Development of a new tool for...

In the News

Laboratory technician is required

Ifakara Health Institute (IHI) is looking for a laboratory technician to work with NC. TB – DAR project in Bagamoyo.The candidate will perform routine experimental laboratory test- mainly in the …

Field Supervisors required

IHI is looking for Field supervisors to fill a vacant positions in a new project on “Calcium supplementation in pregnant women” The Field supervisor will supervise all field activities at …

Recent Projects

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 …

Demonstrating complete disruption of residual malaria transmission by eliminating Anopheles funestus mosquitoes from rural Tanzanian villages

In rural south-eastern Tanzania, where malaria prevalence has reduced by >60% since 2000, low-to-moderate transmission still persists despite very high coverage with long-lasting insecticidal bednets. Like in most residual transmission …

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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