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Place-based factors affecting COVID-19 incidences in Turkey

Author

Listed:
  • Mehmet Ronael

    (Istanbul Technical University)

  • Tüzin Baycan

    (Istanbul Technical University)

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.

Suggested Citation

  • Mehmet Ronael & Tüzin Baycan, 2022. "Place-based factors affecting COVID-19 incidences in Turkey," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1053-1086, October.
    • Handle: RePEc:spr:apjors:v:6:y:2022:i:3:d:10.1007_s41685-022-00257-4
    DOI: 10.1007/s41685-022-00257-4
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    References listed on IDEAS

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    Cited by:

    1. Tüzin Baycan & Suat Tuysuz, 2022. "Special Feature on social, economic, and spatial impacts of COVID-19 pandemic in Turkey," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1041-1051, October.

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    More about this item

    Keywords

    COVID-19 pandemic; Place-based factors affecting pandemic; Geographical dimensions; Ordinary least square regression; Geographically weighted regression; Turkey;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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