Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model
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 inhabi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/11/3/195 |
| _version_ | 1797471101514678272 |
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| author | Piotr A. Werner Małgorzata Kęsik-Brodacka Karolina Nowak Robert Olszewski Mariusz Kaleta David T. Liebers |
| author_facet | Piotr A. Werner Małgorzata Kęsik-Brodacka Karolina Nowak Robert Olszewski Mariusz Kaleta David T. Liebers |
| author_sort | Piotr A. Werner |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T19:44:47Z |
| format | Article |
| id | doaj.art-cb9ce19fff3748a1a2bd72bc0724fcf1 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-09T19:44:47Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-cb9ce19fff3748a1a2bd72bc0724fcf12023-11-24T01:28:40ZengMDPI AGISPRS International Journal of Geo-Information2220-99642022-03-0111319510.3390/ijgi11030195Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction ModelPiotr A. Werner0Małgorzata Kęsik-Brodacka1Karolina Nowak2Robert Olszewski3Mariusz Kaleta4David T. Liebers5Faculty of Geography and Regional Studies, University of Warsaw, 00-927 Warsaw, PolandNational Medicines Institute, 00-700 Warsaw, PolandDepartment of Applied Pharmacy, Faculty of Pharmacy with Laboratory Medicine, Medical University of Warsaw, 02-097 Warsaw, PolandFaculty of Geodesy and Cartography, Warsaw University of Technology, 00-661 Warsaw, PolandFaculty of Electronics and Information Technology, Warsaw University of Technology, 00-665 Warsaw, PolandDepartment of Psychiatry, New York University Langone Medical Center, New York, NY 10016, USAThis 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.https://www.mdpi.com/2220-9964/11/3/195spatial interaction modelspatial modelingCOVID-19spatio-temporal patterns |
| spellingShingle | Piotr A. Werner Małgorzata Kęsik-Brodacka Karolina Nowak Robert Olszewski Mariusz Kaleta David T. Liebers Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model ISPRS International Journal of Geo-Information spatial interaction model spatial modeling COVID-19 spatio-temporal patterns |
| title | Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model |
| title_full | Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model |
| title_fullStr | Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model |
| title_full_unstemmed | Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model |
| title_short | Modeling the Spatial and Temporal Spread of COVID-19 in Poland Based on a Spatial Interaction Model |
| title_sort | modeling the spatial and temporal spread of covid 19 in poland based on a spatial interaction model |
| topic | spatial interaction model spatial modeling COVID-19 spatio-temporal patterns |
| url | https://www.mdpi.com/2220-9964/11/3/195 |
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