Araştırma Makalesi
Yıl 2020,
Cilt: 4 Sayı: 2, 27 - 40, 28.12.2020
Öz
Türkiye'de COVID-19 ilk olarak 12 Mart 2020'de tespit edildi ve o günden bu yana 100 binden fazla kişiye bulaştı. Bu çalışmada hem COVID-19 salgını açısından riskli illeri belirlemeyi hem de il bazındaki verileri kullanarak Türkiye'deki salgının mekansal dinamiklerini keşfetmeyi hedefliyoruz. COVID-19' un mekansal yapısını ortaya çıkarmak amacıyla mekansal bağımlılık istatistiklerinden Moran-I istatistiği kullanılmıştır. Ayrıca, “hot point” ve “cold point” alanları belirlemek amacıyla mekansal etkileşim istatistiklerinden Lokal Moran I-LISA istatistiği kullanılmıştır. İstatistiksel olarak anlamlı bulunan Moran I katsayısı tüm ülke bağlamında mekansal etkileşimin güçlü olmadığını göstermektedir. LISA istatistiğine göre ise Düzce, Kocaeli, Ordu, Tekirdağ ve Trabzon illeri veri dönemi için “hot point”alanındaki şehirlerdir. Yani bu şehirlerin COVID-19 salgını açısından en riskli alanlardır ve komşu şehirlerle daha fazla mekansal etkileşimleri bulunmaktadır. COVID-19 değişkeni açısından, “hot point” şehirler ve onların komşularında tedbirler yoğunlaştırılmalı ve kontrol artırılmalıdır.
Kaynakça
- Al-Ahmadi, K., & Al-Zahrani, A. (2013). Spatial autocorrelation of cancer incidence in Saudi Arabia. International Journal of Environmental Research and Public Health, 10(12), 7207-7228.
- Anselin L. (1988) Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, Dordrecht
- Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical analysis, 27(2), 93-115.
- Baud, D., Qi, X., Nielsen-Saines, K., Musso, D., Pomar, L., & Favre, G. (2020). Real estimates of mortality following COVID-19 infection. The Lancet Infectious Diseases, 20(7), https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30195-X/fulltext?fbclid=IwAR2V4jsykeM-R5lsAjcksGvmw4zYCutcVqLd9btqQkIsldVRoNedkBKDMNs
- Bhunia, G. S., Kesari, S., Chatterjee, N., Kumar, V., & Das, P. (2013). Spatial and temporal variation and hotspot detection of kala-azar disease in Vaishali district (Bihar), India. BMC Infectious Diseases, 13(1), 1-12.
- Chaikaew, N., Tripathi, N. K., & Souris, M. (2009). Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand. International Journal of Health Geographics, 8(1), 36.
- Chan-Yeung, M., & Xu, R. H. (2003). SARS: epidemiology. Respirology, 8, 9-14
- de Groot, R. J., Baker, S. C., Baric, R. S., Brown, C. S., Drosten, C., Enjuanes, L., ... & Perlman, S. (2013), “Commentary: Middle East respiratory syndrome coronavirus (MERS-CoV): announcement of the Coronavirus Study Group. Journal of Virology, 87(14), 7790-7792
- Dokuz8haber, COVID19 - TÜrkiye Raporu, https://datastudio.google.com/u/0/reporting/1KH9kCoJoh1VgwdFbFPIbX3sONzvrOJ2k/page/fpDLB?s=i2fOJW2TkuU [Erişim Tarihi : 20.04.2020]
- Er, A. G. and Ünal, S. (2020). 2019 koronavirüs salgını–anlık durum ve ilk izlenimler. FLORA, 25, 1-5.
- GeoDa center, https://geodacenter.github.io/workbook/5a_global_auto/lab5a.html
- Getis, A., & Ord, J. K. (2010). The analysis of spatial association by use of distance statistics. In Perspectives on spatial data analysis (127-145). Springer, Berlin, Heidelberg
- Guliyev, H. (2020). Determining the spatial effects of COVID-19 using the spatial panel data model. Spatial Statistics, 100443. https://doi.org/10.1016/j.spasta.2020.100443
- He, F., Deng, Y., & Li, W. (2020). Coronavirus disease 2019 (COVID‐19): What we know?. Journal of Medical Virology, https://doi.org/10.1002/jmv.25766
- Kang, D., Choi, H., Kim, J. H., & Choi, J. (2020). Spatial epidemic dynamics of the COVID-19 outbreak in China. International Journal of Infectious Diseases, 94, 96-102
- Kim, D. D., & Goel, A. (2020). Estimating case fatality rates of COVID-19. The Lancet Infectious Diseases.
- Lipsitch, M. (2020). Estimating case fatality rates of COVID-19. The Lancet Infectious Diseases.
- Liu, Y., Gayle, A. A., Wilder-Smith, A., & Rocklöv, J. (2020). The reproductive number of COVID-19 is higher compared to SARS coronavirus. Journal of Travel Medicine. 27(2), 1-4.
- Lu, R., Zhao, X., Li, J., Niu, P., Yang, B., Wu, H., & Bi, Y. (2020). Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet, 395(10224), 565-574.
- Mahase, E. (2020). China coronavirus: what do we know so far?. BMJ 2020, 368 doi: https://doi.org/10.1136/bmj.m308
- Moran, P. A. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B (Methodological), 10(2), 243-251.
- Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17-23.
- Rabi, F. A., Al Zoubi, M. S., Kasasbeh, G. A., Salameh, D. M., & Al-Nasser, A. D. (2020). SARS-CoV-2 and Coronavirus Disease 2019: What We Know So Far. Pathogens, 9(3), 1-14.
- Roser, M, Ritchie, H, Ortiz-Ospina, E., and Hasell, J. (2020). Coronavirus disease (COVID-19). Published online at OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/coronavirus' [Çevrimiçi Kaynak],
- Zhou, P., Yang, X. L., Wang, X. G., Hu, B., Zhang, L., Zhang, W., & Chen, H. D. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579(7798), 270-273.
- Zumla, A., Chan, J. F., Azhar, E. I., Hui, D. S., & Yuen, K. Y. (2016). Coronaviruses-drug discovery and therapeutic options. Nature Reviews Drug Discovery, 15(5), 327-347
Yıl 2020,
Cilt: 4 Sayı: 2, 27 - 40, 28.12.2020
Öz
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, Tekirdağ, 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.
Anahtar Kelimeler
COVID-19 spatial autocorrelation hot-spot cold spots Moran I LISA Turkey
Kaynakça
- Al-Ahmadi, K., & Al-Zahrani, A. (2013). Spatial autocorrelation of cancer incidence in Saudi Arabia. International Journal of Environmental Research and Public Health, 10(12), 7207-7228.
- Anselin L. (1988) Spatial Econometrics: Methods and Models. Kluwer Academic Publishers, Dordrecht
- Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical analysis, 27(2), 93-115.
- Baud, D., Qi, X., Nielsen-Saines, K., Musso, D., Pomar, L., & Favre, G. (2020). Real estimates of mortality following COVID-19 infection. The Lancet Infectious Diseases, 20(7), https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30195-X/fulltext?fbclid=IwAR2V4jsykeM-R5lsAjcksGvmw4zYCutcVqLd9btqQkIsldVRoNedkBKDMNs
- Bhunia, G. S., Kesari, S., Chatterjee, N., Kumar, V., & Das, P. (2013). Spatial and temporal variation and hotspot detection of kala-azar disease in Vaishali district (Bihar), India. BMC Infectious Diseases, 13(1), 1-12.
- Chaikaew, N., Tripathi, N. K., & Souris, M. (2009). Exploring spatial patterns and hotspots of diarrhea in Chiang Mai, Thailand. International Journal of Health Geographics, 8(1), 36.
- Chan-Yeung, M., & Xu, R. H. (2003). SARS: epidemiology. Respirology, 8, 9-14
- de Groot, R. J., Baker, S. C., Baric, R. S., Brown, C. S., Drosten, C., Enjuanes, L., ... & Perlman, S. (2013), “Commentary: Middle East respiratory syndrome coronavirus (MERS-CoV): announcement of the Coronavirus Study Group. Journal of Virology, 87(14), 7790-7792
- Dokuz8haber, COVID19 - TÜrkiye Raporu, https://datastudio.google.com/u/0/reporting/1KH9kCoJoh1VgwdFbFPIbX3sONzvrOJ2k/page/fpDLB?s=i2fOJW2TkuU [Erişim Tarihi : 20.04.2020]
- Er, A. G. and Ünal, S. (2020). 2019 koronavirüs salgını–anlık durum ve ilk izlenimler. FLORA, 25, 1-5.
- GeoDa center, https://geodacenter.github.io/workbook/5a_global_auto/lab5a.html
- Getis, A., & Ord, J. K. (2010). The analysis of spatial association by use of distance statistics. In Perspectives on spatial data analysis (127-145). Springer, Berlin, Heidelberg
- Guliyev, H. (2020). Determining the spatial effects of COVID-19 using the spatial panel data model. Spatial Statistics, 100443. https://doi.org/10.1016/j.spasta.2020.100443
- He, F., Deng, Y., & Li, W. (2020). Coronavirus disease 2019 (COVID‐19): What we know?. Journal of Medical Virology, https://doi.org/10.1002/jmv.25766
- Kang, D., Choi, H., Kim, J. H., & Choi, J. (2020). Spatial epidemic dynamics of the COVID-19 outbreak in China. International Journal of Infectious Diseases, 94, 96-102
- Kim, D. D., & Goel, A. (2020). Estimating case fatality rates of COVID-19. The Lancet Infectious Diseases.
- Lipsitch, M. (2020). Estimating case fatality rates of COVID-19. The Lancet Infectious Diseases.
- Liu, Y., Gayle, A. A., Wilder-Smith, A., & Rocklöv, J. (2020). The reproductive number of COVID-19 is higher compared to SARS coronavirus. Journal of Travel Medicine. 27(2), 1-4.
- Lu, R., Zhao, X., Li, J., Niu, P., Yang, B., Wu, H., & Bi, Y. (2020). Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet, 395(10224), 565-574.
- Mahase, E. (2020). China coronavirus: what do we know so far?. BMJ 2020, 368 doi: https://doi.org/10.1136/bmj.m308
- Moran, P. A. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B (Methodological), 10(2), 243-251.
- Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17-23.
- Rabi, F. A., Al Zoubi, M. S., Kasasbeh, G. A., Salameh, D. M., & Al-Nasser, A. D. (2020). SARS-CoV-2 and Coronavirus Disease 2019: What We Know So Far. Pathogens, 9(3), 1-14.
- Roser, M, Ritchie, H, Ortiz-Ospina, E., and Hasell, J. (2020). Coronavirus disease (COVID-19). Published online at OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/coronavirus' [Çevrimiçi Kaynak],
- Zhou, P., Yang, X. L., Wang, X. G., Hu, B., Zhang, L., Zhang, W., & Chen, H. D. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579(7798), 270-273.
- Zumla, A., Chan, J. F., Azhar, E. I., Hui, D. S., & Yuen, K. Y. (2016). Coronaviruses-drug discovery and therapeutic options. Nature Reviews Drug Discovery, 15(5), 327-347
Toplam 26 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 28 Aralık 2020 |
| Gönderilme Tarihi | 1 Eylül 2020 |
| Yayımlandığı Sayı | Yıl 2020 Cilt: 4 Sayı: 2 |
