CoLabo at 2: looking for a postdoc to work on genetic-epi models using data from a real-life outbreak simulator

Video of OO presentation at AI4PAN
Diagram describing the stages in our proposed modeling platform: live simulations, generation of ground-truth data, construction of predictive models, validation of models during the live simulations.
Each “player” in the OO simulation (1a) will be assigned an individual-level model of viral kinetics (1b), which will determine their infectivity during the outbreak. The transmission network (2), generated in real-time during the simulation will result in a time tree (3) that will be used to calculate coalescence times in the intra-host models of sequence evolution (4–5).

Increasing awareness of the importance to integrate within- and between-host scales has led to the development of models that explicitly link the two scales. These models, often referred to as ‘multi-scale’ models, have increased in popularity in recent years. While there have been exciting advances made in this area, most studies linking within- and between-host scales are conceptual or theoretical with mainly qualitative and little quantitative support from data. Progress towards a predictive multi-scale framework will require a more precise, quantitative understanding of how infection dynamics, pathogen load, target cell depletion, immunology, symptomatology and other clinical features combine to shape pathogen transmission fitness at the population level.

Members of CoLabo at the New England aquarium, earlier in the Spring



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