One of the major problems in suppressing the spreading of an epidemic resides in understanding and monitoring its propagation patterns, and in evaluating how these are modified by enforced policies. The standard solution requires detailed information at the microscopic scales, e.g. how infected people have moved and whom they came in contact with, which is hardly ever available. The researchers propose a novel approach to the study of the propagation of COVID-19, in which a proxy of this information is derived at macroscopic scales. This will be based on two ingredients: the spatiotemporal study in shiny with mathematical models with aggregated or non aggregated data and the reconstruction of functional networks of spreading patterns, and the development of a supporting software.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
spatiotemporal spread
Timeframe: February 1, 2020 to September 30, 2020