviour and reproductive success may allow insecticide-based control methods to retain a higher than expected degree of efficacy, even in areas where IR levels are high. Unfortunately, these parameters are difficult to directly measure under natural field conditions, and may be poorly reflected in laboratory bioassays. However, recent developments in ecological modelling offer an innovative approach for deriving this type of information from the types of data that are routinely collected in vector surveillance. I propose to use a state-space modelling (SSM) approach to investigate the population dynamics and ecology of malaria vectors in an area of high IR, and to quantify the impacts of both traditional and novel control methods on mosquito life history under field operational conditions. I will focus on the Banfora district of Burkina Faso, a region of high IR, and will make use of mosquito surveillance data, including vector abundance,

Financement : UK - Department for Business, Energy and Industrial Strategy
Project budget : £268,742

Présentation (UKAID)

Page publiée le 30 octobre 2022