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Researchers have created a mathematical model to predict genetic resistance to antimalarial drugs in Africa to manage one of the biggest threats to global malarial control.

Medical Center in Conakry, Guinea © Dominic Chavez, World Bank

Malaria is a life-threatening disease caused by parasites and spread to humans through infected mosquitos. It is preventable and curable, yet resistance to current antimalarial drugs is causing avoidable loss of life. The World Health Organisation estimated there were 241 million cases of malaria worldwide in 2020, with more than 600,000 deaths.

In research published today in PLOS Computational Biology(link is external), an international research team used data from the WorldWide Antimalarial Resistance Network (WWARN), a global, scientifically independent collaboration, to map the prevalence of genetic markers that indicate resistance to Plasmodium falciparum – the parasite that causes malaria.

Lead author Associate Professor Jennifer Flegg from the University of Melbourne said malaria has devastating impacts on lower-income countries and effective treatment is key to elimination.

“The antimalarial drug sulfadoxine-pyrimethamine (SP) is commonly used in various preventative malaria treatment programs in Africa, particularly for infants, young children and during pregnancy. But we know its efficacy as a treatment is threatened in areas where resistance to SP is high,” Associate Professor Flegg said.

“The statistical mapping tool we have developed is critical for health organisations to understand the spread of antimalarial resistance. The model takes in the data that is available and fills in the gaps by making continuous predictions in space and time.

“Health agencies can use this tool to understand when and where SP is appropriate to use as part preventive malaria treatments and where other antimalarial methods may need to be explored.”

Read the full story on the The Infectious Diseases Data Observatory (IDDO) website. 

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