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Using Big Data to Fight Malaria

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Using Big Data to Fight Malaria

I've written a few times recently about some exciting innovations around infectious disease control: now Big Data joins the fight against malaria.

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Image title The recent past has seen more and more projects apply computer science toward infectious disease control and wellness.

For examples, last year, uMed was launched to provide remote monitoring and diagnostics devices.

The devices, which cost just $25, aim to offer a range of chemical and biochemical tests using a number of commercially available test strips and electrodes. This analysis then produces a range of outputs, which are sent via a cable attached to the headphone jack of a standard mobile phone. The data is sent via the voice channel of any mobile network, so there is not even the need of a data connection.

In addition, A Microsoft-led team are looking to do a similar thing with drones. The project is currently under development in Grenada where the research team are collecting data from various micro-organisms present in the local environment, with the eventual aim being to track mosquitoes and other infectious agents as they travel the world.

Big Data and Malaria

A recent study, which is part of the wider AvecNet project, looked to Big Data to help tackle malaria.

The idea is to capture and analyze terabytes worth of high-res images of mosquitoes from Tanzania to better understand the creatures and therefore develop better protection against them.

Traditionally researchers have only observed mosquitoes as they tackle the various barriers humans set up, such as netting.  Whilst useful, this often provides a limited picture of how the insects approach the nets.

An Observational Brief

The researchers, from the Liverpool School of Tropical Medicine, based themselves in a hut in Tanzania.  The location was chosen because the mosquito population in the country has a strong mix of creatures that are resistant to insecticide and not.

The researchers used advanced cameras and infrared backlighting to capture the insects during the night.  The cameras captured 50 images per second, or 360,000 per hour.

The researchers then teamed up with engineers at the University of Warwick to process this huge database of high-res images.

“There is a lot of interest in the analysis of so-called ‘big data’—here we have the added complexity of capturing information from the field with everything powered from petrol-fueled generators, and we need very robust algorithms to be tolerant of the natural variability in behavior exhibited by wild mosquitoes,” the team say.

The next phase of the research will see the ante upped further, with a further six cameras added to the hut to capture not just the sleeping area but the whole hut.  The aim will be to provide a full picture of how the mosquitoes approach their ‘target’.

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Topics:
internet of things ,big data ,research and analysis

Published at DZone with permission of Adi Gaskell, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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