COVID-19 pandemisinin nüfus hareketliliği üzerine etkisi: Hareketlilik ve gelir arasındaki ilişkinin analizi

Abstract

Bu çalışma COVID-19 pandemisinde nüfus hareketliliği ve gelir arasındaki ilişkiyi konu alır. Bu

bağlamda araştırmada gelirin pandemi sürecinde yaşanan hareketlilikte belirleyici olup olmadığı

sorusuna yanıt aranmıştır. Çalışma nicel veri toplama ve analiz araçlarından faydalanılarak

tasarlanmıştır. Hareketlilikte yaşanan değişimin analizinde Google tarafından sunulan altı farklı

kategoriye ilişkin hareketlilik verileri ile Türkiye İstatistik Kurumu (TÜİK) tarafından yayınlanan

gelir verilerinden faydalanılmıştır. Hareketlilik verileri mekânsal otokorelasyon, hareketlilik ve

gelir arasındaki ilişki ise korelasyon analizi kullanarak çözümlenmiştir. Araştırmanın temel bulguları

şu şekildedir: Perakende ve rekreasyon, park ve toplu taşıma kategorilerinde nüfusun

hareketliliği değerlendirmeye alınan dönemde azalmıştır. Buna karşın market ve eczane ile konut

kategorilerinde yaşanan hareketlilik artmıştır. Korelasyon analizi sonuçlarına göre ise perakende

ve rekreasyon, market ve eczane, işyeri ve konut kategorilerinde gelir ve hareketlilik

arasında ilişki bulunur. Gelirin fazla olduğu illerde perakende ve rekreasyon, merkez ve eczane

ile işyerinde yaşanan hareketlilik daha fazla azalmıştır. Gelirin düşük olduğu illerde ise konutta

geçirilen hareketlilik azalmaktadır. Park ve toplu taşıma kategorilerinde yaşanan hareketlilik ile

gelir arasında pozitif ilişki bulunduğu tespit edilmiştir. Bununla birlikte bu ilişki istatistiksel olarak

anlamlı değildir.

Keywords

• COVID-19
• Nüfus hareketliliği
• Gelir
• Yoksulluk
• Google Hareketlilik Raporları

Impact of COVID-19 pandemic on population mobility: Analysis of the relationship between mobility and income

Abstract

This study seeks to explore the relationship between population mobility and income in the
COVID-19 pandemic. In this context, it was questioned in the research whether income is a determinant
in the mobility experienced during the pandemic process. The study was designed
using quantitative data collection and analysis tools. In the analysis of the change in mobility,
the mobility data for six different categories prepared by Google and the income data published
by the Turkish Statistical Institute were used. Mobility data were analyzed using spatial
autocorrelation, and the relationship between mobility and income was analyzed using correlation
analysis. The main results of the study are as follows: The mobility of the population in
the categories of retail and recreation, parks and public transport decreased during the period
that analyzed in this research. On the other hand, the activity in the market, pharmacy and
housing categories increased. According to the results of the correlation analysis, there is a relationship
between income and mobility in the categories of retail and recreation, market and
pharmacy, workplace and housing. In provinces with high income, the mobility experienced in
retail and recreation, center, pharmacy and workplace decreased more. On the other hand, in
provinces with low income, mobility in housing decreases. It has been determined that there is
a positive relationship between the mobility experienced in the park and public transportation
categories and income. However, this relationship is not statistically significant.

Keywords

• COVID-19
• Population mobility
• Income
• Poverty
• Google mobility reports

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