arXiv 7 Apr 2020 · physics.soc-ph · 4 citations (OpenAlex)
arXiv:2004.03282 · PDF · DOI · OpenAlex · Extracted main text
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.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Adda, J (2016) Economic activity and the spread of viral diseases: Evidence from high frequency data | 0.511 | 2 | 1 | 100% |
| 2 | Barnay, T (2016) Health, work and working conditions: a review of the european economic literature | 0.405 | 1 | 1 | 100% |
| 3 | Böckerman, P., Johansson, E., Helakorpi, S., and Uutela, A (2009) Economic inequality and population health: looking beyond aggregate indicators | 0.405 | 1 | 1 | 100% |
| 4 | Carlsson, G (2009) Topology and data | 0.405 | 1 | 1 | 100% |
| 5 | Dlotko, P (2019) BallMapper: Create a Ball Mapper graph of the input data self | 0.405 | 1 | 1 | 100% |
| 6 | Dotko, P (2019) Ball mapper: a shape summary for topological data analysis | 0.405 | 1 | 1 | 100% |
| 7 | Eichenbaum, M. S., Rebelo, S., and Trabandt, M (2020) The macroeconomics of epidemics | 0.405 | 1 | 1 | 100% |
| 8 | Jones, K. E., Patel, N. G., Levy, M. A., Storeygard, A., Balk, D., G… (2008) Global trends in emerging infectious diseases | 0.405 | 1 | 1 | 100% |
| 9 | Linderman, G. C., Rachh, M., Hoskins, J. G., Steinerberger, S., and… (2019) Fast interpolation-based t-sne for improved visualization of single-cell rna-seq data | 0.405 | 1 | 1 | 100% |
| 10 | Maaten, L. v. d. and Hinton, G (2008) Visualizing data using t-sne | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 13 scored citations.