When it comes to advancing science, Marianne Sinka has some skin in the game. Some itchy skin.
The Oxford University entomologist has regularly sacrificed her flesh (and blood) as mosquito bait to further her research. Now she's using AI to track the irksome insects and battle the deadly diseases they carry.
"Today, the best way to detect what species are in a place is to sit down, roll up your trousers, and see what mosquitoes bite you," Sinka said. "There are obviously some issues with that."
Instead, Sinka and a group of other Oxford researchers are using cheap mobile phones and GPU-accelerated deep learning to detect mosquitoes. They also want to determine whether the bugs belong to a species that transmits malaria or other life-threatening illnesses.
The goal is to help cash-strapped governments in the regions where malaria is rampant know where and when to deploy insecticides, vaccinations and other actions to prevent disease.
Few creatures are as hated as mosquitoes, and with good reason: They're the world's deadliest animals, killing more people than tigers, snakes, sharks and wolves put together. The blood-sucking insects carry many life-threatening illnesses, including malaria, the Zika virus, dengue and yellow fever.
In 2016, malaria alone infected more than 200 million people -- 90 percent of them in Africa -- and killed some 445,000, according to the World Health Organization. UNICEF reports that most these deaths occured in children less than five years old.
Among some 3,500 species of mosquitoes, only 75 can infect people with malaria, and of these, about 40 are considered the primary carriers of the parasite that causes the disease. To identify mosquito species today, researchers capture the insects (either with human lures or costly light traps) and examine them under the microscope.
For some important species, they must then use molecular methods, such as examining the mosquito's DNA to ensure an accurate identification. These methods can be costly and time-consuming, Sinka said.
Catching a Buzz
Instead of getting up close with the vexatious vermin, the researchers put a smartphone with a sound-sensing app within biting range. Like people, animals and machines the bugs have a unique sound signature.
"It's those distinctive buzzing tones we all hate from mosquitoes," said Ivan Kiskin, an Oxford doctoral student with expertise in signal processing who is working on the mosquito project. The project, dubbed Humbug, is a partnership between Oxford University and London's Kew Gardens.
Researchers are using recordings of captured mosquitoes and NVIDIA GPUs to train a neural network to recognize wing noise. So far, the deep learning-based software reports the likelihood that the buzzing comes from furiously flapping mosquito wings, which beat up to 1000 times a second. In numerous tests, the algorithms have outperformed human experts.
Humbug researchers are beginning to distinguish species as well, Kiskin said. But further progress is stymied by the need for additional training data, he added.
To collect more sound, the team is deploying mobile phones to research groups around the world. In addition, researchers developed an Android app called MozzWear to enlist help from ordinary people. MozzWear will record mosquito buzzing, along with the time and location -- data that users can send to the citizen science web portal, Zooniverse.
"Malaria is a disease of the poor," said Sinka, the bug expert. Although the disease is present in developed countries, it's more common in regions where people live near their livestock and are often too poor to afford air conditioning, window screens or even protective netting to drape over beds.
"Ultimately, we could use our best algorithm and the phones to map malaria prevalence over a region or country," Kiskin said. "Then we could tackle malaria by targeting aid to places in need."