Place-based factors affecting COVID-19 incidences in Turkey

Mehmet Ronael () and Tüzin Baycan
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Mehmet Ronael: Istanbul Technical University
Tüzin Baycan: Istanbul Technical University

Asia-Pacific Journal of Regional Science, 2022, vol. 6, issue 3, No 9, 1053-1086

Abstract: Abstract In December 2019, COVID-19 infections first occurred in Wuhan City, China, after which it rapidly spread throughout the world. Today, COVID-19 has become a major disaster affecting countries physically, socially, and especially economically. However, reasons behind the spread of COVID-19 are still unclear. Therefore, many scholars from different disciplines try to understand the various leading indicators. Our study aimed to reveal place-based factors affecting COVID-19 incidences in Turkey while addressing and analyzing a set of indicators (physical, natural, economic, demographic, and mobility based) within the scope of the recent research findings in the literature on the COVID-19 Pandemic. Following this purpose, we addressed 81 provinces of Turkey using city-level data obtained from the Ministry of Health, and employed global and local regression methods through ArcGIS and GeoDa: Ordinary Least Square, Spatial Lag Model, Spatial Error Model, and Geographically Affected Weighted Regression to highlight place-based factors affecting the spread of the Pandemic. The results of our analyses demonstrated that three factors: (1) population density, (2) annual temperature, and (3) health capacity; are related to the COVID-19 incidences in Turkey. Our results also demonstrated that the impact of these factors causes varying spatial effects within the country, especially in the West–East direction. Although these results provide a base for future studies, COVID-19 is still spreading with several mutations. Therefore, the reliability of produced models and the effectiveness of factors should be retested using new and updated data for cities and at other geographical scales.

Keywords: COVID-19 pandemic; Place-based factors affecting pandemic; Geographical dimensions; Ordinary least square regression; Geographically weighted regression; Turkey (search for similar items in EconPapers)
JEL-codes: C31 C38 C88 R58 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s41685-022-00257-4

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