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Scientists create new mathematical model to fight malaria

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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.

  In research published today in PLOS Computational Biology, 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.

According to lead author, Associate Professor Jennifer Flegg from University of Melbourne, 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,” he said.

It will be recalled that malaria is a life-threatening disease caused by parasites and spread to humans through infected mosquitos that though preventable and curable, resistance to current antimalarial drugs is causing avoidable loss of life with more than 600,000 in 241 million cases worldwide in 2020, according to  World Health Organisation.

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