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Spatio-temporal patterns of the COVID-19 pandemic, and place-based influential factors at the neighborhood scale in Tehran by Azadeh Lak; Ayyoob Sharifi; Siamak Badr; Alireza Zali; Ali Maher; Ehsan Mostafavi; Davood Khalili is a Environmental Science article available to read on EtoBox.
What is Spatio-temporal patterns of the COVID-19 pandemic, and place-based influential factors at the neighborhood scale in Tehran about?
Since its emergence in late 2019, the COVID-19 pandemic has attracted the attention of researchers in various fields, including urban planning and design. However, the spreading patterns of the disease in cities are still not clear. Historically, preventing and controlling pandemics in cities has always been challenging due to various factors such as higher population density, higher mobility of people, and higher contact frequency. To shed more light on the spread patterns of the pandemic, in this study we analyze 43,000 confirmed COVID-19 cases at the neighborhood level in Tehran, the capital of Iran. To examine spatio-temporal patterns and place-based factors contributing to the spread of the pandemic, we used exploratory spatial data analysis and spatial regression. We developed a geo-referenced database composed of 12 quantitative place-based variables related to physical attributes, land use and public transportation facilities, and demographic status. We also used the geographically weighted regression model for the local examination of spatial non-stationarity. According to the results, population density (R2 = 0.88) and distribution of neighborhood centers (R2 = 0.59), dru
Who reads Spatio-temporal patterns of the COVID-19 pandemic, and place-based influential factors at the neighborhood scale in Tehran?
It is typically read by researchers, students, and practitioners in Environmental Science.
- Author
- Azadeh Lak; Ayyoob Sharifi; Siamak Badr; Alireza Zali; Ali Maher; Ehsan Mostafavi; Davood Khalili
- Publisher
- Elsevier BV
- Published
- 2021
- Language
- EN
- Field
- Environmental Science (Physical Sciences)