Researchers at Pennsylvania State University (Penn State) in the US have conducted a new study which is attempting to develop an approach to identify people infected with malaria, including asymptomatic patients.

Existing blood tests are said to lack the ability to detect low densities of the plasmodium parasite infection, while DNA tests are not rapid.

Discover B2B Marketing That Performs

Combine business intelligence and editorial excellence to reach engaged professionals across 36 leading media platforms.

Find out more

Previous research by the team in mouse models showed that malaria infection altered the odours of infected mice, making them more attractive to mosquitoes, especially when the transmissible stage of the parasite was high.

“The researchers developed machine learning-based predictive models to reliably detect the infection based on volatile biomarkers.”

The latest study aimed to investigate these findings in humans in order to determine a new diagnostic method, particularly for individuals who were infected but did not have any symptoms.

Initially, microscopy and an SD Bioline Rapid Diagnostic Test were used to identify infected patients. The researchers also used DNA tests to confirm the results as the initial tests have limited sensitivity.

After identifying both microscopy and DNA positive patients among a total of 333 participants, the study recruited an additional 77 subjects who were found to be positive based on DNA, but did not display any parasites in the microscopic tests.

GlobalData Strategic Intelligence

US Tariffs are shifting - will you react or anticipate?

Don’t let policy changes catch you off guard. Stay proactive with real-time data and expert analysis.

By GlobalData

It was observed that the symptomatic and asymptomatic patients were different from each other and from healthy people.

While malaria infection does not generate new volatile chemicals in the body, it alters the levels that exist in the odours of healthy individuals.

The researchers then developed machine learning-based predictive models to reliably detect the infection based on volatile biomarkers.

When tested, the models said to have demonstrated 100% sensitivity in identifying asymptomatic infections, even at low levels that could not be detected with microscopy.

Penn State biology adjunct professor Mark Mescher said: “In the near term, our goal is to refine the current findings to find the most reliable and effective biomarkers we can.

“This is really basic science to identify the biomarkers of malaria. There is still a lot more work to be done to develop a practical diagnostic assay.”

Medical Device Network Excellence Awards - Nominations Closed

Nominations are now closed for the Medical Device Network Excellence Awards. A big thanks to all the organisations that entered – your response has been outstanding, showcasing exceptional innovation, leadership, and impact

Excellence in Action
Awarded for Innovation in Remote Hearing Diagnostics , hearX’s Self Test Kit (STK) delivers clinically validated audiometry via smart devices, enabling remote, scalable hearing assessments in homes, clinics and retail. Learn how hearX is redefining hearing care delivery and reducing costs for providers globally.

Discover the Impact