Scientists in the UK and Gambia report they have the first evidence that sniffer dogs can smell malaria. They have trained dogs to detect infected people by their socks, even if they show no symptoms. Although research is still in progressis in early stages, scientists hope that trained detection dogs can help prevent the spread of the disease and detect infected people earlier so they can be treated quickly.
"Humans infected with malaria parasites produce odors with their breath and skin that represent specific signals to the animals' sensitive noses," said researcher Prof. Steve Lindsay of Durham University. “This could be a non-invasive method for rapid screening, similar to how sniffer dogs detect drugs at airports.”
McDonald's Germany is launching a vegan burger
McDonald's Germany presents its first vegan burger called "Big Vegan TS". The meat substitute product “Incredible Burger” is produced by Nestlé and consists of soy, wheat, beetroot, peppers and carrots. The veggie burger looks like a classic beef patty.
Socks worn overnight by children from the Upper River region of The Gambia in West Africa have been vacuum packed and shipped to the UK. Of the 175 pairs sent, 30 were worn by children infected with malaria. The results show that the two dogs involved in the experiment correctly detected 70 percent of the malaria-positive socks.
Prof Lindsay said he was "really excited" by the findings so far, but the dogs were not yet ready for routine use. Researchers still need to improve their accuracy, testing them on humans instead of socks, and studying whether the animals can detect different types of malaria.
Malaria is a life-threatening disease caused by parasites. Thepathogensare transmitted to humans by female Anopheles mosquitoes. However, it can be prevented and cured.
According to the World Health Organization's (WHO) latest World Malaria Report, there were an estimated 216 million malaria cases in 2016, an increase of five million cases from the previous year. The number of deaths was around 445,000, similar to the previous year.
