AI Article Synopsis
- The study examines how socio-economic factors influenced the spread of COVID-19 across the 155 urban areas (UAs) in Rome in 2019.
- It employs a spatial data model to analyze the direct and indirect effects of neighboring UAs, highlighting the importance of geographic proximity.
- A geodatabase (GDB) was created through digital geocoding, enabling the integration of statistical data with geographic layers for better spatial analysis of the virus's spread.
Article Abstract
The study investigates the spread of the effects of COVID in 2019 in the city of Rome, focusing on the socio-economic factors that affect the incidence of the virus in the 155 urban areas (UAs) of the city. The units of analysis of this study are the UAs. The survey emphasizes the weight of spatial contiguity between the 155 UAs. For this purpose, the spatial data model analyses the spillover between contiguous units of analysis, distinguishing direct and indirect spatial effects. Digital geocoding of the collected data has been performed to create a geodatabase (GDB) that allows the statistical information to be turned into geographic layers. Geographic layers represent information layers that can be overlapped with each other on the map of Rome. The database allowed the variables to be handled with spatial analysis methods. This emphasizes the usefulness of digital analysis methods for the study of such a complex and rapidly changing phenomenon as the spread of SARS-CoV-19 infection on an urban scale.
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Source |
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9704721 | PMC |
| http://dx.doi.org/10.3389/fsoc.2022.1066396 | DOI Listing |
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