However, current tests do not necessarily detect the infection, particularly at low parasite densities.
Now, an global team of researchers is working toward a way to identify malaria patients, including infected individuals who show no malaria symptoms. DNA tests for the parasite usually show infection, but they are far from rapid.
"Our past work at a mouse model discovered that malaria disease Changed the odours of mice in ways that left them attractive to mosquitoes, especially at a period of disease where the transmissible phase of the parasite was present at elevated levels", said researcher Consuelo De Moraes.
"We also found long-term changes in the odor profiles of infected mice", he adds.
Now, De Moraes and team have investigated whether it is possible to identify changes in human odors associated with malaria infection that may be useful for diagnosis.
Some people who have been infected with malaria but do not any symptoms mostly stay in the heaviest areas of malaria infestation.
Only if the two microscopy and DNA research were negative were issues considered malaria-free.
Because these methods have limited sensitivity, particularly when parasite loads are low, infections were confirmed by DNA tests.
Malaria infects 200 million people worldwide each year, and hundreds of thousands of people die.
As per a study performed by the Penn State, abruptly altered body odour suggests malaria even when the microscope does not.
In some later analyses, the researchers included 77 people who were positive for malaria according to DNA, but showed no parasites in the microscopic tests.Malaria infection does not create new volatile chemicals in the body, but alters the amounts - up or down - of volatile chemicals that are already present in the odors of healthy people.
Malaria infection doesn't produce new volatile compounds from the body but changes the quantities - up or down - of volatile substances which are now within the odours of healthy men and women.
"It is interesting that the symptomatic and asymptomatic infections were different from each other as well as from healthy people", said researcher Mark C. Mescher.
People can eventually result in evaluations capable of quickly and accurately identifying infected men and women, even people without symptoms. "Furthermore, we found that predictive models based on machine learning algorithms reliably determined infection status based on volatile biomarkers and, critically, identified asymptomatic infections with 100% sensitivity, even in the case of low-level infections not detectable by microscopy". Their results far exceed those of the rapid diagnostic tests that are now available.
In the near term, our goal is to refine the current findings to find the most reliable and effective biomarkers we can. "There is still a lot more work to be done to develop a practical diagnostic assay".