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spelling ftsmithonian:oai:figshare.com:article/14477374 2023-05-15T16:47:40+02:00 Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland. Dan Wu (5969) Pól Mac Aonghusa (10692811) Donal F. O’Shea (1433989) 2021-04-23T17:45:34Z https://doi.org/10.1371/journal.pone.0250699.g001 unknown https://figshare.com/articles/figure/Epidemic_profile_lines_for_Ireland_Germany_UK_South_Korea_and_Iceland_/14477374 doi:10.1371/journal.pone.0250699.g001 CC BY 4.0 CC-BY Medicine Biotechnology Ecology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified population scale interventions COVID -19 testing regimes 57- day period infection numbers COVID -19 outbreak HCW infection data time series UK decline infection numbers testing programs Time analysis epidemic line profile healthcare workers COVID -19 infect. disease progression Image Figure 2021 ftsmithonian https://doi.org/10.1371/journal.pone.0250699.g001 2021-05-05T17:36:10Z Plots of five-day averaged confirmed COVID-19 infections as a best-fit smooth epidemic profile line. Still Image Iceland Unknown
institution Open Polar
collection Unknown
op_collection_id ftsmithonian
language unknown
topic Medicine
Biotechnology
Ecology
Infectious Diseases
Computational Biology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
population scale interventions
COVID -19 testing regimes
57- day period
infection numbers
COVID -19 outbreak
HCW
infection data
time series
UK
decline infection numbers
testing programs Time analysis
epidemic line profile
healthcare workers COVID -19 infect.
disease progression
spellingShingle Medicine
Biotechnology
Ecology
Infectious Diseases
Computational Biology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
population scale interventions
COVID -19 testing regimes
57- day period
infection numbers
COVID -19 outbreak
HCW
infection data
time series
UK
decline infection numbers
testing programs Time analysis
epidemic line profile
healthcare workers COVID -19 infect.
disease progression
Dan Wu (5969)
Pól Mac Aonghusa (10692811)
Donal F. O’Shea (1433989)
Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland.
topic_facet Medicine
Biotechnology
Ecology
Infectious Diseases
Computational Biology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
population scale interventions
COVID -19 testing regimes
57- day period
infection numbers
COVID -19 outbreak
HCW
infection data
time series
UK
decline infection numbers
testing programs Time analysis
epidemic line profile
healthcare workers COVID -19 infect.
disease progression
description Plots of five-day averaged confirmed COVID-19 infections as a best-fit smooth epidemic profile line.
format Still Image
author Dan Wu (5969)
Pól Mac Aonghusa (10692811)
Donal F. O’Shea (1433989)
author_facet Dan Wu (5969)
Pól Mac Aonghusa (10692811)
Donal F. O’Shea (1433989)
author_sort Dan Wu (5969)
title Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland.
title_short Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland.
title_full Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland.
title_fullStr Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland.
title_full_unstemmed Epidemic profile lines for Ireland, Germany, UK, South Korea and Iceland.
title_sort epidemic profile lines for ireland, germany, uk, south korea and iceland.
publishDate 2021
url https://doi.org/10.1371/journal.pone.0250699.g001
genre Iceland
genre_facet Iceland
op_relation https://figshare.com/articles/figure/Epidemic_profile_lines_for_Ireland_Germany_UK_South_Korea_and_Iceland_/14477374
doi:10.1371/journal.pone.0250699.g001
op_rights CC BY 4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.1371/journal.pone.0250699.g001
_version_ 1766037750881976320