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Title: Numerical schemes and algorithms for branching processes in modelling Coronavirus (COVID19) pandemics Authors:  Maroussia Slavtchova-Bojkova - Sofia University (Bulgaria) [presenting]
Abstract: A new simulation methodology oriented to model the spread of the COVID19 pandemic caused by SARS-CoV-2 coronavirus is developed. There are many complications when modelling an outbreak of a novel infectious disease. To address some of these, we have described a possible technique to serve as part of a generally applicable toolkit. The mutual concern of estimation and simulation efforts is critical. Our methodology is based on the general branching models, which turned out to be more appropriate and flexible for describing the spread of an infection in a given population, than discrete-time ones. Concretely, Crump-Mode-Jagers branching processes are considered as proper candidates of infectious diseases modelling with incubation period like measles, mumps, avian flu, etc. and including the newly immerged COVID19 pandemic, as well. It can be pointed out that the developed methodology applies to the diseases that follow the so-called SIR (susceptible-infected-removed) and SEIR (susceptible exposed-infected-removed) scheme in terms of epidemiological models. Different forecasts are proposed and compared on the ground of real data and simulation examples.