Modeling and Identifying the foci of the Spread of the Covid-19 virus in Religious Tourism Cities using a Location-Based Model in GIS (Case study: Mashhad Metropolis)

Document Type : Research Article (Applied - Development)

Authors

1 Member of the academic staff of Jihad Academic Research Institute, Mashhad Branch, Razavi Khorasan, Iran.

2 Ferdowsi University of Mashhad, Mashhad, Iran.

10.22103/jusg.2024.2125

Abstract

The Covid-19 epidemic is one of the infectious diseases with a very high prevalence rate, which has led to deep and complex changes in urban spaces. For this purpose, the present article has been carried out with the aim of identifying places with the potential to spread the epidemic of the Covid-19 disease in the city of Mashhad. purpose, the current research is applied research and in terms of method, it is descriptive-analytical and based on spatial analysis. In this study, in order to identify the urban areas that have a high possibility of the spread of the Covid-19 disease, spatial modeling was used based on the location-based model, and spatial data analysis was performed with ArcGIS software. Spatial modeling of the places of outbreak of covid-19 in Mashhad showed that in the central part of Mashhad (areas 1, 2, 3, 6 and 8), especially around the holy shrine of Razavi, the rate of covid-19 is very high. Also, the results of Moran's spatial autocorrelation model showed that at a distance of 1482 meters from the city center, the autocorrelation is positive and strong, and at a distance of 4850 meters, the autocorrelation is positive but weak, which means that the spread of Corona will decrease from this distance.
The spread of the corona virus in religious tourism cities, especially Mashhad metropolis (around the Holy Shrine of Razavi) is high due to the arrival of pilgrims and tourists, which can lead to the spread of this epidemic throughout the country.

Keywords

Main Subjects

Journal of Urban Social Geography

Articles in Press, Accepted Manuscript
Available Online from 12 June 2024

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History

  • Receive Date: 28 May 2023
  • Revise Date: 15 October 2023
  • Accept Date: 04 June 2024

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