Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland.

Mateusz Ciski, Krzysztof Rząsa
Author Information
  1. Mateusz Ciski: Faculty of Geoengineering, Institute of Spatial Management and Geography, Department of Socio-Economic Geography, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland. ORCID
  2. Krzysztof Rząsa: Faculty of Geoengineering, Institute of Spatial Management and Geography, Department of Socio-Economic Geography, University of Warmia and Mazury in Olsztyn, 10-720 Olsztyn, Poland. ORCID

Abstract

A growing number of various studies focusing on different aspects of the COVID-19 pandemic are emerging as the pandemic continues. Three variables that are most commonly used to describe the course of the COVID-19 pandemic worldwide are the number of confirmed SARS-CoV-2 cases, the number of confirmed COVID-19 deaths, and the number of COVID-19 vaccine doses administered. In this paper, using the multiscale geographically weighted regression, an analysis of the interrelationships between the number of confirmed SARS-CoV-2 cases, the number of confirmed COVID-19 deaths, and the number of COVID-19 vaccine doses administered were conducted. Furthermore, using maps of the local R estimates, it was possible to visualize how the relations between the explanatory variables and the dependent variables vary across the study area. Thus, analysis of the influence of demographic factors described by the age structure and gender breakdown of the population over the course of the COVID-19 pandemic was performed. This allowed the identification of local anomalies in the course of the COVID-19 pandemic. Analyses were carried out for the area of Poland. The results obtained may be useful for local authorities in developing strategies to further counter the pandemic.

Keywords

References

  1. Int J Environ Res Public Health. 2021 Mar 01;18(5): [PMID: 33804558]
  2. Int J Environ Res Public Health. 2022 Jul 28;19(15): [PMID: 35954607]
  3. Vaccines (Basel). 2021 Mar 22;9(3): [PMID: 33810131]
  4. Int J Environ Res Public Health. 2022 Sep 20;19(19): [PMID: 36231184]
  5. Int J Environ Res Public Health. 2020 Aug 17;17(16): [PMID: 32824596]
  6. Int J Environ Res Public Health. 2022 Jul 22;19(15): [PMID: 35897309]
  7. Int J Environ Res Public Health. 2020 Sep 05;17(18): [PMID: 32899495]
  8. Vaccines (Basel). 2023 Apr 05;11(4): [PMID: 37112715]
  9. Int J Environ Res Public Health. 2020 Mar 06;17(5): [PMID: 32155789]
  10. Geohealth. 2021 Aug 04;5(8):e2021GH000423 [PMID: 34377879]
  11. Int J Environ Res Public Health. 2020 Jul 17;17(14): [PMID: 32709002]
  12. Vaccines (Basel). 2021 Oct 28;9(11): [PMID: 34835179]
  13. Int J Environ Res Public Health. 2020 May 02;17(9): [PMID: 32370116]
  14. Int J Environ Res Public Health. 2022 Feb 13;19(4): [PMID: 35206271]
  15. Vaccines (Basel). 2020 Oct 03;8(4): [PMID: 33022917]
  16. Int J Environ Res Public Health. 2020 Jun 17;17(12): [PMID: 32560363]
  17. Vaccines (Basel). 2021 Feb 03;9(2): [PMID: 33546165]
  18. Int J Environ Res Public Health. 2020 Sep 21;17(18): [PMID: 32967091]
  19. Int J Environ Res Public Health. 2020 Apr 26;17(9): [PMID: 32357424]
  20. Int J Environ Res Public Health. 2022 Jun 20;19(12): [PMID: 35742773]
  21. Int J Environ Res Public Health. 2021 Jan 19;18(2): [PMID: 33477825]
  22. Vaccines (Basel). 2021 May 21;9(6): [PMID: 34064028]
  23. Int J Environ Res Public Health. 2020 Sep 10;17(18): [PMID: 32927829]
  24. Geospat Health. 2021 May 11;16(1): [PMID: 34000795]
  25. Lancet. 2021 Dec 4;398(10316):2093-2100 [PMID: 34756184]
  26. City Soc (Wash). 2020 Apr;32(1): [PMID: 32508391]
  27. Int J Environ Res Public Health. 2022 Jan 27;19(3): [PMID: 35162439]
  28. BMJ Open. 2021 Mar 8;11(3):e044067 [PMID: 34006030]
  29. Cities. 2022 Jun;125:103676 [PMID: 35340452]
  30. Int J Environ Res Public Health. 2020 Jul 08;17(14): [PMID: 32650522]
  31. Vaccines (Basel). 2023 Mar 24;11(4): [PMID: 37112635]
  32. PLoS One. 2020 Dec 14;15(12):e0243524 [PMID: 33315880]
  33. Int J Environ Res Public Health. 2021 Jul 29;18(15): [PMID: 34360345]
  34. Vaccines (Basel). 2021 Feb 16;9(2): [PMID: 33669441]
  35. Sustain Cities Soc. 2020 Nov;62:102418 [PMID: 32834939]
  36. Int J Environ Res Public Health. 2020 Jul 02;17(13): [PMID: 32630821]
  37. J Egypt Public Health Assoc. 2021 Jul 5;96(1):18 [PMID: 34224031]
  38. Int J Environ Res Public Health. 2020 Jul 29;17(15): [PMID: 32751311]
  39. Int J Environ Res Public Health. 2020 Jun 22;17(12): [PMID: 32580440]
  40. Int J Environ Res Public Health. 2020 Mar 31;17(7): [PMID: 32244498]
  41. Food Chem Toxicol. 2022 May;163:112949 [PMID: 35337897]
  42. Int J Environ Res Public Health. 2021 Jul 29;18(15): [PMID: 34360301]
  43. Int J Environ Res Public Health. 2022 Nov 21;19(22): [PMID: 36430126]
  44. Int J Environ Res Public Health. 2020 Mar 19;17(6): [PMID: 32204411]
  45. Int J Environ Res Public Health. 2022 Jun 08;19(12): [PMID: 35742285]
  46. J Clin Med. 2020 Feb 17;9(2): [PMID: 32079150]
  47. Trop Med Infect Dis. 2023 Jan 26;8(2): [PMID: 36828501]
  48. City Soc (Wash). 2020 Aug;32(2): [PMID: 32836790]
  49. Int J Environ Res Public Health. 2020 May 25;17(10): [PMID: 32466163]
  50. Int J Environ Res Public Health. 2022 Jun 30;19(13): [PMID: 35805680]
  51. Lancet Infect Dis. 2021 Jun;21(6):793-802 [PMID: 33743847]
  52. Int J Environ Res Public Health. 2021 Mar 08;18(5): [PMID: 33800187]
  53. Int J Environ Res Public Health. 2022 Jul 18;19(14): [PMID: 35886580]
  54. Ecol Inform. 2021 Jul;63:101284 [PMID: 33815029]
  55. Int J Environ Res Public Health. 2022 Jul 23;19(15): [PMID: 35897339]
  56. Int J Environ Res Public Health. 2020 Jun 07;17(11): [PMID: 32517294]
  57. Clin Microbiol Infect. 2022 Feb;28(2):202-221 [PMID: 34715347]
  58. Int J Environ Res Public Health. 2022 Sep 29;19(19): [PMID: 36231717]
  59. Int J Environ Res Public Health. 2020 May 31;17(11): [PMID: 32486380]
  60. J Clin Med. 2020 Mar 31;9(4): [PMID: 32244365]
  61. Int J Environ Res Public Health. 2023 Mar 07;20(6): [PMID: 36981592]
  62. Am J Prev Med. 2020 Sep;59(3):317-325 [PMID: 32703701]
  63. Int J Environ Res Public Health. 2020 Aug 28;17(17): [PMID: 32872154]

MeSH Term

Humans
COVID-19
COVID-19 Vaccines
Poland
Pandemics
SARS-CoV-2
Spatial Regression

Chemicals

COVID-19 Vaccines

Word Cloud

Created with Highcharts 10.0.0COVID-19numberpandemicconfirmedvariablescourseSARS-CoV-2localcasesdeathsvaccinedosesadministeredusingmultiscalegeographicallyweightedregressionanalysisareaPolandgrowingvariousstudiesfocusingdifferentaspectsemergingcontinuesThreecommonlyuseddescribeworldwidepaperinterrelationshipsconductedFurthermoremapsRestimatespossiblevisualizerelationsexplanatorydependentvaryacrossstudyThusinfluencedemographicfactorsdescribedagestructuregenderbreakdownpopulationperformedallowedidentificationanomaliesAnalysescarriedresultsobtainedmayusefulauthoritiesdevelopingstrategiescounterMultiscaleGeographicallyWeightedRegressionInvestigationLocalAnomaliesBasedPopulationAgeStructureGISMGWRgeographicinformationsystem

Similar Articles

Cited By

No available data.