magenta
magenta is an individual-based simulation model of malaria epidemiology and parasite genetics, which was designed to extends the Imperial malaria model by tracking the infection history of individuals. With this addition, genetic characteristics of the parasite can be assessed for looking at both neutral genetic variation as well as loci under selection.
The first and main research paper based on this project was published in MBE1, which showed the extenet to which parasite genetic traits could be used to infer malaria transmission intensity.
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Oliver J Watson, Lucy C Okell, Joel Hellewell, Hannah C Slater, H Juliette T Unwin, Irene Omedo, Philip Bejon, Robert W Snow, Abdisalan M Noor, Kirk Rockett, Christina Hubbart, Joaniter I Nankabirwa, Bryan Greenhouse, Hsiao-Han Chang, Azra C Ghani, Robert Verity, Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling, Molecular Biology and Evolution, Volume 38, Issue 1, January 2021, Pages 274–289, https://doi.org/10.1093/molbev/msaa225 ↩︎
OJ Watson
Imperial College Research Fellow
I am an Imperial College Research Fellow supported by an Eric and Wendy Schmidt AI in Science Fellowship, working within Imperial's new AI Initiative: I-X. My primary focus is as an infectious disease modeller, data scientist, epidemiologist and an R developer. My academic work has focussed on modelling the spread of malaria and COVID-19, based at Imperial College London, Brown University and the London School of Hygiene and Tropical Medicine.