The geography of the covid-19 pandemic: A data-driven approach to exploring geographical driving forces

Frederik Seeup Hass, Jamal Jokar Arsanjani*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)
Original languageEnglish
Article number2803
JournalInternational Journal of Environmental Research and Public Health
Volume18
Issue number6
Pages (from-to)1-19
Number of pages19
ISSN1661-7827
DOIs
Publication statusPublished - 2 Mar 2021

Bibliographical note

Funding Information:
Funding: EOSCsecretariat.eu has received funding from the European Union’s Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.”

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • Covid-19 pandemic
  • Machine learning
  • Public health
  • Spatial au-tocorrelation
  • Spatio-temporal analysis
  • COVID-19
  • Geography
  • SARS-CoV-2
  • Pandemics
  • Europe/epidemiology
  • Humans
  • Communicable Disease Control

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