Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters

Database
Language
Document Type
Year range
1.
PLoS One ; 16(8): e0255584, 2021.
Article in English | MEDLINE | ID: covidwho-1341505

ABSTRACT

We apply topological data analysis, specifically the Mapper algorithm, to the U.S. COVID-19 data. The resulting Mapper graphs provide visualizations of the pandemic that are more complete than those supplied by other, more standard methods. They allow for easy comparisons of the features of the pandemic across time and space and encode a variety of geometric features of the data cloud created from geographic information, time progression, and the number of COVID-19 cases. The Mapper graphs reflect the development of the pandemic across all of the U.S. and capture the growth rates as well as the regional prominence of hot-spots.


Subject(s)
Algorithms , COVID-19/transmission , Models, Statistical , COVID-19/epidemiology , Data Analysis , Geographic Mapping , Humans , Pandemics , SARS-CoV-2/physiology , United States/epidemiology
SELECTION OF CITATIONS
SEARCH DETAIL