Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model Article Swipe
Piotr Werner
,
Małgorzata Kęsik-Brodacka
,
Karolina Nowak
,
Robert Olszewski
,
Mariusz Kaleta
,
David T. Liebers
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/ijgi11030195
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/ijgi11030195
This article describes an original methodology for integrating global SIR-like epidemic models with spatial interaction models, which enables the forecasting of COVID-19 dynamics in Poland through time and space. Mobility level, estimated by the regional population density and distances among inhabitants, was the determining variable in the spatial interaction model. The spatiotemporal diffusion model, which allows the temporal prediction of case counts and the possibility of determining their spatial distribution, made it possible to forecast the dynamics of the COVID-19 pandemic at a regional level in Poland. This model was used to predict incidence in 380 counties in Poland, which represents a much more detailed modeling than NUTS 3 according to the widely used geocoding standard Nomenclature of Territorial Units for Statistics. The research covered the entire territory of Poland in seven weeks of early 2021, just before the start of vaccination in Poland. The results were verified using official epidemiological data collected by sanitary and epidemiological stations. As the conducted analyses show, the application of the approach proposed in the article, integrating epidemiological models with spatial interaction models, especially unconstrained gravity models and destination (attraction) constrained models, leads to obtaining almost 90% of the coefficient of determination, which reflects the quality of the model’s fit with the spatiotemporal distribution of the validation data.
Related Topics
Concepts
Geography
Econometrics
Population
Gravity model of trade
Spatial distribution
Distribution (mathematics)
Spatial analysis
Spatial epidemiology
Geocoding
Coronavirus disease 2019 (COVID-19)
Variable (mathematics)
Statistics
Cartography
Computer science
Mathematics
Epidemiology
Demography
Remote sensing
Medicine
International trade
Infectious disease (medical specialty)
Pathology
Disease
Mathematical analysis
Internal medicine
Business
Sociology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/ijgi11030195
- https://www.mdpi.com/2220-9964/11/3/195/pdf?version=1647922341
- OA Status
- gold
- Cited By
- 12
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221089843
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4221089843Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/ijgi11030195Digital Object Identifier
- Title
-
Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction ModelWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-14Full publication date if available
- Authors
-
Piotr Werner, Małgorzata Kęsik-Brodacka, Karolina Nowak, Robert Olszewski, Mariusz Kaleta, David T. LiebersList of authors in order
- Landing page
-
https://doi.org/10.3390/ijgi11030195Publisher landing page
- PDF URL
-
https://www.mdpi.com/2220-9964/11/3/195/pdf?version=1647922341Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2220-9964/11/3/195/pdf?version=1647922341Direct OA link when available
- Concepts
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Geography, Econometrics, Population, Gravity model of trade, Spatial distribution, Distribution (mathematics), Spatial analysis, Spatial epidemiology, Geocoding, Coronavirus disease 2019 (COVID-19), Variable (mathematics), Statistics, Cartography, Computer science, Mathematics, Epidemiology, Demography, Remote sensing, Medicine, International trade, Infectious disease (medical specialty), Pathology, Disease, Mathematical analysis, Internal medicine, Business, SociologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
12Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 6, 2023: 1, 2022: 4Per-year citation counts (last 5 years)
- References (count)
-
41Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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