About: Visualising the Evolution of English Covid-19 Cases with Topological Data Analysis Ball Mapper

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Visualising the Evolution of English Covid-19 Cases with Topological Data Analysis Ball Mapper
Creator	Dlotko, Pawel Rudkin, Simon
source	ArXiv
abstract	Understanding disease spread through data visualisation has concentrated on trends and maps. Whilst these are helpful, they neglect important multi-dimensional interactions between characteristics of communities. Using the Topological Data Analysis Ball Mapper algorithm we construct an abstract representation of NUTS3 level economic data, overlaying onto it the confirmed cases of Covid-19 in England. In so doing we may understand how the disease spreads on different socio-economical dimensions. It is observed that some areas of the characteristic space have quickly raced to the highest levels of infection, while others close by in the characteristic space, do not show large infection growth. Likewise, we see patterns emerging in very different areas that command more monitoring. A strong contribution for Topological Data Analysis, and the Ball Mapper algorithm especially, in comprehending dynamic epidemic data is signposted.
has issue date	2020-04-07(xsd:dateTime)
has license	arxiv
sha1sum (hex)	4d19ca3b426c1864ac9d5bc719e47977c352e981
resource representing a document's title	Visualising the Evolution of English Covid-19 Cases with Topological Data Analysis Ball Mapper
resource representing a document's body	covid:4d19ca3b426c1864ac9d5bc719e47977c352e981#body_text
is schema:about of	named entity 'helpful' named entity 'concentrated' named entity 'English' named entity 'Topological Data Analysis' named entity 'ABSTRACT' »more»

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