COVID-19 is first detected on 12 March 2020 in Turkey, and since that day more than 100 thousand people are infected. In this study, we aim to determine risky provinces in terms of COVID-19 outbreak and also explore the spatial dynamics of the outbreak in Turkey using province-level data. To analyze spatial patterns of COVID-19, we employ spatial dependence statistics Moran-I. Also, we employ Local Indicator Spatial Association-LISA to detect the hot-spots and cold-spots. Moran-I coefficient found as low and statistically significant that shows spatial interaction is not strong in the context of the whole country. Also using LISA, we found Düzce, Kocaeli, Ordu, Tekirda?, and Trabzon as hot-spots for data period, which indicates these cities can be classified as risky in terms of COVID-19 outbreak. There are more spatial interaction with their neighbours cities. In terms of the COVID-19 variable, in hot-spot provinces and neighboring provinces of these provinces, measures should be intensified, and control should be increased.
Real Time Impact Factor:
Pending
Author Name: Fatma Zeren, Veli Yilanci
URL: View PDF
Keywords: COVID-19, spatial autocorrelation, hot-spot, cold spots, Moran I, LISA, Turkey
ISSN: 2651-3234
EISSN: 2651-3307
EOI/DOI: https://doi.org/10.33399/biibf
Add Citation
Views: 1
