
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
  <dc:source>Open Geosciences 12(1)</dc:source>
  <dc:creator>Valjarević, Aleksandar</dc:creator>
  <dc:creator>Milić, Marija</dc:creator>
  <dc:creator>Valjarević, Dragana</dc:creator>
  <dc:creator>Stanojević Ristić, Zorica</dc:creator>
  <dc:creator id="https://plus.cobiss.net/cobiss/sr/sr/conor/12464743">Petrović, Ljiljana</dc:creator>
  <dc:creator>Milanović, Miško</dc:creator>
  <dc:creator>Filipović, Dejan</dc:creator>
  <dc:creator>Ristanović, Branko</dc:creator>
  <dc:creator>Basarin, Biljana</dc:creator>
  <dc:creator>Lukić, Tin</dc:creator>
  <dc:identifier>https://phaidrabg.bg.ac.rs/o:29396</dc:identifier>
  <dc:identifier>doi:10.1515/geo-2020-0156</dc:identifier>
  <dc:identifier>ISSN: 2391-5447</dc:identifier>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:description xml:lang="eng">Abstract: In December 2019, the virus SARS-CoV-2
responsible for the COVID-19 pandemic was detected in
the Chinese city of Wuhan. The virus started to spread
from China and dispersed over the rest of the world. In
March 2020, WHO (World Health Organization) declared
COVID-19 a pandemic. The transmission path of the pandemic was accelerated by different types of transportation. With complete analysis of spatial data, population
density, types of traffic networks, and their properties,
the spatial distribution of COVID-19 was estimated. GIS
(Geographical Information System), numerical methods,
and software for network analysis were used in this
research to model scenarios of virus distribution on a
global scale. The analyzed data included air, railway,
marine, and road traffic. In the pandemic research,
numerous models of possible trajectory of viruses can
be created. Many have a stochastic character. This study
includes all countries in the world affected by the COVID19 up to date. In this study, GIS methods such as buffer,
interpolations, and numerical analysis were used in order
to estimate and visualize ongoing COVID-19 pandemic
situation. According to the availability of new data, trajectory of virus paths was estimated. On the other hand,
sparsely populated areas with poorly developed and small
traffic networks (and isolated island territories) tend to be
less or not affected as shown by the model. This low-cost
approach can be used in order to define important measures that need to be addressed and implemented in order
to successfully mitigate the implications of COVID-19 not
only on global, but local and regional scales as well.</dc:description>
  <dc:subject xml:lang="eng">Keywords: COVID-19, GIS, progressions, traffic types, modelling, mapping</dc:subject>
  <dc:date>2020</dc:date>
  <dc:language>eng</dc:language>
  <dc:format>application/pdf</dc:format>
  <dc:format>4562646 bytes</dc:format>
  <dc:title xml:lang="eng">Modelling and mapping of the COVID-19 trajectory and pandemic paths at global scale : A geographer’s perspective</dc:title>
</oai_dc:dc>