| Title: |
A Downscaling Approach to Compare COVID-19 Count Data from Databases Aggregated at Different Spatial Scales |
| Authors: |
Python, Andre; Bender, Andreas; Blangiardo, Marta; Illian, Janine B.; Lin, Ying; Liu, Baoli; Lucas, Tim C.D.; Tan, Siwei; Wen, Yingying; Svanidze, Davit; Yin, Jianwei |
| Contributors: |
Zhejiang University Educational Funding; Zhejiang University Global Partnership Fund; Zhejiang University Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China; The Royal Society, United Kingdom; German Federal Ministry of Education and Research |
| Source: |
Journal of the Royal Statistical Society Series A: Statistics in Society ; volume 185, issue 1, page 202-218 ; ISSN 0964-1998 1467-985X |
| Publisher Information: |
Oxford University Press (OUP) |
| Publication Year: |
2021 |
| Description: |
As the COVID-19 pandemic continues to threaten various regions around the world, obtaining accurate and reliable COVID-19 data is crucial for governments and local communities aiming at rigorously assessing the extent and magnitude of the virus spread and deploying efficient interventions. Using data reported between January and February 2020 in China, we compared counts of COVID-19 from near-real-time spatially disaggregated data (city level) with fine-spatial scale predictions from a Bayesian downscaling regression model applied to a reference province-level data set. The results highlight discrepancies in the counts of coronavirus-infected cases at the district level and identify districts that may require further investigation. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1111/rssa.12738 |
| Availability: |
https://doi.org/10.1111/rssa.12738; https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssa.12738; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/rssa.12738; https://academic.oup.com/jrsssa/article-pdf/185/1/202/49412072/jrsssa_185_1_202.pdf |
| Rights: |
https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model |
| Accession Number: |
edsbas.FF3BA58B |
| Database: |
BASE |