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Dogs sniff out instant, non-invasive way to diagnose malaria

Sniffer dogs have been trained to detect malaria in children in Africa.

Sniffer dogs could point to better malaria detection. AFP
Sniffer dogs could point to better malaria detection. AFP

Sniffer dogs have been trained to detect malaria in children in Africa, offering a new weapon against the life-threatening disease.

Two dogs trained in Milton Keynes, north of London, were able to identify children in Gambia infected by the malaria parasite after sniffing their socks.

The breakthrough could lead to the first instant and non-invasive diagnostic test for a disease that ­affects millions of people.

James Logan of the London School of Hygiene & Tropical Medicine said: “Our progress on the control of malaria has stalled in recent years. We desperately need new tools. Our results show that sniffer dogs could be a serious way of making diagnoses.”

According to WHO estimates, there were 216 million cases of malaria in 2016, a rise of five million on 2015. Deaths remained stable, at about 445,000 a year.

Research suggests odours produced by chemicals called aldehydes make infected people attractive to the mosquitoes. In the study, apparently healthy children aged between five and 14 in the Gambia wore nylon socks overnight. Using a finger-prick test, the children were screened for the ­malaria parasite.

At the Medical Detection Dogs charity in Milton Keynes, the dogs identified 70 per cent of the ­malaria-infected samples and 90 per cent of the samples without malaria parasites. Researchers believe success rates could rise if the dogs could sniff patients directly.

Steve Lindsay of Durham University, who led the research, said: “This could help prevent the spread of malaria and also ensure that people, many of whom might be unaware that they are infected, receive antimalarial treatment.”

The Times

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Original URL: https://www.theaustralian.com.au/news/world/the-times/dogs-sniff-out-instant-noninvasive-way-to-diagnose-malaria/news-story/8cddab70300f9c28d4f8c5c70bd3bd3e