Title:
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Modelling the spread of infectious diseases in confined and crowded environments
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The study of infectious diseases and their spreading mechanisms is fundamental to
prevent new infections and limit the eventual death toll. Just as not all diseases
have the same characteristics, not all individuals have the same probability of
contracting the infection and different scenarios lead to different outcomes.
Focusing on the heterogeneity of the populations, we create an interdisciplinary and
novel approach that relax the assumption of well-mixed populations, typical of compartmental
models, by incorporating state-of-the-art results of empirical and analytical
pedestrian studies. By knowing the relationship between crowd density and walking velocity
we are able to devise a density-dependent contact rate allowing us to estimate the
number of contacts between infectious and healthy individuals in crowded and confined
situations.
The advantages of this method are: (i) the ability of getting more realistic solutions
on the number of new infections and (ii) the possibility of studying a scenario a-priori.
This means that just by knowing the size of the population and the extension of the
environment we are able to infer the number of contacts between individuals and,
consequently, the number of new infections.
We apply the method to the London Underground network by using data from
Transport for London (TfL). We firstly devise a transportation model that evaluates
the amount of time passengers spend in each station in order to walk from entrance
to platform and vice-versa. After that we infer the density inside the stations and the
number of contacts between passengers. As a validation we compare the results with
data of infections (reported by general practitioners) in London boroughs and obtain a
clear correlation between the use of public transport and the incidence rate of infections.
Further studies using this new type of modelling could help evaluate and, eventually,
prevent contagion in most crowded environments such as public transport, offices, schools
and hospitals.
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