id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-218324-gqiapgiv	Dlotko, Pawel	Visualising the Evolution of English Covid-19 Cases with Topological Data Analysis Ball Mapper	2020-04-07		.txt	text/plain	3586	179	60	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. Where summary statistics speak of trends, and maps of cases help get a visual handle on the spatial scale, Topological Data Analysis (TDA) after Carlsson (2009) and particularly the Ball Mapper (BM) algorithm of D lotko (2019) can quickly highlight patterns within the characteristics of communities for policy to attend to. This short note, firstly, contributes a first look at how BM produces an abstract two dimensional representation of NUTS3 data and how, by doing so, we can see where in the characteristic space cases are particularly fast rising in terms of number of infections. This contribution to the literature owes much to the pioneering work in combining high, and low, frequency data to marry annually updated regional characteristics with the daily information on Covid-19 cases.	./cache/cord-218324-gqiapgiv.txt	./txt/cord-218324-gqiapgiv.txt