Geography and Human Relationships

Geography and Human Relationships

Studying the spatial distribution of the covid-19 virus with the methods of measuring geographical statistical functions in the GIS environment, case: Khoy city neighborhoods

Document Type : thesis

Authors
1 Department of Geography & Rural Planning, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran.
2 PhD student in Geography and Urban Planning, University of Mohaghegh Ardabili, Ardabil, Iran
10.22034/gahr.2024.452667.2095
Abstract
Improving the knowledge of dealing with crises that threaten human life can ensure the resilience of the human generation. The continued spread of the covid-19 virus has affected Iran's national health systems as well as other health systems around the world. The covid-19 pandemic created a form of socio-economic and especially spatial inequality and ultimately health inequality. The public health system of Khoy cities in West Azerbaijan province was also affected by the spread of this virus and reported its first case of infection and death on April 30, 2019, and recorded 530 deaths. Today he is fighting this virus. Using the descriptive-analytical method, this research studied the spatial distribution of the covid-19 virus in 62 neighborhoods of city Khoy from the beginning of 2019 to the end of 2012 using geographic information system. The purpose of this research is to use geographic measurement methods to analyze the spatial distribution of the Covid-19 virus based on the spatial diffusion theory. The findings of the research showed that the range of distribution is concentrated in the western neighborhoods of Khoy city with high population density and the oval elongation of the distribution with a relative north-south direction, and unequal factors are effective and evident in enjoying stable health. The mechanism of the spatial spread of the Covid-19 virus in Khoy areas is relatively compatible with some of the steps and the mechanism of the spatial spread theory, and some of the steps are generally disused in this field.
Keywords

Subjects


1-بازرگان, مهدی, 2-امیرفخریان, مصطفی. (1401). تحلیل جغرافیایی اپیدمیولوژی کووید-19 در ایران با رویکرد تحلیل اکتشافی داده های مکانی (ESDA). طب نظامی. 22(6), 542-552.        doi: 10:30491/jmm.22.6.542
2-مهردانش, گونا,آزادی زاده, نامدار. (1399). موضوع :مفهوم تاب آوری شهری مدیریت و برنامه ریزی آینده شهرها (کرونا 19)، جغرافیا و روابط انسانی. 3(1), 132-16، doi: 10.22034/gahr.2020.109955
3-Ahasan R, Alam MS, Chakraborty T, Hossain MM. Applications of GIS and geospatial analyses in COVID-19 research: A systematic review. F1000Res. 2022 Jan 28; 9:1379. doi: 10.12688/f1000research.27544.2. PMCID: PMC8822139.
4-Samany, N.N., Liu, H., Aghataher, R. et al. Ten GIS-Based Solutions for Managing and Controlling COVID-19 Pandemic Outbreak. SN COMPUT. SCI. 3, 269 (2022). https://doi.org/10.1007/s42979-022-01150-95-Cascella M, Rajnik M, Aleem A, et al. Features, Evaluation, and Treatment of Coronavirus (COVID-19) [Updated 2023 Aug 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK554776/
6-Chen ZL, Zhang Q, Lu Y, Guo ZM, Zhang X, Zhang WJ, Guo C, Liao CH, Li QL, Han XH, Lu JH. Distribution of the COVID-19 epidemic and correlation with population emigration from Wuhan, China. Chin Med J (Engl). 2020 May 5;133(9):1044-1050. doi: 10.1097/CM9.0000000000000782. PMID: 32118644; PMCID: PMC7147281.
7-Ghosh P, Cartone A. A Spatiotemporal analysis of COVID19 outbreak in Italy. Regional Science Policy & Practice. 2020 Dec;12(6):1047–62. doi: 10.1111/rsp3.12376. Epub 2020 Dec 9. PMCID: PMC7753657.
8-Isazade, V., Qasimi, A.B., Dong, P. et al. Integration of Moran’s I, geographically weighted regression (GWR), and ordinary least square (OLS) models in spatiotemporal modeling of COVID-19 outbreak in Qom and Mazandaran Provinces, Iran. Model. Earth Syst. Environ. 9, 3923–3937 (2023). https://doi.org/10.1007/s40808-023-01729-y
9-Hu, N., Zhang, Z., Duffield, N. et al. Geographical and temporal weighted regression: examining spatial variations of COVID-19 mortality pattern using mobility and multi-source data. Comput.Urban Sci. 4, 6 (2024). https://doi.org/10.1007/s43762-024-00117-1
10-Hu, N., Zhang, Z., Duffield, N. et al. Geographical and temporal weighted regression: examining spatial variations of COVID-19 mortality pattern using mobility and multi-source data. Comput.Urban Sci. 4, 6 (2024). https://doi.org/10.1007/s43762-024-00117-1
11-Kopczewska, K. Spatial machine learning: new opportunities for regional science. Ann Reg Sci 68, 713–755 (2022). https://doi.org/10.1007/s00168-021-01101-x
12-Kuhn, H. W., &. Kuenne, R. E. (1962). An efficient algorithm for the numerical solution of the Generalized Weber Problem in spatial economics. Journal of Regional Science, 4(2):21-33.
13-Esra Ozdenerol,  2023, The Role of GIS in COVID-19 Management and Control, ISBN 9781032129754 310 Pages 29 Color & 75 B/W Illustrations, Published May 4, 2023 by CRC Press

14-Mohammadihamidi s, Fürst C, Nazmfar H, Ghayehbashi AR, Anwar MM. The Spatial Diffusion of COVID -19 in the World: Revisiting Hägerstrand's Study of Diffusion in Geography. Research Square; 2021. DOI: 10.21203/rs.3.rs-632320/v1.

 
 
Volume 8, Issue 4 - Serial Number 32
Winter 2026
Pages 203-222

  • Receive Date 15 April 2024
  • Revise Date 09 May 2024
  • Accept Date 31 May 2024