Yayın: Spatiotemporal pattern of COVID-19 outbreak in Turkey
| dc.contributor.author | Aral, Neşe | |
| dc.contributor.author | Bakır, Hasan | |
| dc.contributor.buuauthor | ARAL, NEŞE | |
| dc.contributor.buuauthor | BAKIR, HASAN | |
| dc.contributor.department | Sosyal Bilimler Meslek Yüksekokulu | |
| dc.contributor.department | İktisadi ve İdari Bilimler Fakültesi | |
| dc.contributor.department | Uluslararası Ticaret Bilim Dalı | |
| dc.contributor.department | Ekonometri Bölümü | |
| dc.contributor.orcid | 0000-0001-7599-5047 | |
| dc.contributor.orcid | 0000-0002-8248-6643 | |
| dc.contributor.researcherid | ABD-2939-2020 | |
| dc.contributor.researcherid | JEI-2603-2023 | |
| dc.date.accessioned | 2024-10-11T05:37:55Z | |
| dc.date.available | 2024-10-11T05:37:55Z | |
| dc.date.issued | 2022-06-16 | |
| dc.description.abstract | The earliest case of Covid-19 was documented in Wuhan city of China and since then the virus has been spreading throughout the globe. The aim of this study is to evaluate the clusters of Covid-19 among the provinces in Turkey and to examine whether the clustering pattern has changed after the country's lockdown strategy. The spatial dependence of Covid-19 in 81 provinces of Turkey was examined by spatial analysis between February 8 and June 28, 2021. Global and Local Moran's I and Gi* were employed to measure the global and local spatial autocorrelation degrees. The geographical distribution of Covid-19 in the provinces of Turkey showed a strong spatial autocorrelation while the spatial structure of the clusters varied by weeks. The findings of the study show that the complete lockdown carried out in Turkey has been quite effective in mitigating Covid-19. The importance of spatial relations in preventing the spread of the disease in Turkey has also been demonstrated in this context. | |
| dc.identifier.doi | 10.1007/s10708-022-10666-9 | |
| dc.identifier.eissn | 1572-9893 | |
| dc.identifier.endpage | 1316 | |
| dc.identifier.issn | 0343-2521 | |
| dc.identifier.issue | 2 | |
| dc.identifier.scopus | 2-s2.0-85132282371 | |
| dc.identifier.startpage | 1305 | |
| dc.identifier.uri | https://doi.org/10.1007/s10708-022-10666-9 | |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s10708-022-10666-9 | |
| dc.identifier.uri | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200931/ | |
| dc.identifier.uri | https://hdl.handle.net/11452/46238 | |
| dc.identifier.volume | 88 | |
| dc.identifier.wos | 000811960100001 | |
| dc.indexed.wos | WOS.ESCI | |
| dc.language.iso | en | |
| dc.publisher | Springer | |
| dc.relation.journal | Geojournal | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Local spatial autocorrelation | |
| dc.subject | Sars epidemic | |
| dc.subject | Association | |
| dc.subject | Dynamics | |
| dc.subject | Health | |
| dc.subject | Gis | |
| dc.subject | Covid-19 | |
| dc.subject | Turkey | |
| dc.subject | Spatial statistics | |
| dc.subject | Spatial autocorelation | |
| dc.subject | Spatiotemporal pattern | |
| dc.subject | Social sciences | |
| dc.subject | Geography | |
| dc.title | Spatiotemporal pattern of COVID-19 outbreak in Turkey | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| local.contributor.department | İktisadi ve İdari Bilimler Fakültesi/Ekonometri Bölümü | |
| local.contributor.department | Sosyal Bilimler Meslek Yüksekokulu/Uluslararası Ticaret Bilim Dalı | |
| local.indexed.at | WOS | |
| local.indexed.at | Scopus | |
| relation.isAuthorOfPublication | 568b539a-b9a0-44ac-9d78-3cead8124c2e | |
| relation.isAuthorOfPublication | 638b130e-daa2-4824-84ef-44d11fc4ac67 | |
| relation.isAuthorOfPublication.latestForDiscovery | 568b539a-b9a0-44ac-9d78-3cead8124c2e |
Dosyalar
Orijinal seri
1 - 1 / 1
