Development of a new tool for...

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Vacancy: Office Assistant – IHI Mtwara site office

IHI is looking for an Office Assistant to fill a vacant position at the IHI Mtwara Site Office. She/he will be responsible for handling all day to day activities of …

Join us for the Innovation Workshop on April 8-19

(Ifakara, Morogoro) If you can develop truly novel approaches to health in Tanzania and beyond, and you’re an inventor or entrepreneur, join us for the 2019 #Innovation Workshop in Ifakara …

Recent Projects

Calcium supplementation on pregnant women

Project summary This is a trial-based study funded by the Bill and Melinda Gates Foundation. It intends to generate evidence for decision-making on the potential non-inferiority of a lower dose …

Sustainable, Healthy, Learning Cities and Neighbourhoods

The Sustainable, Healthy, Learning Cities and Neighbourhoods is an exciting project in which IHI works with a consortium of partners from Asia and Africa to 1) develop capacity for improved …

Malaria transmission is influenced not only by vector abundance, but as well by demographic traits such as vector species and age structure, as these influence the intensity by which the disease is transmitted. Measuring these traits and the susceptibility to insecticide in natural mosquito populations is key to implement vector control strategies. Currently, methods to measure all these traits are expensive and time consuming and cannot be combined to simultaneously measure them in individual mosquitoes. Here we propose to develop a rapid and cost effective tool based on mid-infrared spectroscopy (MIRS) analysis to simultaneously determine these traits in malaria vectors to facilitate large scale surveillance of wild populations. Specifically, we aim to develop this technology to determine:

1- The species and age

2- Insecticide resistance status

The methodology is based on the MIRS measurement of the amount of light absorbed by the mosquito cuticle. As cuticular composition changes during mosquito ageing, differs between species and is influenced by insecticide resistance status, we will use the MIR spectra to predict these traits. Specifically, using computational analysis based on neural networks, we will analyze the complexity of the spectra variations associated with specific traits to make accurate predictions. We will use MIRS to measure different malaria mosquito species with different traits under laboratory settings to develop predictive algorithms; afterwards we will optimize the tool incorporating spectra from natural mosquitoes collected from the field. The development of tool will directly enable the direct integration of this technology into large scale vector surveillance programmes, enabling critically important insights to assist the control of malaria vectors.


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University of Glasgow

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