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Public Lecture: Big Data in Malaria Elimination

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Perdana University

MAEPS Building, MARDI Complex

Jalan MAEPS Perdana

Serdang, Selangor 43400

Malaysia

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Dr. Olivo Miotto

By Dr Olivo Miotto
Senior Informatics Fellow
Mahidol-Oxford Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok;
Centre for Genomics and Global Health, Oxford University, Oxford.

Malaria is one of the most important causes of morbidity and mortality in the developing world. Most of the deaths are in children infected by Plasmodium falciparum, a mosquito-borne protozoan parasite that invades red blood cells. Much progress has been made to reduce the burden of malaria. However, the remarkable adaptive capabilities of P. falciparum constantly undermine the efficacy of antimalarial drugs. Through significant advances in sample processing, it has now become possible to conduct large-scale population genetics studies using WGS data from dried blood spots collected in the most basic endemic settings.

The MalariaGEN P. falciparum Community Project collaborates with dozens of clinical research groups and national malaria control programmes to maintain the world’s largest repository of malaria genetic data. Presently, our global studies use WGS data from nearly 7,000 clinical cases from 4 continents, and this number is rapidly increasing with falling sequencing costs. This dataset has enabled a number of significant advances in P. falciparum genetic epidemiology including the identification of genetic factors associated with resistance to artemisinin and piperaquine.

Genomic data is gradually becoming incorporated in surveillance, control and elimination interventions, but this is not without challenges. It will be important for all public health and research partners to understand which capacities are to be developed in the country, and which to be acquired through partnerships.

For more information on the talk, please visit our website.

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Perdana University

MAEPS Building, MARDI Complex

Jalan MAEPS Perdana

Serdang, Selangor 43400

Malaysia

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